Add stuck initiatives audit report
This commit is contained in:
Ezra
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---
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name: code-review
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description: Guidelines for performing thorough code reviews with security and quality focus
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---
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# Code Review Skill
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Use this skill when reviewing code changes, pull requests, or auditing existing code.
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## Review Checklist
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### 1. Security First
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- [ ] No hardcoded secrets, API keys, or credentials
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- [ ] Input validation on all user-provided data
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- [ ] SQL queries use parameterized statements (no string concatenation)
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- [ ] File operations validate paths (no path traversal)
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- [ ] Authentication/authorization checks present where needed
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### 2. Error Handling
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- [ ] All external calls (API, DB, file) have try/catch
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- [ ] Errors are logged with context (but no sensitive data)
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- [ ] User-facing errors are helpful but don't leak internals
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- [ ] Resources are cleaned up in finally blocks or context managers
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### 3. Code Quality
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- [ ] Functions do one thing and are reasonably sized (<50 lines ideal)
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- [ ] Variable names are descriptive (no single letters except loops)
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- [ ] No commented-out code left behind
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- [ ] Complex logic has explanatory comments
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- [ ] No duplicate code (DRY principle)
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### 4. Testing Considerations
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- [ ] Edge cases handled (empty inputs, nulls, boundaries)
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- [ ] Happy path and error paths both work
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- [ ] New code has corresponding tests (if test suite exists)
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## Review Response Format
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When providing review feedback, structure it as:
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```
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## Summary
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[1-2 sentence overall assessment]
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## Critical Issues (Must Fix)
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- Issue 1: [description + suggested fix]
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- Issue 2: ...
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## Suggestions (Nice to Have)
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- Suggestion 1: [description]
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## Questions
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- [Any clarifying questions about intent]
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```
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## Common Patterns to Flag
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### Python
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```python
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# Bad: SQL injection risk
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cursor.execute(f"SELECT * FROM users WHERE id = {user_id}")
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# Good: Parameterized query
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cursor.execute("SELECT * FROM users WHERE id = ?", (user_id,))
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```
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### JavaScript
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```javascript
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// Bad: XSS risk
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element.innerHTML = userInput;
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// Good: Safe text content
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element.textContent = userInput;
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```
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## Tone Guidelines
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- Be constructive, not critical
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- Explain *why* something is an issue, not just *what*
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- Offer solutions, not just problems
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- Acknowledge good patterns you see
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57
protected/skills-backup/software-development/plan/SKILL.md
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57
protected/skills-backup/software-development/plan/SKILL.md
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---
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name: plan
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description: Plan mode for Hermes — inspect context, write a markdown plan into the active workspace's `.hermes/plans/` directory, and do not execute the work.
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version: 1.0.0
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author: Hermes Agent
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license: MIT
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metadata:
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hermes:
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tags: [planning, plan-mode, implementation, workflow]
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related_skills: [writing-plans, subagent-driven-development]
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---
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# Plan Mode
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Use this skill when the user wants a plan instead of execution.
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## Core behavior
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For this turn, you are planning only.
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- Do not implement code.
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- Do not edit project files except the plan markdown file.
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- Do not run mutating terminal commands, commit, push, or perform external actions.
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- You may inspect the repo or other context with read-only commands/tools when needed.
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- Your deliverable is a markdown plan saved inside the active workspace under `.hermes/plans/`.
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## Output requirements
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Write a markdown plan that is concrete and actionable.
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Include, when relevant:
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- Goal
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- Current context / assumptions
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- Proposed approach
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- Step-by-step plan
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- Files likely to change
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- Tests / validation
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- Risks, tradeoffs, and open questions
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If the task is code-related, include exact file paths, likely test targets, and verification steps.
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## Save location
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Save the plan with `write_file` under:
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- `.hermes/plans/YYYY-MM-DD_HHMMSS-<slug>.md`
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Treat that as relative to the active working directory / backend workspace. Hermes file tools are backend-aware, so using this relative path keeps the plan with the workspace on local, docker, ssh, modal, and daytona backends.
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If the runtime provides a specific target path, use that exact path.
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If not, create a sensible timestamped filename yourself under `.hermes/plans/`.
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## Interaction style
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- If the request is clear enough, write the plan directly.
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- If no explicit instruction accompanies `/plan`, infer the task from the current conversation context.
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- If it is genuinely underspecified, ask a brief clarifying question instead of guessing.
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- After saving the plan, reply briefly with what you planned and the saved path.
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---
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name: requesting-code-review
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description: Use when completing tasks, implementing major features, or before merging. Validates work meets requirements through systematic review process.
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version: 1.1.0
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author: Hermes Agent (adapted from obra/superpowers)
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license: MIT
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metadata:
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hermes:
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tags: [code-review, quality, validation, workflow, review]
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related_skills: [subagent-driven-development, writing-plans, test-driven-development]
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---
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# Requesting Code Review
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## Overview
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Dispatch a reviewer subagent to catch issues before they cascade. Review early, review often.
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**Core principle:** Fresh perspective finds issues you'll miss.
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## When to Request Review
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**Mandatory:**
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- After each task in subagent-driven development
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- After completing a major feature
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- Before merge to main
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- After bug fixes
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**Optional but valuable:**
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- When stuck (fresh perspective)
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- Before refactoring (baseline check)
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- After complex logic implementation
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- When touching critical code (auth, payments, data)
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**Never skip because:**
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- "It's simple" — simple bugs compound
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- "I'm in a hurry" — reviews save time
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- "I tested it" — you have blind spots
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## Review Process
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### Step 1: Self-Review First
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Before dispatching a reviewer, check yourself:
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- [ ] Code follows project conventions
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- [ ] All tests pass
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- [ ] No debug print statements left
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- [ ] No hardcoded secrets or credentials
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- [ ] Error handling in place
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- [ ] Commit messages are clear
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```bash
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# Run full test suite
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pytest tests/ -q
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# Check for debug code
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search_files("print(", path="src/", file_glob="*.py")
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search_files("console.log", path="src/", file_glob="*.js")
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# Check for TODOs
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search_files("TODO|FIXME|HACK", path="src/")
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```
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### Step 2: Gather Context
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```bash
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# Changed files
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git diff --name-only HEAD~1
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# Diff summary
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git diff --stat HEAD~1
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# Recent commits
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git log --oneline -5
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```
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### Step 3: Dispatch Reviewer Subagent
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Use `delegate_task` to dispatch a focused reviewer:
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```python
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delegate_task(
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goal="Review implementation for correctness and quality",
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context="""
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WHAT WAS IMPLEMENTED:
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[Brief description of the feature/fix]
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ORIGINAL REQUIREMENTS:
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[From plan, issue, or user request]
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FILES CHANGED:
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- src/models/user.py (added User class)
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- src/auth/login.py (added login endpoint)
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- tests/test_auth.py (added 8 tests)
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REVIEW CHECKLIST:
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- [ ] Correctness: Does it do what it should?
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- [ ] Edge cases: Are they handled?
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- [ ] Error handling: Is it adequate?
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- [ ] Code quality: Clear names, good structure?
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- [ ] Test coverage: Are tests meaningful?
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- [ ] Security: Any vulnerabilities?
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- [ ] Performance: Any obvious issues?
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OUTPUT FORMAT:
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- Summary: [brief assessment]
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- Critical Issues: [must fix — blocks merge]
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- Important Issues: [should fix before merge]
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- Minor Issues: [nice to have]
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- Strengths: [what was done well]
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- Verdict: APPROVE / REQUEST_CHANGES
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""",
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toolsets=['file']
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)
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```
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### Step 4: Act on Feedback
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**Critical Issues (block merge):**
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- Security vulnerabilities
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- Broken functionality
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- Data loss risk
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- Test failures
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- **Action:** Fix immediately before proceeding
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**Important Issues (should fix):**
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- Missing edge case handling
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- Poor error messages
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- Unclear code
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- Missing tests
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- **Action:** Fix before merge if possible
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**Minor Issues (nice to have):**
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- Style preferences
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- Refactoring suggestions
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- Documentation improvements
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- **Action:** Note for later or quick fix
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**If reviewer is wrong:**
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- Push back with technical reasoning
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- Show code/tests that prove it works
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- Request clarification
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## Review Dimensions
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### Correctness
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- Does it implement the requirements?
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- Are there logic errors?
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- Do edge cases work?
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- Are there race conditions?
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### Code Quality
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- Is code readable?
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- Are names clear and descriptive?
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- Is it too complex? (Functions >20 lines = smell)
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- Is there duplication?
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### Testing
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- Are there meaningful tests?
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- Do they cover edge cases?
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- Do they test behavior, not implementation?
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- Do all tests pass?
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### Security
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- Any injection vulnerabilities?
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- Proper input validation?
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- Secrets handled correctly?
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- Access control in place?
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### Performance
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- Any N+1 queries?
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- Unnecessary computation in loops?
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- Memory leaks?
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- Missing caching opportunities?
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## Review Output Format
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Standard format for reviewer subagent output:
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```markdown
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## Review Summary
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**Assessment:** [Brief overall assessment]
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**Verdict:** APPROVE / REQUEST_CHANGES
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---
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## Critical Issues (Fix Required)
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1. **[Issue title]**
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- Location: `file.py:45`
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- Problem: [Description]
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- Suggestion: [How to fix]
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## Important Issues (Should Fix)
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1. **[Issue title]**
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- Location: `file.py:67`
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- Problem: [Description]
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- Suggestion: [How to fix]
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## Minor Issues (Optional)
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1. **[Issue title]**
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- Suggestion: [Improvement idea]
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## Strengths
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- [What was done well]
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```
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## Integration with Other Skills
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### With subagent-driven-development
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Review after EACH task — this is the two-stage review:
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1. Spec compliance review (does it match the plan?)
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2. Code quality review (is it well-built?)
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3. Fix issues from either review
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4. Proceed to next task only when both approve
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### With test-driven-development
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Review verifies:
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- Tests were written first (RED-GREEN-REFACTOR followed?)
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- Tests are meaningful (not just asserting True)?
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- Edge cases covered?
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- All tests pass?
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### With writing-plans
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Review validates:
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- Implementation matches the plan?
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- All tasks completed?
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- Quality standards met?
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## Red Flags
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**Never:**
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- Skip review because "it's simple"
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- Ignore Critical issues
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- Proceed with unfixed Important issues
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- Argue with valid technical feedback without evidence
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## Quality Gates
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**Must pass before merge:**
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- [ ] No critical issues
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- [ ] All tests pass
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- [ ] Review verdict: APPROVE
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- [ ] Requirements met
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**Should pass before merge:**
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- [ ] No important issues
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- [ ] Documentation updated
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- [ ] Performance acceptable
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## Remember
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```
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Review early
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Review often
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Be specific
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Fix critical issues first
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Quality over speed
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```
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**A good review catches what you missed.**
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@@ -0,0 +1,342 @@
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---
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name: subagent-driven-development
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description: Use when executing implementation plans with independent tasks. Dispatches fresh delegate_task per task with two-stage review (spec compliance then code quality).
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version: 1.1.0
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author: Hermes Agent (adapted from obra/superpowers)
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license: MIT
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metadata:
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hermes:
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tags: [delegation, subagent, implementation, workflow, parallel]
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related_skills: [writing-plans, requesting-code-review, test-driven-development]
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---
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# Subagent-Driven Development
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## Overview
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Execute implementation plans by dispatching fresh subagents per task with systematic two-stage review.
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**Core principle:** Fresh subagent per task + two-stage review (spec then quality) = high quality, fast iteration.
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## When to Use
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Use this skill when:
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- You have an implementation plan (from writing-plans skill or user requirements)
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- Tasks are mostly independent
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- Quality and spec compliance are important
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- You want automated review between tasks
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**vs. manual execution:**
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- Fresh context per task (no confusion from accumulated state)
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- Automated review process catches issues early
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- Consistent quality checks across all tasks
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- Subagents can ask questions before starting work
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## The Process
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### 1. Read and Parse Plan
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Read the plan file. Extract ALL tasks with their full text and context upfront. Create a todo list:
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```python
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# Read the plan
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read_file("docs/plans/feature-plan.md")
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# Create todo list with all tasks
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todo([
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{"id": "task-1", "content": "Create User model with email field", "status": "pending"},
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{"id": "task-2", "content": "Add password hashing utility", "status": "pending"},
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{"id": "task-3", "content": "Create login endpoint", "status": "pending"},
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])
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```
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**Key:** Read the plan ONCE. Extract everything. Don't make subagents read the plan file — provide the full task text directly in context.
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### 2. Per-Task Workflow
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For EACH task in the plan:
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#### Step 1: Dispatch Implementer Subagent
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Use `delegate_task` with complete context:
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```python
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delegate_task(
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goal="Implement Task 1: Create User model with email and password_hash fields",
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context="""
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TASK FROM PLAN:
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- Create: src/models/user.py
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- Add User class with email (str) and password_hash (str) fields
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- Use bcrypt for password hashing
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- Include __repr__ for debugging
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FOLLOW TDD:
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1. Write failing test in tests/models/test_user.py
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2. Run: pytest tests/models/test_user.py -v (verify FAIL)
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3. Write minimal implementation
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4. Run: pytest tests/models/test_user.py -v (verify PASS)
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5. Run: pytest tests/ -q (verify no regressions)
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6. Commit: git add -A && git commit -m "feat: add User model with password hashing"
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||||
PROJECT CONTEXT:
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- Python 3.11, Flask app in src/app.py
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- Existing models in src/models/
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- Tests use pytest, run from project root
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||||
- bcrypt already in requirements.txt
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""",
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||||
toolsets=['terminal', 'file']
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||||
)
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||||
```
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||||
#### Step 2: Dispatch Spec Compliance Reviewer
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||||
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||||
After the implementer completes, verify against the original spec:
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||||
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```python
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||||
delegate_task(
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goal="Review if implementation matches the spec from the plan",
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||||
context="""
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||||
ORIGINAL TASK SPEC:
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- Create src/models/user.py with User class
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- Fields: email (str), password_hash (str)
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- Use bcrypt for password hashing
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- Include __repr__
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||||
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||||
CHECK:
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||||
- [ ] All requirements from spec implemented?
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||||
- [ ] File paths match spec?
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||||
- [ ] Function signatures match spec?
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||||
- [ ] Behavior matches expected?
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||||
- [ ] Nothing extra added (no scope creep)?
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||||
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||||
OUTPUT: PASS or list of specific spec gaps to fix.
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||||
""",
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||||
toolsets=['file']
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||||
)
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||||
```
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||||
|
||||
**If spec issues found:** Fix gaps, then re-run spec review. Continue only when spec-compliant.
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||||
|
||||
#### Step 3: Dispatch Code Quality Reviewer
|
||||
|
||||
After spec compliance passes:
|
||||
|
||||
```python
|
||||
delegate_task(
|
||||
goal="Review code quality for Task 1 implementation",
|
||||
context="""
|
||||
FILES TO REVIEW:
|
||||
- src/models/user.py
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||||
- tests/models/test_user.py
|
||||
|
||||
CHECK:
|
||||
- [ ] Follows project conventions and style?
|
||||
- [ ] Proper error handling?
|
||||
- [ ] Clear variable/function names?
|
||||
- [ ] Adequate test coverage?
|
||||
- [ ] No obvious bugs or missed edge cases?
|
||||
- [ ] No security issues?
|
||||
|
||||
OUTPUT FORMAT:
|
||||
- Critical Issues: [must fix before proceeding]
|
||||
- Important Issues: [should fix]
|
||||
- Minor Issues: [optional]
|
||||
- Verdict: APPROVED or REQUEST_CHANGES
|
||||
""",
|
||||
toolsets=['file']
|
||||
)
|
||||
```
|
||||
|
||||
**If quality issues found:** Fix issues, re-review. Continue only when approved.
|
||||
|
||||
#### Step 4: Mark Complete
|
||||
|
||||
```python
|
||||
todo([{"id": "task-1", "content": "Create User model with email field", "status": "completed"}], merge=True)
|
||||
```
|
||||
|
||||
### 3. Final Review
|
||||
|
||||
After ALL tasks are complete, dispatch a final integration reviewer:
|
||||
|
||||
```python
|
||||
delegate_task(
|
||||
goal="Review the entire implementation for consistency and integration issues",
|
||||
context="""
|
||||
All tasks from the plan are complete. Review the full implementation:
|
||||
- Do all components work together?
|
||||
- Any inconsistencies between tasks?
|
||||
- All tests passing?
|
||||
- Ready for merge?
|
||||
""",
|
||||
toolsets=['terminal', 'file']
|
||||
)
|
||||
```
|
||||
|
||||
### 4. Verify and Commit
|
||||
|
||||
```bash
|
||||
# Run full test suite
|
||||
pytest tests/ -q
|
||||
|
||||
# Review all changes
|
||||
git diff --stat
|
||||
|
||||
# Final commit if needed
|
||||
git add -A && git commit -m "feat: complete [feature name] implementation"
|
||||
```
|
||||
|
||||
## Task Granularity
|
||||
|
||||
**Each task = 2-5 minutes of focused work.**
|
||||
|
||||
**Too big:**
|
||||
- "Implement user authentication system"
|
||||
|
||||
**Right size:**
|
||||
- "Create User model with email and password fields"
|
||||
- "Add password hashing function"
|
||||
- "Create login endpoint"
|
||||
- "Add JWT token generation"
|
||||
- "Create registration endpoint"
|
||||
|
||||
## Red Flags — Never Do These
|
||||
|
||||
- Start implementation without a plan
|
||||
- Skip reviews (spec compliance OR code quality)
|
||||
- Proceed with unfixed critical/important issues
|
||||
- Dispatch multiple implementation subagents for tasks that touch the same files
|
||||
- Make subagent read the plan file (provide full text in context instead)
|
||||
- Skip scene-setting context (subagent needs to understand where the task fits)
|
||||
- Ignore subagent questions (answer before letting them proceed)
|
||||
- Accept "close enough" on spec compliance
|
||||
- Skip review loops (reviewer found issues → implementer fixes → review again)
|
||||
- Let implementer self-review replace actual review (both are needed)
|
||||
- **Start code quality review before spec compliance is PASS** (wrong order)
|
||||
- Move to next task while either review has open issues
|
||||
|
||||
## Handling Issues
|
||||
|
||||
### If Subagent Asks Questions
|
||||
|
||||
- Answer clearly and completely
|
||||
- Provide additional context if needed
|
||||
- Don't rush them into implementation
|
||||
|
||||
### If Reviewer Finds Issues
|
||||
|
||||
- Implementer subagent (or a new one) fixes them
|
||||
- Reviewer reviews again
|
||||
- Repeat until approved
|
||||
- Don't skip the re-review
|
||||
|
||||
### If Subagent Fails a Task
|
||||
|
||||
- Dispatch a new fix subagent with specific instructions about what went wrong
|
||||
- Don't try to fix manually in the controller session (context pollution)
|
||||
|
||||
## Efficiency Notes
|
||||
|
||||
**Why fresh subagent per task:**
|
||||
- Prevents context pollution from accumulated state
|
||||
- Each subagent gets clean, focused context
|
||||
- No confusion from prior tasks' code or reasoning
|
||||
|
||||
**Why two-stage review:**
|
||||
- Spec review catches under/over-building early
|
||||
- Quality review ensures the implementation is well-built
|
||||
- Catches issues before they compound across tasks
|
||||
|
||||
**Cost trade-off:**
|
||||
- More subagent invocations (implementer + 2 reviewers per task)
|
||||
- But catches issues early (cheaper than debugging compounded problems later)
|
||||
|
||||
## Integration with Other Skills
|
||||
|
||||
### With writing-plans
|
||||
|
||||
This skill EXECUTES plans created by the writing-plans skill:
|
||||
1. User requirements → writing-plans → implementation plan
|
||||
2. Implementation plan → subagent-driven-development → working code
|
||||
|
||||
### With test-driven-development
|
||||
|
||||
Implementer subagents should follow TDD:
|
||||
1. Write failing test first
|
||||
2. Implement minimal code
|
||||
3. Verify test passes
|
||||
4. Commit
|
||||
|
||||
Include TDD instructions in every implementer context.
|
||||
|
||||
### With requesting-code-review
|
||||
|
||||
The two-stage review process IS the code review. For final integration review, use the requesting-code-review skill's review dimensions.
|
||||
|
||||
### With systematic-debugging
|
||||
|
||||
If a subagent encounters bugs during implementation:
|
||||
1. Follow systematic-debugging process
|
||||
2. Find root cause before fixing
|
||||
3. Write regression test
|
||||
4. Resume implementation
|
||||
|
||||
## Example Workflow
|
||||
|
||||
```
|
||||
[Read plan: docs/plans/auth-feature.md]
|
||||
[Create todo list with 5 tasks]
|
||||
|
||||
--- Task 1: Create User model ---
|
||||
[Dispatch implementer subagent]
|
||||
Implementer: "Should email be unique?"
|
||||
You: "Yes, email must be unique"
|
||||
Implementer: Implemented, 3/3 tests passing, committed.
|
||||
|
||||
[Dispatch spec reviewer]
|
||||
Spec reviewer: ✅ PASS — all requirements met
|
||||
|
||||
[Dispatch quality reviewer]
|
||||
Quality reviewer: ✅ APPROVED — clean code, good tests
|
||||
|
||||
[Mark Task 1 complete]
|
||||
|
||||
--- Task 2: Password hashing ---
|
||||
[Dispatch implementer subagent]
|
||||
Implementer: No questions, implemented, 5/5 tests passing.
|
||||
|
||||
[Dispatch spec reviewer]
|
||||
Spec reviewer: ❌ Missing: password strength validation (spec says "min 8 chars")
|
||||
|
||||
[Implementer fixes]
|
||||
Implementer: Added validation, 7/7 tests passing.
|
||||
|
||||
[Dispatch spec reviewer again]
|
||||
Spec reviewer: ✅ PASS
|
||||
|
||||
[Dispatch quality reviewer]
|
||||
Quality reviewer: Important: Magic number 8, extract to constant
|
||||
Implementer: Extracted MIN_PASSWORD_LENGTH constant
|
||||
Quality reviewer: ✅ APPROVED
|
||||
|
||||
[Mark Task 2 complete]
|
||||
|
||||
... (continue for all tasks)
|
||||
|
||||
[After all tasks: dispatch final integration reviewer]
|
||||
[Run full test suite: all passing]
|
||||
[Done!]
|
||||
```
|
||||
|
||||
## Remember
|
||||
|
||||
```
|
||||
Fresh subagent per task
|
||||
Two-stage review every time
|
||||
Spec compliance FIRST
|
||||
Code quality SECOND
|
||||
Never skip reviews
|
||||
Catch issues early
|
||||
```
|
||||
|
||||
**Quality is not an accident. It's the result of systematic process.**
|
||||
@@ -0,0 +1,366 @@
|
||||
---
|
||||
name: systematic-debugging
|
||||
description: Use when encountering any bug, test failure, or unexpected behavior. 4-phase root cause investigation — NO fixes without understanding the problem first.
|
||||
version: 1.1.0
|
||||
author: Hermes Agent (adapted from obra/superpowers)
|
||||
license: MIT
|
||||
metadata:
|
||||
hermes:
|
||||
tags: [debugging, troubleshooting, problem-solving, root-cause, investigation]
|
||||
related_skills: [test-driven-development, writing-plans, subagent-driven-development]
|
||||
---
|
||||
|
||||
# Systematic Debugging
|
||||
|
||||
## Overview
|
||||
|
||||
Random fixes waste time and create new bugs. Quick patches mask underlying issues.
|
||||
|
||||
**Core principle:** ALWAYS find root cause before attempting fixes. Symptom fixes are failure.
|
||||
|
||||
**Violating the letter of this process is violating the spirit of debugging.**
|
||||
|
||||
## The Iron Law
|
||||
|
||||
```
|
||||
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
|
||||
```
|
||||
|
||||
If you haven't completed Phase 1, you cannot propose fixes.
|
||||
|
||||
## When to Use
|
||||
|
||||
Use for ANY technical issue:
|
||||
- Test failures
|
||||
- Bugs in production
|
||||
- Unexpected behavior
|
||||
- Performance problems
|
||||
- Build failures
|
||||
- Integration issues
|
||||
|
||||
**Use this ESPECIALLY when:**
|
||||
- Under time pressure (emergencies make guessing tempting)
|
||||
- "Just one quick fix" seems obvious
|
||||
- You've already tried multiple fixes
|
||||
- Previous fix didn't work
|
||||
- You don't fully understand the issue
|
||||
|
||||
**Don't skip when:**
|
||||
- Issue seems simple (simple bugs have root causes too)
|
||||
- You're in a hurry (rushing guarantees rework)
|
||||
- Someone wants it fixed NOW (systematic is faster than thrashing)
|
||||
|
||||
## The Four Phases
|
||||
|
||||
You MUST complete each phase before proceeding to the next.
|
||||
|
||||
---
|
||||
|
||||
## Phase 1: Root Cause Investigation
|
||||
|
||||
**BEFORE attempting ANY fix:**
|
||||
|
||||
### 1. Read Error Messages Carefully
|
||||
|
||||
- Don't skip past errors or warnings
|
||||
- They often contain the exact solution
|
||||
- Read stack traces completely
|
||||
- Note line numbers, file paths, error codes
|
||||
|
||||
**Action:** Use `read_file` on the relevant source files. Use `search_files` to find the error string in the codebase.
|
||||
|
||||
### 2. Reproduce Consistently
|
||||
|
||||
- Can you trigger it reliably?
|
||||
- What are the exact steps?
|
||||
- Does it happen every time?
|
||||
- If not reproducible → gather more data, don't guess
|
||||
|
||||
**Action:** Use the `terminal` tool to run the failing test or trigger the bug:
|
||||
|
||||
```bash
|
||||
# Run specific failing test
|
||||
pytest tests/test_module.py::test_name -v
|
||||
|
||||
# Run with verbose output
|
||||
pytest tests/test_module.py -v --tb=long
|
||||
```
|
||||
|
||||
### 3. Check Recent Changes
|
||||
|
||||
- What changed that could cause this?
|
||||
- Git diff, recent commits
|
||||
- New dependencies, config changes
|
||||
|
||||
**Action:**
|
||||
|
||||
```bash
|
||||
# Recent commits
|
||||
git log --oneline -10
|
||||
|
||||
# Uncommitted changes
|
||||
git diff
|
||||
|
||||
# Changes in specific file
|
||||
git log -p --follow src/problematic_file.py | head -100
|
||||
```
|
||||
|
||||
### 4. Gather Evidence in Multi-Component Systems
|
||||
|
||||
**WHEN system has multiple components (API → service → database, CI → build → deploy):**
|
||||
|
||||
**BEFORE proposing fixes, add diagnostic instrumentation:**
|
||||
|
||||
For EACH component boundary:
|
||||
- Log what data enters the component
|
||||
- Log what data exits the component
|
||||
- Verify environment/config propagation
|
||||
- Check state at each layer
|
||||
|
||||
Run once to gather evidence showing WHERE it breaks.
|
||||
THEN analyze evidence to identify the failing component.
|
||||
THEN investigate that specific component.
|
||||
|
||||
### 5. Trace Data Flow
|
||||
|
||||
**WHEN error is deep in the call stack:**
|
||||
|
||||
- Where does the bad value originate?
|
||||
- What called this function with the bad value?
|
||||
- Keep tracing upstream until you find the source
|
||||
- Fix at the source, not at the symptom
|
||||
|
||||
**Action:** Use `search_files` to trace references:
|
||||
|
||||
```python
|
||||
# Find where the function is called
|
||||
search_files("function_name(", path="src/", file_glob="*.py")
|
||||
|
||||
# Find where the variable is set
|
||||
search_files("variable_name\\s*=", path="src/", file_glob="*.py")
|
||||
```
|
||||
|
||||
### Phase 1 Completion Checklist
|
||||
|
||||
- [ ] Error messages fully read and understood
|
||||
- [ ] Issue reproduced consistently
|
||||
- [ ] Recent changes identified and reviewed
|
||||
- [ ] Evidence gathered (logs, state, data flow)
|
||||
- [ ] Problem isolated to specific component/code
|
||||
- [ ] Root cause hypothesis formed
|
||||
|
||||
**STOP:** Do not proceed to Phase 2 until you understand WHY it's happening.
|
||||
|
||||
---
|
||||
|
||||
## Phase 2: Pattern Analysis
|
||||
|
||||
**Find the pattern before fixing:**
|
||||
|
||||
### 1. Find Working Examples
|
||||
|
||||
- Locate similar working code in the same codebase
|
||||
- What works that's similar to what's broken?
|
||||
|
||||
**Action:** Use `search_files` to find comparable patterns:
|
||||
|
||||
```python
|
||||
search_files("similar_pattern", path="src/", file_glob="*.py")
|
||||
```
|
||||
|
||||
### 2. Compare Against References
|
||||
|
||||
- If implementing a pattern, read the reference implementation COMPLETELY
|
||||
- Don't skim — read every line
|
||||
- Understand the pattern fully before applying
|
||||
|
||||
### 3. Identify Differences
|
||||
|
||||
- What's different between working and broken?
|
||||
- List every difference, however small
|
||||
- Don't assume "that can't matter"
|
||||
|
||||
### 4. Understand Dependencies
|
||||
|
||||
- What other components does this need?
|
||||
- What settings, config, environment?
|
||||
- What assumptions does it make?
|
||||
|
||||
---
|
||||
|
||||
## Phase 3: Hypothesis and Testing
|
||||
|
||||
**Scientific method:**
|
||||
|
||||
### 1. Form a Single Hypothesis
|
||||
|
||||
- State clearly: "I think X is the root cause because Y"
|
||||
- Write it down
|
||||
- Be specific, not vague
|
||||
|
||||
### 2. Test Minimally
|
||||
|
||||
- Make the SMALLEST possible change to test the hypothesis
|
||||
- One variable at a time
|
||||
- Don't fix multiple things at once
|
||||
|
||||
### 3. Verify Before Continuing
|
||||
|
||||
- Did it work? → Phase 4
|
||||
- Didn't work? → Form NEW hypothesis
|
||||
- DON'T add more fixes on top
|
||||
|
||||
### 4. When You Don't Know
|
||||
|
||||
- Say "I don't understand X"
|
||||
- Don't pretend to know
|
||||
- Ask the user for help
|
||||
- Research more
|
||||
|
||||
---
|
||||
|
||||
## Phase 4: Implementation
|
||||
|
||||
**Fix the root cause, not the symptom:**
|
||||
|
||||
### 1. Create Failing Test Case
|
||||
|
||||
- Simplest possible reproduction
|
||||
- Automated test if possible
|
||||
- MUST have before fixing
|
||||
- Use the `test-driven-development` skill
|
||||
|
||||
### 2. Implement Single Fix
|
||||
|
||||
- Address the root cause identified
|
||||
- ONE change at a time
|
||||
- No "while I'm here" improvements
|
||||
- No bundled refactoring
|
||||
|
||||
### 3. Verify Fix
|
||||
|
||||
```bash
|
||||
# Run the specific regression test
|
||||
pytest tests/test_module.py::test_regression -v
|
||||
|
||||
# Run full suite — no regressions
|
||||
pytest tests/ -q
|
||||
```
|
||||
|
||||
### 4. If Fix Doesn't Work — The Rule of Three
|
||||
|
||||
- **STOP.**
|
||||
- Count: How many fixes have you tried?
|
||||
- If < 3: Return to Phase 1, re-analyze with new information
|
||||
- **If ≥ 3: STOP and question the architecture (step 5 below)**
|
||||
- DON'T attempt Fix #4 without architectural discussion
|
||||
|
||||
### 5. If 3+ Fixes Failed: Question Architecture
|
||||
|
||||
**Pattern indicating an architectural problem:**
|
||||
- Each fix reveals new shared state/coupling in a different place
|
||||
- Fixes require "massive refactoring" to implement
|
||||
- Each fix creates new symptoms elsewhere
|
||||
|
||||
**STOP and question fundamentals:**
|
||||
- Is this pattern fundamentally sound?
|
||||
- Are we "sticking with it through sheer inertia"?
|
||||
- Should we refactor the architecture vs. continue fixing symptoms?
|
||||
|
||||
**Discuss with the user before attempting more fixes.**
|
||||
|
||||
This is NOT a failed hypothesis — this is a wrong architecture.
|
||||
|
||||
---
|
||||
|
||||
## Red Flags — STOP and Follow Process
|
||||
|
||||
If you catch yourself thinking:
|
||||
- "Quick fix for now, investigate later"
|
||||
- "Just try changing X and see if it works"
|
||||
- "Add multiple changes, run tests"
|
||||
- "Skip the test, I'll manually verify"
|
||||
- "It's probably X, let me fix that"
|
||||
- "I don't fully understand but this might work"
|
||||
- "Pattern says X but I'll adapt it differently"
|
||||
- "Here are the main problems: [lists fixes without investigation]"
|
||||
- Proposing solutions before tracing data flow
|
||||
- **"One more fix attempt" (when already tried 2+)**
|
||||
- **Each fix reveals a new problem in a different place**
|
||||
|
||||
**ALL of these mean: STOP. Return to Phase 1.**
|
||||
|
||||
**If 3+ fixes failed:** Question the architecture (Phase 4 step 5).
|
||||
|
||||
## Common Rationalizations
|
||||
|
||||
| Excuse | Reality |
|
||||
|--------|---------|
|
||||
| "Issue is simple, don't need process" | Simple issues have root causes too. Process is fast for simple bugs. |
|
||||
| "Emergency, no time for process" | Systematic debugging is FASTER than guess-and-check thrashing. |
|
||||
| "Just try this first, then investigate" | First fix sets the pattern. Do it right from the start. |
|
||||
| "I'll write test after confirming fix works" | Untested fixes don't stick. Test first proves it. |
|
||||
| "Multiple fixes at once saves time" | Can't isolate what worked. Causes new bugs. |
|
||||
| "Reference too long, I'll adapt the pattern" | Partial understanding guarantees bugs. Read it completely. |
|
||||
| "I see the problem, let me fix it" | Seeing symptoms ≠ understanding root cause. |
|
||||
| "One more fix attempt" (after 2+ failures) | 3+ failures = architectural problem. Question the pattern, don't fix again. |
|
||||
|
||||
## Quick Reference
|
||||
|
||||
| Phase | Key Activities | Success Criteria |
|
||||
|-------|---------------|------------------|
|
||||
| **1. Root Cause** | Read errors, reproduce, check changes, gather evidence, trace data flow | Understand WHAT and WHY |
|
||||
| **2. Pattern** | Find working examples, compare, identify differences | Know what's different |
|
||||
| **3. Hypothesis** | Form theory, test minimally, one variable at a time | Confirmed or new hypothesis |
|
||||
| **4. Implementation** | Create regression test, fix root cause, verify | Bug resolved, all tests pass |
|
||||
|
||||
## Hermes Agent Integration
|
||||
|
||||
### Investigation Tools
|
||||
|
||||
Use these Hermes tools during Phase 1:
|
||||
|
||||
- **`search_files`** — Find error strings, trace function calls, locate patterns
|
||||
- **`read_file`** — Read source code with line numbers for precise analysis
|
||||
- **`terminal`** — Run tests, check git history, reproduce bugs
|
||||
- **`web_search`/`web_extract`** — Research error messages, library docs
|
||||
|
||||
### With delegate_task
|
||||
|
||||
For complex multi-component debugging, dispatch investigation subagents:
|
||||
|
||||
```python
|
||||
delegate_task(
|
||||
goal="Investigate why [specific test/behavior] fails",
|
||||
context="""
|
||||
Follow systematic-debugging skill:
|
||||
1. Read the error message carefully
|
||||
2. Reproduce the issue
|
||||
3. Trace the data flow to find root cause
|
||||
4. Report findings — do NOT fix yet
|
||||
|
||||
Error: [paste full error]
|
||||
File: [path to failing code]
|
||||
Test command: [exact command]
|
||||
""",
|
||||
toolsets=['terminal', 'file']
|
||||
)
|
||||
```
|
||||
|
||||
### With test-driven-development
|
||||
|
||||
When fixing bugs:
|
||||
1. Write a test that reproduces the bug (RED)
|
||||
2. Debug systematically to find root cause
|
||||
3. Fix the root cause (GREEN)
|
||||
4. The test proves the fix and prevents regression
|
||||
|
||||
## Real-World Impact
|
||||
|
||||
From debugging sessions:
|
||||
- Systematic approach: 15-30 minutes to fix
|
||||
- Random fixes approach: 2-3 hours of thrashing
|
||||
- First-time fix rate: 95% vs 40%
|
||||
- New bugs introduced: Near zero vs common
|
||||
|
||||
**No shortcuts. No guessing. Systematic always wins.**
|
||||
@@ -0,0 +1,342 @@
|
||||
---
|
||||
name: test-driven-development
|
||||
description: Use when implementing any feature or bugfix, before writing implementation code. Enforces RED-GREEN-REFACTOR cycle with test-first approach.
|
||||
version: 1.1.0
|
||||
author: Hermes Agent (adapted from obra/superpowers)
|
||||
license: MIT
|
||||
metadata:
|
||||
hermes:
|
||||
tags: [testing, tdd, development, quality, red-green-refactor]
|
||||
related_skills: [systematic-debugging, writing-plans, subagent-driven-development]
|
||||
---
|
||||
|
||||
# Test-Driven Development (TDD)
|
||||
|
||||
## Overview
|
||||
|
||||
Write the test first. Watch it fail. Write minimal code to pass.
|
||||
|
||||
**Core principle:** If you didn't watch the test fail, you don't know if it tests the right thing.
|
||||
|
||||
**Violating the letter of the rules is violating the spirit of the rules.**
|
||||
|
||||
## When to Use
|
||||
|
||||
**Always:**
|
||||
- New features
|
||||
- Bug fixes
|
||||
- Refactoring
|
||||
- Behavior changes
|
||||
|
||||
**Exceptions (ask the user first):**
|
||||
- Throwaway prototypes
|
||||
- Generated code
|
||||
- Configuration files
|
||||
|
||||
Thinking "skip TDD just this once"? Stop. That's rationalization.
|
||||
|
||||
## The Iron Law
|
||||
|
||||
```
|
||||
NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST
|
||||
```
|
||||
|
||||
Write code before the test? Delete it. Start over.
|
||||
|
||||
**No exceptions:**
|
||||
- Don't keep it as "reference"
|
||||
- Don't "adapt" it while writing tests
|
||||
- Don't look at it
|
||||
- Delete means delete
|
||||
|
||||
Implement fresh from tests. Period.
|
||||
|
||||
## Red-Green-Refactor Cycle
|
||||
|
||||
### RED — Write Failing Test
|
||||
|
||||
Write one minimal test showing what should happen.
|
||||
|
||||
**Good test:**
|
||||
```python
|
||||
def test_retries_failed_operations_3_times():
|
||||
attempts = 0
|
||||
def operation():
|
||||
nonlocal attempts
|
||||
attempts += 1
|
||||
if attempts < 3:
|
||||
raise Exception('fail')
|
||||
return 'success'
|
||||
|
||||
result = retry_operation(operation)
|
||||
|
||||
assert result == 'success'
|
||||
assert attempts == 3
|
||||
```
|
||||
Clear name, tests real behavior, one thing.
|
||||
|
||||
**Bad test:**
|
||||
```python
|
||||
def test_retry_works():
|
||||
mock = MagicMock()
|
||||
mock.side_effect = [Exception(), Exception(), 'success']
|
||||
result = retry_operation(mock)
|
||||
assert result == 'success' # What about retry count? Timing?
|
||||
```
|
||||
Vague name, tests mock not real code.
|
||||
|
||||
**Requirements:**
|
||||
- One behavior per test
|
||||
- Clear descriptive name ("and" in name? Split it)
|
||||
- Real code, not mocks (unless truly unavoidable)
|
||||
- Name describes behavior, not implementation
|
||||
|
||||
### Verify RED — Watch It Fail
|
||||
|
||||
**MANDATORY. Never skip.**
|
||||
|
||||
```bash
|
||||
# Use terminal tool to run the specific test
|
||||
pytest tests/test_feature.py::test_specific_behavior -v
|
||||
```
|
||||
|
||||
Confirm:
|
||||
- Test fails (not errors from typos)
|
||||
- Failure message is expected
|
||||
- Fails because the feature is missing
|
||||
|
||||
**Test passes immediately?** You're testing existing behavior. Fix the test.
|
||||
|
||||
**Test errors?** Fix the error, re-run until it fails correctly.
|
||||
|
||||
### GREEN — Minimal Code
|
||||
|
||||
Write the simplest code to pass the test. Nothing more.
|
||||
|
||||
**Good:**
|
||||
```python
|
||||
def add(a, b):
|
||||
return a + b # Nothing extra
|
||||
```
|
||||
|
||||
**Bad:**
|
||||
```python
|
||||
def add(a, b):
|
||||
result = a + b
|
||||
logging.info(f"Adding {a} + {b} = {result}") # Extra!
|
||||
return result
|
||||
```
|
||||
|
||||
Don't add features, refactor other code, or "improve" beyond the test.
|
||||
|
||||
**Cheating is OK in GREEN:**
|
||||
- Hardcode return values
|
||||
- Copy-paste
|
||||
- Duplicate code
|
||||
- Skip edge cases
|
||||
|
||||
We'll fix it in REFACTOR.
|
||||
|
||||
### Verify GREEN — Watch It Pass
|
||||
|
||||
**MANDATORY.**
|
||||
|
||||
```bash
|
||||
# Run the specific test
|
||||
pytest tests/test_feature.py::test_specific_behavior -v
|
||||
|
||||
# Then run ALL tests to check for regressions
|
||||
pytest tests/ -q
|
||||
```
|
||||
|
||||
Confirm:
|
||||
- Test passes
|
||||
- Other tests still pass
|
||||
- Output pristine (no errors, warnings)
|
||||
|
||||
**Test fails?** Fix the code, not the test.
|
||||
|
||||
**Other tests fail?** Fix regressions now.
|
||||
|
||||
### REFACTOR — Clean Up
|
||||
|
||||
After green only:
|
||||
- Remove duplication
|
||||
- Improve names
|
||||
- Extract helpers
|
||||
- Simplify expressions
|
||||
|
||||
Keep tests green throughout. Don't add behavior.
|
||||
|
||||
**If tests fail during refactor:** Undo immediately. Take smaller steps.
|
||||
|
||||
### Repeat
|
||||
|
||||
Next failing test for next behavior. One cycle at a time.
|
||||
|
||||
## Why Order Matters
|
||||
|
||||
**"I'll write tests after to verify it works"**
|
||||
|
||||
Tests written after code pass immediately. Passing immediately proves nothing:
|
||||
- Might test the wrong thing
|
||||
- Might test implementation, not behavior
|
||||
- Might miss edge cases you forgot
|
||||
- You never saw it catch the bug
|
||||
|
||||
Test-first forces you to see the test fail, proving it actually tests something.
|
||||
|
||||
**"I already manually tested all the edge cases"**
|
||||
|
||||
Manual testing is ad-hoc. You think you tested everything but:
|
||||
- No record of what you tested
|
||||
- Can't re-run when code changes
|
||||
- Easy to forget cases under pressure
|
||||
- "It worked when I tried it" ≠ comprehensive
|
||||
|
||||
Automated tests are systematic. They run the same way every time.
|
||||
|
||||
**"Deleting X hours of work is wasteful"**
|
||||
|
||||
Sunk cost fallacy. The time is already gone. Your choice now:
|
||||
- Delete and rewrite with TDD (high confidence)
|
||||
- Keep it and add tests after (low confidence, likely bugs)
|
||||
|
||||
The "waste" is keeping code you can't trust.
|
||||
|
||||
**"TDD is dogmatic, being pragmatic means adapting"**
|
||||
|
||||
TDD IS pragmatic:
|
||||
- Finds bugs before commit (faster than debugging after)
|
||||
- Prevents regressions (tests catch breaks immediately)
|
||||
- Documents behavior (tests show how to use code)
|
||||
- Enables refactoring (change freely, tests catch breaks)
|
||||
|
||||
"Pragmatic" shortcuts = debugging in production = slower.
|
||||
|
||||
**"Tests after achieve the same goals — it's spirit not ritual"**
|
||||
|
||||
No. Tests-after answer "What does this do?" Tests-first answer "What should this do?"
|
||||
|
||||
Tests-after are biased by your implementation. You test what you built, not what's required. Tests-first force edge case discovery before implementing.
|
||||
|
||||
## Common Rationalizations
|
||||
|
||||
| Excuse | Reality |
|
||||
|--------|---------|
|
||||
| "Too simple to test" | Simple code breaks. Test takes 30 seconds. |
|
||||
| "I'll test after" | Tests passing immediately prove nothing. |
|
||||
| "Tests after achieve same goals" | Tests-after = "what does this do?" Tests-first = "what should this do?" |
|
||||
| "Already manually tested" | Ad-hoc ≠ systematic. No record, can't re-run. |
|
||||
| "Deleting X hours is wasteful" | Sunk cost fallacy. Keeping unverified code is technical debt. |
|
||||
| "Keep as reference, write tests first" | You'll adapt it. That's testing after. Delete means delete. |
|
||||
| "Need to explore first" | Fine. Throw away exploration, start with TDD. |
|
||||
| "Test hard = design unclear" | Listen to the test. Hard to test = hard to use. |
|
||||
| "TDD will slow me down" | TDD faster than debugging. Pragmatic = test-first. |
|
||||
| "Manual test faster" | Manual doesn't prove edge cases. You'll re-test every change. |
|
||||
| "Existing code has no tests" | You're improving it. Add tests for the code you touch. |
|
||||
|
||||
## Red Flags — STOP and Start Over
|
||||
|
||||
If you catch yourself doing any of these, delete the code and restart with TDD:
|
||||
|
||||
- Code before test
|
||||
- Test after implementation
|
||||
- Test passes immediately on first run
|
||||
- Can't explain why test failed
|
||||
- Tests added "later"
|
||||
- Rationalizing "just this once"
|
||||
- "I already manually tested it"
|
||||
- "Tests after achieve the same purpose"
|
||||
- "Keep as reference" or "adapt existing code"
|
||||
- "Already spent X hours, deleting is wasteful"
|
||||
- "TDD is dogmatic, I'm being pragmatic"
|
||||
- "This is different because..."
|
||||
|
||||
**All of these mean: Delete code. Start over with TDD.**
|
||||
|
||||
## Verification Checklist
|
||||
|
||||
Before marking work complete:
|
||||
|
||||
- [ ] Every new function/method has a test
|
||||
- [ ] Watched each test fail before implementing
|
||||
- [ ] Each test failed for expected reason (feature missing, not typo)
|
||||
- [ ] Wrote minimal code to pass each test
|
||||
- [ ] All tests pass
|
||||
- [ ] Output pristine (no errors, warnings)
|
||||
- [ ] Tests use real code (mocks only if unavoidable)
|
||||
- [ ] Edge cases and errors covered
|
||||
|
||||
Can't check all boxes? You skipped TDD. Start over.
|
||||
|
||||
## When Stuck
|
||||
|
||||
| Problem | Solution |
|
||||
|---------|----------|
|
||||
| Don't know how to test | Write the wished-for API. Write the assertion first. Ask the user. |
|
||||
| Test too complicated | Design too complicated. Simplify the interface. |
|
||||
| Must mock everything | Code too coupled. Use dependency injection. |
|
||||
| Test setup huge | Extract helpers. Still complex? Simplify the design. |
|
||||
|
||||
## Hermes Agent Integration
|
||||
|
||||
### Running Tests
|
||||
|
||||
Use the `terminal` tool to run tests at each step:
|
||||
|
||||
```python
|
||||
# RED — verify failure
|
||||
terminal("pytest tests/test_feature.py::test_name -v")
|
||||
|
||||
# GREEN — verify pass
|
||||
terminal("pytest tests/test_feature.py::test_name -v")
|
||||
|
||||
# Full suite — verify no regressions
|
||||
terminal("pytest tests/ -q")
|
||||
```
|
||||
|
||||
### With delegate_task
|
||||
|
||||
When dispatching subagents for implementation, enforce TDD in the goal:
|
||||
|
||||
```python
|
||||
delegate_task(
|
||||
goal="Implement [feature] using strict TDD",
|
||||
context="""
|
||||
Follow test-driven-development skill:
|
||||
1. Write failing test FIRST
|
||||
2. Run test to verify it fails
|
||||
3. Write minimal code to pass
|
||||
4. Run test to verify it passes
|
||||
5. Refactor if needed
|
||||
6. Commit
|
||||
|
||||
Project test command: pytest tests/ -q
|
||||
Project structure: [describe relevant files]
|
||||
""",
|
||||
toolsets=['terminal', 'file']
|
||||
)
|
||||
```
|
||||
|
||||
### With systematic-debugging
|
||||
|
||||
Bug found? Write failing test reproducing it. Follow TDD cycle. The test proves the fix and prevents regression.
|
||||
|
||||
Never fix bugs without a test.
|
||||
|
||||
## Testing Anti-Patterns
|
||||
|
||||
- **Testing mock behavior instead of real behavior** — mocks should verify interactions, not replace the system under test
|
||||
- **Testing implementation details** — test behavior/results, not internal method calls
|
||||
- **Happy path only** — always test edge cases, errors, and boundaries
|
||||
- **Brittle tests** — tests should verify behavior, not structure; refactoring shouldn't break them
|
||||
|
||||
## Final Rule
|
||||
|
||||
```
|
||||
Production code → test exists and failed first
|
||||
Otherwise → not TDD
|
||||
```
|
||||
|
||||
No exceptions without the user's explicit permission.
|
||||
@@ -0,0 +1,296 @@
|
||||
---
|
||||
name: writing-plans
|
||||
description: Use when you have a spec or requirements for a multi-step task. Creates comprehensive implementation plans with bite-sized tasks, exact file paths, and complete code examples.
|
||||
version: 1.1.0
|
||||
author: Hermes Agent (adapted from obra/superpowers)
|
||||
license: MIT
|
||||
metadata:
|
||||
hermes:
|
||||
tags: [planning, design, implementation, workflow, documentation]
|
||||
related_skills: [subagent-driven-development, test-driven-development, requesting-code-review]
|
||||
---
|
||||
|
||||
# Writing Implementation Plans
|
||||
|
||||
## Overview
|
||||
|
||||
Write comprehensive implementation plans assuming the implementer has zero context for the codebase and questionable taste. Document everything they need: which files to touch, complete code, testing commands, docs to check, how to verify. Give them bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
|
||||
|
||||
Assume the implementer is a skilled developer but knows almost nothing about the toolset or problem domain. Assume they don't know good test design very well.
|
||||
|
||||
**Core principle:** A good plan makes implementation obvious. If someone has to guess, the plan is incomplete.
|
||||
|
||||
## When to Use
|
||||
|
||||
**Always use before:**
|
||||
- Implementing multi-step features
|
||||
- Breaking down complex requirements
|
||||
- Delegating to subagents via subagent-driven-development
|
||||
|
||||
**Don't skip when:**
|
||||
- Feature seems simple (assumptions cause bugs)
|
||||
- You plan to implement it yourself (future you needs guidance)
|
||||
- Working alone (documentation matters)
|
||||
|
||||
## Bite-Sized Task Granularity
|
||||
|
||||
**Each task = 2-5 minutes of focused work.**
|
||||
|
||||
Every step is one action:
|
||||
- "Write the failing test" — step
|
||||
- "Run it to make sure it fails" — step
|
||||
- "Implement the minimal code to make the test pass" — step
|
||||
- "Run the tests and make sure they pass" — step
|
||||
- "Commit" — step
|
||||
|
||||
**Too big:**
|
||||
```markdown
|
||||
### Task 1: Build authentication system
|
||||
[50 lines of code across 5 files]
|
||||
```
|
||||
|
||||
**Right size:**
|
||||
```markdown
|
||||
### Task 1: Create User model with email field
|
||||
[10 lines, 1 file]
|
||||
|
||||
### Task 2: Add password hash field to User
|
||||
[8 lines, 1 file]
|
||||
|
||||
### Task 3: Create password hashing utility
|
||||
[15 lines, 1 file]
|
||||
```
|
||||
|
||||
## Plan Document Structure
|
||||
|
||||
### Header (Required)
|
||||
|
||||
Every plan MUST start with:
|
||||
|
||||
```markdown
|
||||
# [Feature Name] Implementation Plan
|
||||
|
||||
> **For Hermes:** Use subagent-driven-development skill to implement this plan task-by-task.
|
||||
|
||||
**Goal:** [One sentence describing what this builds]
|
||||
|
||||
**Architecture:** [2-3 sentences about approach]
|
||||
|
||||
**Tech Stack:** [Key technologies/libraries]
|
||||
|
||||
---
|
||||
```
|
||||
|
||||
### Task Structure
|
||||
|
||||
Each task follows this format:
|
||||
|
||||
````markdown
|
||||
### Task N: [Descriptive Name]
|
||||
|
||||
**Objective:** What this task accomplishes (one sentence)
|
||||
|
||||
**Files:**
|
||||
- Create: `exact/path/to/new_file.py`
|
||||
- Modify: `exact/path/to/existing.py:45-67` (line numbers if known)
|
||||
- Test: `tests/path/to/test_file.py`
|
||||
|
||||
**Step 1: Write failing test**
|
||||
|
||||
```python
|
||||
def test_specific_behavior():
|
||||
result = function(input)
|
||||
assert result == expected
|
||||
```
|
||||
|
||||
**Step 2: Run test to verify failure**
|
||||
|
||||
Run: `pytest tests/path/test.py::test_specific_behavior -v`
|
||||
Expected: FAIL — "function not defined"
|
||||
|
||||
**Step 3: Write minimal implementation**
|
||||
|
||||
```python
|
||||
def function(input):
|
||||
return expected
|
||||
```
|
||||
|
||||
**Step 4: Run test to verify pass**
|
||||
|
||||
Run: `pytest tests/path/test.py::test_specific_behavior -v`
|
||||
Expected: PASS
|
||||
|
||||
**Step 5: Commit**
|
||||
|
||||
```bash
|
||||
git add tests/path/test.py src/path/file.py
|
||||
git commit -m "feat: add specific feature"
|
||||
```
|
||||
````
|
||||
|
||||
## Writing Process
|
||||
|
||||
### Step 1: Understand Requirements
|
||||
|
||||
Read and understand:
|
||||
- Feature requirements
|
||||
- Design documents or user description
|
||||
- Acceptance criteria
|
||||
- Constraints
|
||||
|
||||
### Step 2: Explore the Codebase
|
||||
|
||||
Use Hermes tools to understand the project:
|
||||
|
||||
```python
|
||||
# Understand project structure
|
||||
search_files("*.py", target="files", path="src/")
|
||||
|
||||
# Look at similar features
|
||||
search_files("similar_pattern", path="src/", file_glob="*.py")
|
||||
|
||||
# Check existing tests
|
||||
search_files("*.py", target="files", path="tests/")
|
||||
|
||||
# Read key files
|
||||
read_file("src/app.py")
|
||||
```
|
||||
|
||||
### Step 3: Design Approach
|
||||
|
||||
Decide:
|
||||
- Architecture pattern
|
||||
- File organization
|
||||
- Dependencies needed
|
||||
- Testing strategy
|
||||
|
||||
### Step 4: Write Tasks
|
||||
|
||||
Create tasks in order:
|
||||
1. Setup/infrastructure
|
||||
2. Core functionality (TDD for each)
|
||||
3. Edge cases
|
||||
4. Integration
|
||||
5. Cleanup/documentation
|
||||
|
||||
### Step 5: Add Complete Details
|
||||
|
||||
For each task, include:
|
||||
- **Exact file paths** (not "the config file" but `src/config/settings.py`)
|
||||
- **Complete code examples** (not "add validation" but the actual code)
|
||||
- **Exact commands** with expected output
|
||||
- **Verification steps** that prove the task works
|
||||
|
||||
### Step 6: Review the Plan
|
||||
|
||||
Check:
|
||||
- [ ] Tasks are sequential and logical
|
||||
- [ ] Each task is bite-sized (2-5 min)
|
||||
- [ ] File paths are exact
|
||||
- [ ] Code examples are complete (copy-pasteable)
|
||||
- [ ] Commands are exact with expected output
|
||||
- [ ] No missing context
|
||||
- [ ] DRY, YAGNI, TDD principles applied
|
||||
|
||||
### Step 7: Save the Plan
|
||||
|
||||
```bash
|
||||
mkdir -p docs/plans
|
||||
# Save plan to docs/plans/YYYY-MM-DD-feature-name.md
|
||||
git add docs/plans/
|
||||
git commit -m "docs: add implementation plan for [feature]"
|
||||
```
|
||||
|
||||
## Principles
|
||||
|
||||
### DRY (Don't Repeat Yourself)
|
||||
|
||||
**Bad:** Copy-paste validation in 3 places
|
||||
**Good:** Extract validation function, use everywhere
|
||||
|
||||
### YAGNI (You Aren't Gonna Need It)
|
||||
|
||||
**Bad:** Add "flexibility" for future requirements
|
||||
**Good:** Implement only what's needed now
|
||||
|
||||
```python
|
||||
# Bad — YAGNI violation
|
||||
class User:
|
||||
def __init__(self, name, email):
|
||||
self.name = name
|
||||
self.email = email
|
||||
self.preferences = {} # Not needed yet!
|
||||
self.metadata = {} # Not needed yet!
|
||||
|
||||
# Good — YAGNI
|
||||
class User:
|
||||
def __init__(self, name, email):
|
||||
self.name = name
|
||||
self.email = email
|
||||
```
|
||||
|
||||
### TDD (Test-Driven Development)
|
||||
|
||||
Every task that produces code should include the full TDD cycle:
|
||||
1. Write failing test
|
||||
2. Run to verify failure
|
||||
3. Write minimal code
|
||||
4. Run to verify pass
|
||||
|
||||
See `test-driven-development` skill for details.
|
||||
|
||||
### Frequent Commits
|
||||
|
||||
Commit after every task:
|
||||
```bash
|
||||
git add [files]
|
||||
git commit -m "type: description"
|
||||
```
|
||||
|
||||
## Common Mistakes
|
||||
|
||||
### Vague Tasks
|
||||
|
||||
**Bad:** "Add authentication"
|
||||
**Good:** "Create User model with email and password_hash fields"
|
||||
|
||||
### Incomplete Code
|
||||
|
||||
**Bad:** "Step 1: Add validation function"
|
||||
**Good:** "Step 1: Add validation function" followed by the complete function code
|
||||
|
||||
### Missing Verification
|
||||
|
||||
**Bad:** "Step 3: Test it works"
|
||||
**Good:** "Step 3: Run `pytest tests/test_auth.py -v`, expected: 3 passed"
|
||||
|
||||
### Missing File Paths
|
||||
|
||||
**Bad:** "Create the model file"
|
||||
**Good:** "Create: `src/models/user.py`"
|
||||
|
||||
## Execution Handoff
|
||||
|
||||
After saving the plan, offer the execution approach:
|
||||
|
||||
**"Plan complete and saved. Ready to execute using subagent-driven-development — I'll dispatch a fresh subagent per task with two-stage review (spec compliance then code quality). Shall I proceed?"**
|
||||
|
||||
When executing, use the `subagent-driven-development` skill:
|
||||
- Fresh `delegate_task` per task with full context
|
||||
- Spec compliance review after each task
|
||||
- Code quality review after spec passes
|
||||
- Proceed only when both reviews approve
|
||||
|
||||
## Remember
|
||||
|
||||
```
|
||||
Bite-sized tasks (2-5 min each)
|
||||
Exact file paths
|
||||
Complete code (copy-pasteable)
|
||||
Exact commands with expected output
|
||||
Verification steps
|
||||
DRY, YAGNI, TDD
|
||||
Frequent commits
|
||||
```
|
||||
|
||||
**A good plan makes implementation obvious.**
|
||||
Reference in New Issue
Block a user