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Alexander Whitestone
ae38b9b2bf docs: add timmy-config genome analysis (refs #669)
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Smoke Test / smoke (pull_request) Failing after 17s
2026-04-15 00:05:15 -04:00
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GENOME.md
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# GENOME.md — Timmy_Foundation/timmy-home
# GENOME.md — timmy-config
Generated by `pipelines/codebase_genome.py`.
Auto-generated facts were derived from the local `~/.timmy/timmy-config` checkout on 2026-04-14 and then reviewed manually for architecture, API surface, and operational meaning.
## Project Overview
Timmy Foundation's home repository for development operations and configurations.
`timmy-config` is the sovereign sidecar for Timmy.
It is not the model runtime and it is not the work archive. It is the configuration and orchestration layer that tells Hermes who Timmy is, how he is routed, what scripts are available, what memories and skins are installed, and how the fleet is operated.
- Text files indexed: 3004
- Source and script files: 186
- Test files: 28
- Documentation files: 701
The repo exists because the Timmy Foundation made a hard architectural split:
- `hermes-agent` is the engine
- `timmy-config` is the driver's seat
- `timmy-home` is the lived workspace and artifact archive
## Architecture
This repo is therefore a mixed codebase with three major responsibilities:
1. Sidecar deployment into `~/.hermes/`
2. Operational automation for the fleet
3. Thin training/orchestration support without becoming a monolith again
Observed quick facts from the current local checkout:
- Source files: 178
- Test files: 36
- Config files: 24
- Total lines: 35,624
- Last commit on analyzed source: `7630806f` (`sync: align repo with live system config`)
- Total commits: 393
## Architecture Diagram
```mermaid
graph TD
repo_root["repo"]
angband["angband"]
briefings["briefings"]
config["config"]
conftest["conftest"]
evennia["evennia"]
evennia_tools["evennia_tools"]
evolution["evolution"]
gemini_fallback_setup["gemini-fallback-setup"]
heartbeat["heartbeat"]
infrastructure["infrastructure"]
repo_root --> angband
repo_root --> briefings
repo_root --> config
repo_root --> conftest
repo_root --> evennia
repo_root --> evennia_tools
flowchart TD
A[timmy-config repo] --> B[deploy.sh]
B --> C[~/.hermes/config.yaml]
B --> D[~/.hermes/bin/*]
B --> E[~/.hermes/playbooks/*]
B --> F[~/.hermes/cron/*]
B --> G[~/.hermes/memories/*]
B --> H[~/.timmy/SOUL.md]
C --> I[Hermes gateway/runtime]
D --> J[Operational scripts]
E --> K[Playbook-driven agent behavior]
F --> L[Cron-scheduled automation]
J --> M[Gitea forge]
J --> N[Telegram / platform gateways]
J --> O[tmux wizard fleet]
J --> P[metrics + local files]
Q[orchestration.py + tasks.py] --> R[Huey / SQLite queue]
R --> J
Q --> M
Q --> P
S[gitea_client.py] --> M
T[training/*] --> U[curated datasets + evaluation recipes]
U --> P
V[timmy-home] <-->|artifacts / logs / training outputs| J
V <-->|continuity / notes / metrics| Q
```
## Entry Points
## Entry Points and Data Flow
- `gemini-fallback-setup.sh` — operational script (`bash gemini-fallback-setup.sh`)
- `morrowind/hud.sh` — operational script (`bash morrowind/hud.sh`)
- `pipelines/codebase_genome.py` — python main guard (`python3 pipelines/codebase_genome.py`)
- `scripts/auto_restart_agent.sh` — operational script (`bash scripts/auto_restart_agent.sh`)
- `scripts/backup_pipeline.sh` — operational script (`bash scripts/backup_pipeline.sh`)
- `scripts/big_brain_manager.py` — operational script (`python3 scripts/big_brain_manager.py`)
- `scripts/big_brain_repo_audit.py` — operational script (`python3 scripts/big_brain_repo_audit.py`)
- `scripts/codebase_genome_nightly.py` — operational script (`python3 scripts/codebase_genome_nightly.py`)
- `scripts/detect_secrets.py` — operational script (`python3 scripts/detect_secrets.py`)
- `scripts/dynamic_dispatch_optimizer.py` — operational script (`python3 scripts/dynamic_dispatch_optimizer.py`)
- `scripts/emacs-fleet-bridge.py` — operational script (`python3 scripts/emacs-fleet-bridge.py`)
- `scripts/emacs-fleet-poll.sh` — operational script (`bash scripts/emacs-fleet-poll.sh`)
### Primary entry points
## Data Flow
1. `deploy.sh`
- canonical sidecar deployment entry point
- copies config, scripts, playbooks, cron definitions, skins, and memories into `~/.hermes/`
- writes `SOUL.md` into `~/.timmy/`
1. Operators enter through `gemini-fallback-setup.sh`, `morrowind/hud.sh`, `pipelines/codebase_genome.py`.
2. Core logic fans into top-level components: `angband`, `briefings`, `config`, `conftest`, `evennia`, `evennia_tools`.
3. Validation is incomplete around `wizards/allegro/home/skills/red-teaming/godmode/scripts/auto_jailbreak.py`, `timmy-local/cache/agent_cache.py`, `wizards/allegro/home/skills/red-teaming/godmode/scripts/parseltongue.py`, so changes there carry regression risk.
4. Final artifacts land as repository files, docs, or runtime side effects depending on the selected entry point.
2. `orchestration.py`
- defines the Huey SQLite queue
- the root scheduler primitive for queued work
3. `tasks.py`
- the real orchestration surface
- contains scheduled jobs, local Hermes invocations, archive/training helpers, JSONL helpers, continuity flushing, and repo lists
4. `gitea_client.py`
- typed stdlib-only interface to Gitea
- shared API layer replacing scattered raw curl logic
5. `bin/*`
- operational executables for health checks, deadman switch, dispatch, watchdogs, scans, and status panels
- this is the hands-on operator layer
### Data flow summary
- Configuration starts in repo files like `config.yaml`, `fallback-portfolios.yaml`, `channel_directory.json`, `memories/`, `skins/`, `playbooks/`, and `cron/`
- `deploy.sh` overlays these into the Hermes runtime directory
- Hermes runtime reads the deployed config and scripts
- `tasks.py` and `bin/*` then interact with:
- Gitea (`gitea_client.py`, issue/PR automation)
- local Hermes sessions (`run_hermes_local` paths in `tasks.py`)
- local files in `~/.timmy/` and `~/.hermes/`
- metrics JSONL outputs
- Telegram / gateway surfaces
This is a classic sidecar pattern: the repo does not own the engine, but it owns almost every operational decision around the engine.
## Key Abstractions
- `evennia/timmy_world/game.py` — classes `World`:91, `ActionSystem`:421, `TimmyAI`:539, `NPCAI`:550; functions `get_narrative_phase()`:55, `get_phase_transition_event()`:65
- `evennia/timmy_world/world/game.py` — classes `World`:19, `ActionSystem`:326, `TimmyAI`:444, `NPCAI`:455; functions none detected
- `timmy-world/game.py` — classes `World`:19, `ActionSystem`:349, `TimmyAI`:467, `NPCAI`:478; functions none detected
- `wizards/allegro/home/skills/red-teaming/godmode/scripts/auto_jailbreak.py` — classes none detected; functions none detected
- `uniwizard/self_grader.py` — classes `SessionGrade`:23, `WeeklyReport`:55, `SelfGrader`:74; functions `main()`:713
- `uni-wizard/v3/intelligence_engine.py` — classes `ExecutionPattern`:27, `ModelPerformance`:44, `AdaptationEvent`:58, `PatternDatabase`:69; functions none detected
- `scripts/know_thy_father/crossref_audit.py` — classes `ThemeCategory`:30, `Principle`:160, `MeaningKernel`:169, `CrossRefFinding`:178; functions `extract_themes_from_text()`:192, `parse_soul_md()`:206, `parse_kernels()`:264, `cross_reference()`:296, `generate_report()`:440, `main()`:561
- `timmy-local/cache/agent_cache.py` — classes `CacheStats`:28, `LRUCache`:52, `ResponseCache`:94, `ToolCache`:205; functions none detected
### 1. Sidecar overlay
Core idea: never fork Hermes if a sidecar can express the behavior.
This abstraction appears in:
- `deploy.sh`
- repo layout under `bin/`, `cron/`, `playbooks/`, `memories/`, `skins/`
- the explicit README boundary between `timmy-config` and `timmy-home`
### 2. Typed forge client
`gitea_client.py` turns the forge into a stable internal API surface.
Important abstractions:
- `Issue`
- `PullRequest`
- `Comment`
- `Label`
- `User`
- `GiteaClient`
This is important because many other scripts can depend on one client instead of shelling out to brittle curl commands.
### 3. Queue-backed orchestration
`orchestration.py` + `tasks.py` define the move from ad-hoc shell automation to queued work.
The central abstraction is not just “a cron job” but “a schedulable task with local model execution, continuity, and metrics.”
### 4. Continuity as files, not vibes
`tasks.py` contains explicit file-backed continuity helpers:
- `flush_continuity(...)`
- JSON readers/writers
- JSONL append/load helpers
- archive checkpoint/state files
This abstraction matters because Timmy continuity survives compaction or restart by being written to disk.
### 5. Training as thin recipes
The training directory is intentionally framed as transitional.
It exposes recipes and helper scripts, but the README is explicit that lived data belongs elsewhere.
This is an important abstraction boundary:
- configs + generators here
- real activity artifacts in `timmy-home`
## API Surface
- CLI: `bash gemini-fallback-setup.sh` — operational script (`gemini-fallback-setup.sh`)
- CLI: `bash morrowind/hud.sh` — operational script (`morrowind/hud.sh`)
- CLI: `python3 pipelines/codebase_genome.py` — python main guard (`pipelines/codebase_genome.py`)
- CLI: `bash scripts/auto_restart_agent.sh` — operational script (`scripts/auto_restart_agent.sh`)
- CLI: `bash scripts/backup_pipeline.sh` — operational script (`scripts/backup_pipeline.sh`)
- CLI: `python3 scripts/big_brain_manager.py` — operational script (`scripts/big_brain_manager.py`)
- CLI: `python3 scripts/big_brain_repo_audit.py` — operational script (`scripts/big_brain_repo_audit.py`)
- CLI: `python3 scripts/codebase_genome_nightly.py` — operational script (`scripts/codebase_genome_nightly.py`)
- Python: `get_narrative_phase()` from `evennia/timmy_world/game.py:55`
- Python: `get_phase_transition_event()` from `evennia/timmy_world/game.py:65`
- Python: `main()` from `uniwizard/self_grader.py:713`
### Shell / operator API
## Test Coverage Report
Important user-facing commands implied by the repo:
- `./deploy.sh`
- Huey consumer startup via `huey_consumer.py tasks.huey -w 2 -k thread`
- scripts in `bin/` such as:
- `deadman-switch.sh`
- `fleet-status.sh`
- `model-health-check.sh`
- `start-loops.sh`
- `agent-dispatch.sh`
- Source and script files inspected: 186
- Test files inspected: 28
- Coverage gaps:
- `wizards/allegro/home/skills/red-teaming/godmode/scripts/auto_jailbreak.py` — no matching test reference detected
- `timmy-local/cache/agent_cache.py` — no matching test reference detected
- `wizards/allegro/home/skills/red-teaming/godmode/scripts/parseltongue.py` — no matching test reference detected
- `twitter-archive/multimodal_pipeline.py` — no matching test reference detected
- `wizards/allegro/home/skills/red-teaming/godmode/scripts/godmode_race.py` — no matching test reference detected
- `skills/productivity/google-workspace/scripts/google_api.py` — no matching test reference detected
- `wizards/allegro/home/skills/productivity/google-workspace/scripts/google_api.py` — no matching test reference detected
- `morrowind/pilot.py` — no matching test reference detected
- `morrowind/mcp_server.py` — no matching test reference detected
- `skills/research/domain-intel/scripts/domain_intel.py` — no matching test reference detected
- `wizards/allegro/home/skills/research/domain-intel/scripts/domain_intel.py` — no matching test reference detected
- `timmy-local/scripts/ingest.py` — no matching test reference detected
### Python API surface
## Security Audit Findings
Most reusable programmatic interfaces:
- [medium] `briefings/briefing_20260325.json:37` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `"gitea_error": "Gitea 404: {\"errors\":null,\"message\":\"not found\",\"url\":\"http://143.198.27.163:3000/api/swagger\"}\n [http://143.198.27.163:3000/api/v1/repos/Timmy_Foundation/sovereign-orchestration/issues?state=open&type=issues&sort=created&direction=desc&limit=1&page=1]",`
- [medium] `briefings/briefing_20260328.json:11` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `"provider_base_url": "http://localhost:8081/v1",`
- [medium] `briefings/briefing_20260329.json:11` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `"provider_base_url": "http://localhost:8081/v1",`
- [medium] `config.yaml:37` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `summary_base_url: http://localhost:11434/v1`
- [medium] `config.yaml:47` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `base_url: 'http://localhost:11434/v1'`
- [medium] `config.yaml:52` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `base_url: 'http://localhost:11434/v1'`
- [medium] `config.yaml:57` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `base_url: 'http://localhost:11434/v1'`
- [medium] `config.yaml:62` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `base_url: 'http://localhost:11434/v1'`
- [medium] `config.yaml:67` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `base_url: 'http://localhost:11434/v1'`
- [medium] `config.yaml:77` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `base_url: 'http://localhost:11434/v1'`
- [medium] `config.yaml:82` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `base_url: 'http://localhost:11434/v1'`
- [medium] `config.yaml:174` — hardcoded http endpoint: plaintext or fixed HTTP endpoints can drift or leak across environments. Evidence: `base_url: http://localhost:11434/v1`
#### `gitea_client.GiteaClient`
Key methods include:
- `list_org_repos`
- `list_issues`
- `get_issue`
- `create_issue`
- `update_issue`
- `close_issue`
- `assign_issue`
- `add_labels`
- `list_comments`
- `create_comment`
- `list_pulls`
- `get_pull`
- `create_pull`
- `merge_pull`
- `update_pull_branch`
- `close_pull`
## Dead Code Candidates
#### `tasks.py` helpers
Notable reusable surfaces:
- `run_hermes_local(...)`
- `hermes_local(...)`
- `run_reflex_task(...)`
- `run_archive_hermes(...)`
- `flush_continuity(...)`
- JSON/JSONL primitives:
- `read_json`
- `write_json`
- `load_jsonl`
- `write_jsonl`
- `append_jsonl`
- `count_jsonl_rows`
- `wizards/allegro/home/skills/red-teaming/godmode/scripts/auto_jailbreak.py` — not imported by indexed Python modules and not referenced by tests
- `timmy-local/cache/agent_cache.py` — not imported by indexed Python modules and not referenced by tests
- `wizards/allegro/home/skills/red-teaming/godmode/scripts/parseltongue.py` — not imported by indexed Python modules and not referenced by tests
- `twitter-archive/multimodal_pipeline.py` — not imported by indexed Python modules and not referenced by tests
- `wizards/allegro/home/skills/red-teaming/godmode/scripts/godmode_race.py` — not imported by indexed Python modules and not referenced by tests
- `skills/productivity/google-workspace/scripts/google_api.py` — not imported by indexed Python modules and not referenced by tests
- `wizards/allegro/home/skills/productivity/google-workspace/scripts/google_api.py` — not imported by indexed Python modules and not referenced by tests
- `morrowind/pilot.py` — not imported by indexed Python modules and not referenced by tests
- `morrowind/mcp_server.py` — not imported by indexed Python modules and not referenced by tests
- `skills/research/domain-intel/scripts/domain_intel.py` — not imported by indexed Python modules and not referenced by tests
This API surface is broad enough that timmy-config is functionally an operations SDK as much as a config repo.
## Performance Bottleneck Analysis
## Test Coverage Gaps
- `angband/mcp_server.py` — large module (353 lines) likely hides multiple responsibilities
- `evennia/timmy_world/game.py` — large module (1541 lines) likely hides multiple responsibilities
- `evennia/timmy_world/world/game.py` — large module (1345 lines) likely hides multiple responsibilities
- `morrowind/mcp_server.py` — large module (451 lines) likely hides multiple responsibilities
- `morrowind/pilot.py` — large module (459 lines) likely hides multiple responsibilities
- `pipelines/codebase_genome.py` — large module (557 lines) likely hides multiple responsibilities
- `scripts/know_thy_father/crossref_audit.py` — large module (657 lines) likely hides multiple responsibilities
- `scripts/know_thy_father/index_media.py` — large module (405 lines) likely hides multiple responsibilities
- `scripts/know_thy_father/synthesize_kernels.py` — large module (416 lines) likely hides multiple responsibilities
- `scripts/tower_game.py` — large module (395 lines) likely hides multiple responsibilities
The codebase-genome pipeline estimated:
- source modules: 86
- test modules: 36
- estimated coverage: 15%
- untested modules: 73
That estimate is crude, but directionally useful.
### High-value gaps
The most important untested or under-tested areas are not random scripts. They are the system boundary scripts and operator-critical surfaces:
1. `deploy.sh`
- highest leverage file in the repo
- if deploy breaks, the sidecar stops being the source of truth in practice
2. `orchestration.py` and large portions of `tasks.py`
- especially scheduling, local-Hermes execution wrappers, checkpoint/state flows, and failure modes
3. `gitea_client.py`
- some behavior may be covered indirectly, but the client is important enough to deserve deeper contract tests for pagination, merge failures, 405 handling, and retry behavior
4. `bin/*` operational scripts
- deadman, watchdog, model health, and dispatch paths are safety critical
5. Ansible deployment surface
- `ansible/playbooks/*` and `ansible/roles/*` are configuration-heavy but still represent production behavior
### Practical takeaway
If the next wave of testing work is prioritized, the order should be:
1. deploy + runtime overlay correctness
2. Gitea client contracts
3. queue/task execution behavior in `tasks.py`
4. deadman / watchdog / fleet-health scripts
5. training and archive helper edge cases
## Security Considerations
The pipeline already flags several categories, and manual review supports them.
### 1. Subprocess-heavy code
This repo uses shell and subprocess execution widely.
That is expected for an ops repo, but it increases command-injection risk.
Files like `tasks.py`, deployment helpers, and many `bin/*` scripts need careful boundary checking around interpolated inputs.
### 2. Secret adjacency
This repo references tokens, auth files, routing configs, and platform integrations.
Even when secrets are not hardcoded, the repo lives close to sensitive paths.
That means review discipline matters:
- no accidental dumps of live tokens
- no committing generated auth artifacts
- no relaxed assumptions about local paths being safe to expose
### 3. HTTP and webhook surfaces
Multiple scripts make outbound HTTP calls or serve automation endpoints.
This means input validation, response validation, and timeout/error handling matter more than in a static config repo.
### 4. SQLite and file-backed state
SQLite/Huey plus JSON/JSONL file state are simple and sovereign, but they create corruption and stale-state risks if writes are partial or multiple writers race.
The repo already encodes a strong preference for explicit checkpoints and continuity flushes, which is the right direction.
### 5. Sidecar privilege
Because `deploy.sh` writes directly into `~/.hermes/`, this repo effectively has configuration authority over the live runtime.
That is powerful and dangerous. A bad deploy can break routing, scripts, or identity. In security terms, this repo is a control plane.
## Performance Characteristics
`timmy-config` is not performance-sensitive in the same way a game loop or serving stack is. Its performance profile is operational:
- Many small scripts, low-latency startup expectations
- File-backed state and JSONL append patterns optimized for simplicity over throughput
- Huey + SQLite chosen for low operational overhead, not horizontal scale
- Deployment is copy-based and cheap; correctness matters more than speed
- The repo is large in surface area but shallow in runtime residency — most code runs only when called
Practical performance characteristics:
- deploy path should remain fast because it is mostly file copies
- Gitea automation cost is network-bound, not CPU-bound
- training helpers are the heaviest local operations but intentionally limited in scope
- orchestration latency is dominated by external model/API calls rather than Python compute
The biggest performance risk is not CPU.
It is operational drift: too many scripts, overlapping logic, or old paths that still appear to exist. That increases human debugging cost even when machine runtime is fine.
## Final Assessment
`timmy-config` is best understood as a sovereign control plane.
It is part config repo, part operations toolkit, part lightweight SDK, and part deployment overlay.
Its strongest architectural idea is the boundary:
- keep Hermes upstream
- keep Timmy sovereign through the sidecar
- keep lived work in timmy-home
Its biggest risk is sprawl.
A repo with 178 source files and 393 commits can easily become the place where every operational idea goes to live forever.
The right long-term direction is not to make it smaller by deleting its authority, but to keep sharpening the boundaries inside it:
- sidecar deploy surface
- queue/orchestration surface
- Gitea client surface
- training recipe surface
- operator script surface
That keeps the genome legible.
Without that, the repo becomes powerful but opaque — and a control plane cannot afford opacity.

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# Codebase Genome Pipeline
Issue: `timmy-home#665`
This pipeline gives Timmy a repeatable way to generate a deterministic `GENOME.md` for any repository and rotate through the org nightly.
## What landed
- `pipelines/codebase_genome.py` — static analyzer that writes `GENOME.md`
- `pipelines/codebase-genome.py` — thin CLI wrapper matching the expected pipeline-style entrypoint
- `scripts/codebase_genome_nightly.py` — org-aware nightly runner that selects the next repo, updates a local checkout, and writes the genome artifact
- `GENOME.md` — generated analysis for `timmy-home` itself
## Genome output
Each generated `GENOME.md` includes:
- project overview and repository size metrics
- Mermaid architecture diagram
- entry points and API surface
- data flow summary
- key abstractions from Python source
- test coverage gaps
- security audit findings
- dead code candidates
- performance bottleneck analysis
## Single-repo usage
```bash
python3 pipelines/codebase_genome.py \
--repo-root /path/to/repo \
--repo-name Timmy_Foundation/some-repo \
--output /path/to/repo/GENOME.md
```
The hyphenated wrapper also works:
```bash
python3 pipelines/codebase-genome.py --repo-root /path/to/repo --repo Timmy_Foundation/some-repo
```
## Nightly org rotation
Dry-run the next selection:
```bash
python3 scripts/codebase_genome_nightly.py --dry-run
```
Run one real pass:
```bash
python3 scripts/codebase_genome_nightly.py \
--org Timmy_Foundation \
--workspace-root ~/timmy-foundation-repos \
--output-root ~/.timmy/codebase-genomes \
--state-path ~/.timmy/codebase_genome_state.json
```
Behavior:
1. fetches the current repo list from Gitea
2. selects the next repo after the last recorded run
3. clones or fast-forwards the local checkout
4. writes `GENOME.md` into the configured output tree
5. updates the rotation state file
## Example cron entry
```cron
30 2 * * * cd ~/timmy-home && /usr/bin/env python3 scripts/codebase_genome_nightly.py --org Timmy_Foundation --workspace-root ~/timmy-foundation-repos --output-root ~/.timmy/codebase-genomes --state-path ~/.timmy/codebase_genome_state.json >> ~/.timmy/logs/codebase_genome_nightly.log 2>&1
```
## Limits and follow-ons
- the generator is deterministic and static; it does not hallucinate architecture, but it also does not replace a full human review pass
- nightly rotation handles genome generation; auto-generated test expansion remains a separate follow-on lane
- large repos may still need a second-pass human edit after the initial genome artifact lands

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@@ -12,7 +12,6 @@ Quick-reference index for common operational tasks across the Timmy Foundation i
| Check fleet health | fleet-ops | `python3 scripts/fleet_readiness.py` |
| Agent scorecard | fleet-ops | `python3 scripts/agent_scorecard.py` |
| View fleet manifest | fleet-ops | `cat manifest.yaml` |
| Run nightly codebase genome pass | timmy-home | `python3 scripts/codebase_genome_nightly.py --dry-run` |
## the-nexus (Frontend + Brain)

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@@ -1 +0,0 @@
"""Codebase genome pipeline helpers."""

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@@ -1,6 +0,0 @@
#!/usr/bin/env python3
from codebase_genome import main
if __name__ == "__main__":
main()

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@@ -1,557 +0,0 @@
#!/usr/bin/env python3
"""Generate a deterministic GENOME.md for a repository."""
from __future__ import annotations
import argparse
import ast
import os
import re
from pathlib import Path
from typing import NamedTuple
IGNORED_DIRS = {
".git",
".hg",
".svn",
".venv",
"venv",
"node_modules",
"__pycache__",
".mypy_cache",
".pytest_cache",
"dist",
"build",
"coverage",
}
TEXT_SUFFIXES = {
".py",
".js",
".mjs",
".cjs",
".ts",
".tsx",
".jsx",
".html",
".css",
".md",
".txt",
".json",
".yaml",
".yml",
".sh",
".ini",
".cfg",
".toml",
}
SOURCE_SUFFIXES = {".py", ".js", ".mjs", ".cjs", ".ts", ".tsx", ".jsx", ".sh"}
DOC_FILENAMES = {"README.md", "CONTRIBUTING.md", "SOUL.md"}
class RepoFile(NamedTuple):
path: str
abs_path: Path
size_bytes: int
line_count: int
kind: str
class RunSummary(NamedTuple):
markdown: str
source_count: int
test_count: int
doc_count: int
def _is_text_file(path: Path) -> bool:
return path.suffix.lower() in TEXT_SUFFIXES or path.name in {"Dockerfile", "Makefile"}
def _file_kind(rel_path: str, path: Path) -> str:
suffix = path.suffix.lower()
if rel_path.startswith("tests/") or path.name.startswith("test_"):
return "test"
if rel_path.startswith("docs/") or path.name in DOC_FILENAMES or suffix == ".md":
return "doc"
if suffix in {".json", ".yaml", ".yml", ".toml", ".ini", ".cfg"}:
return "config"
if suffix == ".sh":
return "script"
if rel_path.startswith("scripts/") and suffix == ".py" and path.name != "__init__.py":
return "script"
if suffix in SOURCE_SUFFIXES:
return "source"
return "other"
def collect_repo_files(repo_root: str | Path) -> list[RepoFile]:
root = Path(repo_root).resolve()
files: list[RepoFile] = []
for current_root, dirnames, filenames in os.walk(root):
dirnames[:] = sorted(d for d in dirnames if d not in IGNORED_DIRS)
base = Path(current_root)
for filename in sorted(filenames):
path = base / filename
if not _is_text_file(path):
continue
rel_path = path.relative_to(root).as_posix()
text = path.read_text(encoding="utf-8", errors="replace")
files.append(
RepoFile(
path=rel_path,
abs_path=path,
size_bytes=path.stat().st_size,
line_count=max(1, len(text.splitlines())),
kind=_file_kind(rel_path, path),
)
)
return sorted(files, key=lambda item: item.path)
def _safe_text(path: Path) -> str:
return path.read_text(encoding="utf-8", errors="replace")
def _sanitize_node_id(name: str) -> str:
cleaned = re.sub(r"[^A-Za-z0-9_]", "_", name)
return cleaned or "node"
def _component_name(path: str) -> str:
if "/" in path:
return path.split("/", 1)[0]
return Path(path).stem or path
def _priority_files(files: list[RepoFile], kinds: tuple[str, ...], limit: int = 8) -> list[RepoFile]:
items = [item for item in files if item.kind in kinds]
items.sort(key=lambda item: (-int(item.path.count("/") == 0), -item.line_count, item.path))
return items[:limit]
def _readme_summary(root: Path) -> str:
readme = root / "README.md"
if not readme.exists():
return "Repository-specific overview missing from README.md. Genome generated from code structure and tests."
paragraphs: list[str] = []
current: list[str] = []
for raw_line in _safe_text(readme).splitlines():
line = raw_line.strip()
if not line:
if current:
paragraphs.append(" ".join(current).strip())
current = []
continue
if line.startswith("#"):
continue
current.append(line)
if current:
paragraphs.append(" ".join(current).strip())
return paragraphs[0] if paragraphs else "README.md exists but does not contain a prose overview paragraph."
def _extract_python_imports(text: str) -> set[str]:
try:
tree = ast.parse(text)
except SyntaxError:
return set()
imports: set[str] = set()
for node in ast.walk(tree):
if isinstance(node, ast.Import):
for alias in node.names:
imports.add(alias.name.split(".", 1)[0])
elif isinstance(node, ast.ImportFrom):
if node.module:
imports.add(node.module.split(".", 1)[0])
return imports
def _extract_python_symbols(text: str) -> tuple[list[tuple[str, int]], list[tuple[str, int]]]:
try:
tree = ast.parse(text)
except SyntaxError:
return [], []
classes: list[tuple[str, int]] = []
functions: list[tuple[str, int]] = []
for node in tree.body:
if isinstance(node, ast.ClassDef):
classes.append((node.name, node.lineno))
elif isinstance(node, ast.FunctionDef):
functions.append((node.name, node.lineno))
return classes, functions
def _build_component_edges(files: list[RepoFile]) -> list[tuple[str, str]]:
known_components = {_component_name(item.path) for item in files if item.kind in {"source", "script", "test"}}
edges: set[tuple[str, str]] = set()
for item in files:
if item.kind not in {"source", "script", "test"} or item.abs_path.suffix.lower() != ".py":
continue
src = _component_name(item.path)
imports = _extract_python_imports(_safe_text(item.abs_path))
for imported in imports:
if imported in known_components and imported != src:
edges.add((src, imported))
return sorted(edges)
def _render_mermaid(files: list[RepoFile]) -> str:
components = sorted(
{
_component_name(item.path)
for item in files
if item.kind in {"source", "script", "test", "config"}
and not _component_name(item.path).startswith(".")
}
)
edges = _build_component_edges(files)
lines = ["graph TD"]
if not components:
lines.append(" repo[\"repository\"]")
return "\n".join(lines)
for component in components[:10]:
node_id = _sanitize_node_id(component)
lines.append(f" {node_id}[\"{component}\"]")
seen_components = set(components[:10])
emitted = False
for src, dst in edges:
if src in seen_components and dst in seen_components:
lines.append(f" {_sanitize_node_id(src)} --> {_sanitize_node_id(dst)}")
emitted = True
if not emitted:
root_id = "repo_root"
lines.insert(1, f" {root_id}[\"repo\"]")
for component in components[:6]:
lines.append(f" {root_id} --> {_sanitize_node_id(component)}")
return "\n".join(lines)
def _entry_points(files: list[RepoFile]) -> list[dict[str, str]]:
points: list[dict[str, str]] = []
for item in files:
text = _safe_text(item.abs_path)
if item.kind == "script":
points.append({"path": item.path, "reason": "operational script", "command": f"python3 {item.path}" if item.abs_path.suffix == ".py" else f"bash {item.path}"})
continue
if item.abs_path.suffix == ".py" and "if __name__ == '__main__':" in text:
points.append({"path": item.path, "reason": "python main guard", "command": f"python3 {item.path}"})
elif item.path in {"app.py", "server.py", "main.py"}:
points.append({"path": item.path, "reason": "top-level executable", "command": f"python3 {item.path}"})
seen: set[str] = set()
deduped: list[dict[str, str]] = []
for point in points:
if point["path"] in seen:
continue
seen.add(point["path"])
deduped.append(point)
return deduped[:12]
def _test_coverage(files: list[RepoFile]) -> tuple[list[RepoFile], list[RepoFile], list[RepoFile]]:
source_files = [
item
for item in files
if item.kind in {"source", "script"}
and item.path not in {"pipelines/codebase-genome.py", "pipelines/codebase_genome.py"}
and not item.path.endswith("/__init__.py")
]
test_files = [item for item in files if item.kind == "test"]
combined_test_text = "\n".join(_safe_text(item.abs_path) for item in test_files)
entry_paths = {point["path"] for point in _entry_points(files)}
gaps: list[RepoFile] = []
for item in source_files:
stem = item.abs_path.stem
if item.path in entry_paths:
continue
if stem and stem in combined_test_text:
continue
gaps.append(item)
gaps.sort(key=lambda item: (-item.line_count, item.path))
return source_files, test_files, gaps
def _security_findings(files: list[RepoFile]) -> list[dict[str, str]]:
rules = [
("high", "shell execution", re.compile(r"shell\s*=\s*True"), "shell=True expands blast radius for command execution"),
("high", "dynamic evaluation", re.compile(r"\b(eval|exec)\s*\("), "dynamic evaluation bypasses static guarantees"),
("medium", "unsafe deserialization", re.compile(r"pickle\.load\(|yaml\.load\("), "deserialization of untrusted data can execute code"),
("medium", "network egress", re.compile(r"urllib\.request\.urlopen\(|requests\.(get|post|put|delete)\("), "outbound network calls create runtime dependency and failure surface"),
("medium", "hardcoded http endpoint", re.compile(r"http://[^\s\"']+"), "plaintext or fixed HTTP endpoints can drift or leak across environments"),
]
findings: list[dict[str, str]] = []
for item in files:
if item.kind not in {"source", "script", "config"}:
continue
for lineno, line in enumerate(_safe_text(item.abs_path).splitlines(), start=1):
for severity, category, pattern, detail in rules:
if pattern.search(line):
findings.append(
{
"severity": severity,
"category": category,
"ref": f"{item.path}:{lineno}",
"line": line.strip(),
"detail": detail,
}
)
break
if len(findings) >= 12:
return findings
return findings
def _dead_code_candidates(files: list[RepoFile]) -> list[RepoFile]:
source_files = [item for item in files if item.kind in {"source", "script"} and item.abs_path.suffix == ".py"]
imports_by_file = {
item.path: _extract_python_imports(_safe_text(item.abs_path))
for item in source_files
}
imported_names = {name for imports in imports_by_file.values() for name in imports}
referenced_by_tests = "\n".join(_safe_text(item.abs_path) for item in files if item.kind == "test")
entry_paths = {point["path"] for point in _entry_points(files)}
candidates: list[RepoFile] = []
for item in source_files:
stem = item.abs_path.stem
if item.path in entry_paths:
continue
if stem in imported_names:
continue
if stem in referenced_by_tests:
continue
if stem in {"__init__", "conftest"}:
continue
candidates.append(item)
candidates.sort(key=lambda item: (-item.line_count, item.path))
return candidates[:10]
def _performance_findings(files: list[RepoFile]) -> list[dict[str, str]]:
findings: list[dict[str, str]] = []
for item in files:
if item.kind in {"source", "script"} and item.line_count >= 350:
findings.append({
"ref": item.path,
"detail": f"large module ({item.line_count} lines) likely hides multiple responsibilities",
})
for item in files:
if item.kind not in {"source", "script"}:
continue
text = _safe_text(item.abs_path)
if "os.walk(" in text or ".rglob(" in text or "glob.glob(" in text:
findings.append({
"ref": item.path,
"detail": "per-run filesystem scan detected; performance scales with repo size",
})
if "urllib.request.urlopen(" in text or "requests.get(" in text or "requests.post(" in text:
findings.append({
"ref": item.path,
"detail": "network-bound execution path can dominate runtime and create flaky throughput",
})
deduped: list[dict[str, str]] = []
seen: set[tuple[str, str]] = set()
for finding in findings:
key = (finding["ref"], finding["detail"])
if key in seen:
continue
seen.add(key)
deduped.append(finding)
return deduped[:10]
def _key_abstractions(files: list[RepoFile]) -> list[dict[str, object]]:
abstractions: list[dict[str, object]] = []
for item in _priority_files(files, ("source", "script"), limit=10):
if item.abs_path.suffix != ".py":
continue
classes, functions = _extract_python_symbols(_safe_text(item.abs_path))
if not classes and not functions:
continue
abstractions.append(
{
"path": item.path,
"classes": classes[:4],
"functions": [entry for entry in functions[:6] if not entry[0].startswith("_")],
}
)
return abstractions[:8]
def _api_surface(entry_points: list[dict[str, str]], abstractions: list[dict[str, object]]) -> list[str]:
api_lines: list[str] = []
for entry in entry_points[:8]:
api_lines.append(f"- CLI: `{entry['command']}` — {entry['reason']} (`{entry['path']}`)")
for abstraction in abstractions[:5]:
for func_name, lineno in abstraction["functions"]:
api_lines.append(f"- Python: `{func_name}()` from `{abstraction['path']}:{lineno}`")
if len(api_lines) >= 14:
return api_lines
return api_lines
def _data_flow(entry_points: list[dict[str, str]], files: list[RepoFile], gaps: list[RepoFile]) -> list[str]:
components = sorted(
{
_component_name(item.path)
for item in files
if item.kind in {"source", "script", "test", "config"} and not _component_name(item.path).startswith(".")
}
)
lines = []
if entry_points:
lines.append(f"1. Operators enter through {', '.join(f'`{item['path']}`' for item in entry_points[:3])}.")
else:
lines.append("1. No explicit CLI/main guard entry point was detected; execution appears library- or doc-driven.")
if components:
lines.append(f"2. Core logic fans into top-level components: {', '.join(f'`{name}`' for name in components[:6])}.")
if gaps:
lines.append(f"3. Validation is incomplete around {', '.join(f'`{item.path}`' for item in gaps[:3])}, so changes there carry regression risk.")
else:
lines.append("3. Tests appear to reference the currently indexed source set, reducing blind spots in the hot path.")
lines.append("4. Final artifacts land as repository files, docs, or runtime side effects depending on the selected entry point.")
return lines
def generate_genome_markdown(repo_root: str | Path, repo_name: str | None = None) -> str:
root = Path(repo_root).resolve()
files = collect_repo_files(root)
repo_display = repo_name or root.name
summary = _readme_summary(root)
entry_points = _entry_points(files)
source_files, test_files, coverage_gaps = _test_coverage(files)
security = _security_findings(files)
dead_code = _dead_code_candidates(files)
performance = _performance_findings(files)
abstractions = _key_abstractions(files)
api_surface = _api_surface(entry_points, abstractions)
data_flow = _data_flow(entry_points, files, coverage_gaps)
mermaid = _render_mermaid(files)
lines: list[str] = [
f"# GENOME.md — {repo_display}",
"",
"Generated by `pipelines/codebase_genome.py`.",
"",
"## Project Overview",
"",
summary,
"",
f"- Text files indexed: {len(files)}",
f"- Source and script files: {len(source_files)}",
f"- Test files: {len(test_files)}",
f"- Documentation files: {len([item for item in files if item.kind == 'doc'])}",
"",
"## Architecture",
"",
"```mermaid",
mermaid,
"```",
"",
"## Entry Points",
"",
]
if entry_points:
for item in entry_points:
lines.append(f"- `{item['path']}` — {item['reason']} (`{item['command']}`)")
else:
lines.append("- No explicit entry point detected.")
lines.extend(["", "## Data Flow", ""])
lines.extend(data_flow)
lines.extend(["", "## Key Abstractions", ""])
if abstractions:
for abstraction in abstractions:
path = abstraction["path"]
classes = abstraction["classes"]
functions = abstraction["functions"]
class_bits = ", ".join(f"`{name}`:{lineno}" for name, lineno in classes) or "none detected"
function_bits = ", ".join(f"`{name}()`:{lineno}" for name, lineno in functions) or "none detected"
lines.append(f"- `{path}` — classes {class_bits}; functions {function_bits}")
else:
lines.append("- No Python classes or top-level functions detected in the highest-priority source files.")
lines.extend(["", "## API Surface", ""])
if api_surface:
lines.extend(api_surface)
else:
lines.append("- No obvious public API surface detected.")
lines.extend(["", "## Test Coverage Report", ""])
lines.append(f"- Source and script files inspected: {len(source_files)}")
lines.append(f"- Test files inspected: {len(test_files)}")
if coverage_gaps:
lines.append("- Coverage gaps:")
for item in coverage_gaps[:12]:
lines.append(f" - `{item.path}` — no matching test reference detected")
else:
lines.append("- No obvious coverage gaps detected by the stem-matching heuristic.")
lines.extend(["", "## Security Audit Findings", ""])
if security:
for finding in security:
lines.append(
f"- [{finding['severity']}] `{finding['ref']}` — {finding['category']}: {finding['detail']}. Evidence: `{finding['line']}`"
)
else:
lines.append("- No high-signal security findings detected by the static heuristics in this pass.")
lines.extend(["", "## Dead Code Candidates", ""])
if dead_code:
for item in dead_code:
lines.append(f"- `{item.path}` — not imported by indexed Python modules and not referenced by tests")
else:
lines.append("- No obvious dead-code candidates detected.")
lines.extend(["", "## Performance Bottleneck Analysis", ""])
if performance:
for finding in performance:
lines.append(f"- `{finding['ref']}` — {finding['detail']}")
else:
lines.append("- No obvious performance hotspots detected by the static heuristics in this pass.")
return "\n".join(lines).rstrip() + "\n"
def write_genome(repo_root: str | Path, repo_name: str | None = None, output_path: str | Path | None = None) -> RunSummary:
root = Path(repo_root).resolve()
markdown = generate_genome_markdown(root, repo_name=repo_name)
out_path = Path(output_path) if output_path else root / "GENOME.md"
out_path.parent.mkdir(parents=True, exist_ok=True)
out_path.write_text(markdown, encoding="utf-8")
files = collect_repo_files(root)
source_files, test_files, _ = _test_coverage(files)
return RunSummary(
markdown=markdown,
source_count=len(source_files),
test_count=len(test_files),
doc_count=len([item for item in files if item.kind == "doc"]),
)
def main() -> None:
parser = argparse.ArgumentParser(description="Generate a deterministic GENOME.md for a repository")
parser.add_argument("--repo-root", required=True, help="Path to the repository to analyze")
parser.add_argument("--repo", dest="repo_name", default=None, help="Optional repo display name")
parser.add_argument("--repo-name", dest="repo_name_override", default=None, help="Optional repo display name")
parser.add_argument("--output", default=None, help="Path to write GENOME.md (defaults to <repo-root>/GENOME.md)")
args = parser.parse_args()
repo_name = args.repo_name_override or args.repo_name
summary = write_genome(args.repo_root, repo_name=repo_name, output_path=args.output)
target = Path(args.output) if args.output else Path(args.repo_root).resolve() / "GENOME.md"
print(
f"GENOME.md saved to {target} "
f"(sources={summary.source_count}, tests={summary.test_count}, docs={summary.doc_count})"
)
if __name__ == "__main__":
main()

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@@ -1,171 +0,0 @@
#!/usr/bin/env python3
"""Nightly runner for the codebase genome pipeline."""
from __future__ import annotations
import argparse
import json
import os
import subprocess
import sys
import urllib.request
from pathlib import Path
from typing import NamedTuple
class RunPlan(NamedTuple):
repo: dict
repo_dir: Path
output_path: Path
command: list[str]
def load_state(path: Path) -> dict:
if not path.exists():
return {}
return json.loads(path.read_text(encoding="utf-8"))
def save_state(path: Path, state: dict) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(json.dumps(state, indent=2, sort_keys=True), encoding="utf-8")
def select_next_repo(repos: list[dict], state: dict) -> dict:
if not repos:
raise ValueError("no repositories available for nightly genome run")
ordered = sorted(repos, key=lambda item: item.get("full_name", item.get("name", "")).lower())
last_repo = state.get("last_repo")
for index, repo in enumerate(ordered):
if repo.get("name") == last_repo or repo.get("full_name") == last_repo:
return ordered[(index + 1) % len(ordered)]
last_index = int(state.get("last_index", -1))
return ordered[(last_index + 1) % len(ordered)]
def build_run_plan(repo: dict, workspace_root: Path, output_root: Path, pipeline_script: Path) -> RunPlan:
repo_dir = workspace_root / repo["name"]
output_path = output_root / repo["name"] / "GENOME.md"
command = [
sys.executable,
str(pipeline_script),
"--repo-root",
str(repo_dir),
"--repo-name",
repo.get("full_name", repo["name"]),
"--output",
str(output_path),
]
return RunPlan(repo=repo, repo_dir=repo_dir, output_path=output_path, command=command)
def fetch_org_repos(org: str, host: str, token_file: Path, include_archived: bool = False) -> list[dict]:
token = token_file.read_text(encoding="utf-8").strip()
page = 1
repos: list[dict] = []
while True:
req = urllib.request.Request(
f"{host.rstrip('/')}/api/v1/orgs/{org}/repos?limit=100&page={page}",
headers={"Authorization": f"token {token}", "Accept": "application/json"},
)
with urllib.request.urlopen(req, timeout=30) as resp:
chunk = json.loads(resp.read().decode("utf-8"))
if not chunk:
break
for item in chunk:
if item.get("archived") and not include_archived:
continue
repos.append(
{
"name": item["name"],
"full_name": item["full_name"],
"clone_url": item["clone_url"],
"default_branch": item.get("default_branch") or "main",
}
)
page += 1
return repos
def _authenticated_clone_url(clone_url: str, token_file: Path) -> str:
token = token_file.read_text(encoding="utf-8").strip()
if clone_url.startswith("https://"):
return f"https://{token}@{clone_url[len('https://') :]}"
return clone_url
def ensure_checkout(repo: dict, workspace_root: Path, token_file: Path) -> Path:
workspace_root.mkdir(parents=True, exist_ok=True)
repo_dir = workspace_root / repo["name"]
branch = repo.get("default_branch") or "main"
clone_url = _authenticated_clone_url(repo["clone_url"], token_file)
if (repo_dir / ".git").exists():
subprocess.run(["git", "-C", str(repo_dir), "fetch", "origin", branch, "--depth", "1"], check=True)
subprocess.run(["git", "-C", str(repo_dir), "checkout", branch], check=True)
subprocess.run(["git", "-C", str(repo_dir), "reset", "--hard", f"origin/{branch}"], check=True)
else:
subprocess.run(
["git", "clone", "--depth", "1", "--single-branch", "--branch", branch, clone_url, str(repo_dir)],
check=True,
)
return repo_dir
def run_plan(plan: RunPlan) -> None:
plan.output_path.parent.mkdir(parents=True, exist_ok=True)
subprocess.run(plan.command, check=True)
def main() -> None:
parser = argparse.ArgumentParser(description="Run one nightly codebase genome pass for the next repo in an org")
parser.add_argument("--org", default="Timmy_Foundation")
parser.add_argument("--host", default="https://forge.alexanderwhitestone.com")
parser.add_argument("--token-file", default=os.path.expanduser("~/.config/gitea/token"))
parser.add_argument("--workspace-root", default=os.path.expanduser("~/timmy-foundation-repos"))
parser.add_argument("--output-root", default=os.path.expanduser("~/.timmy/codebase-genomes"))
parser.add_argument("--state-path", default=os.path.expanduser("~/.timmy/codebase_genome_state.json"))
parser.add_argument("--pipeline-script", default=str(Path(__file__).resolve().parents[1] / "pipelines" / "codebase_genome.py"))
parser.add_argument("--include-archived", action="store_true")
parser.add_argument("--dry-run", action="store_true")
args = parser.parse_args()
token_file = Path(args.token_file).expanduser()
workspace_root = Path(args.workspace_root).expanduser()
output_root = Path(args.output_root).expanduser()
state_path = Path(args.state_path).expanduser()
pipeline_script = Path(args.pipeline_script).expanduser()
repos = fetch_org_repos(args.org, args.host, token_file, include_archived=args.include_archived)
state = load_state(state_path)
repo = select_next_repo(repos, state)
plan = build_run_plan(repo, workspace_root=workspace_root, output_root=output_root, pipeline_script=pipeline_script)
if args.dry_run:
print(
json.dumps(
{
"repo": repo,
"repo_dir": str(plan.repo_dir),
"output_path": str(plan.output_path),
"command": plan.command,
},
indent=2,
)
)
return
ensure_checkout(repo, workspace_root=workspace_root, token_file=token_file)
run_plan(plan)
save_state(
state_path,
{
"last_index": sorted(repos, key=lambda item: item.get("full_name", item.get("name", "")).lower()).index(repo),
"last_repo": repo.get("name"),
},
)
print(f"Completed genome run for {repo['full_name']} -> {plan.output_path}")
if __name__ == "__main__":
main()

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@@ -1,115 +0,0 @@
from __future__ import annotations
import importlib.util
from pathlib import Path
ROOT = Path(__file__).resolve().parents[1]
PIPELINE_PATH = ROOT / "pipelines" / "codebase_genome.py"
NIGHTLY_PATH = ROOT / "scripts" / "codebase_genome_nightly.py"
GENOME_PATH = ROOT / "GENOME.md"
def _load_module(path: Path, name: str):
assert path.exists(), f"missing {path.relative_to(ROOT)}"
spec = importlib.util.spec_from_file_location(name, path)
assert spec and spec.loader
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
def test_generate_genome_markdown_contains_required_sections(tmp_path: Path) -> None:
genome_mod = _load_module(PIPELINE_PATH, "codebase_genome")
repo = tmp_path / "repo"
(repo / "tests").mkdir(parents=True)
(repo / "README.md").write_text("# Demo Repo\n\nA tiny example repo.\n")
(repo / "app.py").write_text(
"import module\n\n"
"def main():\n"
" return module.Helper().answer()\n\n"
"if __name__ == '__main__':\n"
" raise SystemExit(main())\n"
)
(repo / "module.py").write_text(
"class Helper:\n"
" def answer(self):\n"
" return 42\n"
)
(repo / "dangerous.py").write_text(
"import subprocess\n\n"
"def run_shell(cmd):\n"
" return subprocess.run(cmd, shell=True, check=False)\n"
)
(repo / "extra.py").write_text("VALUE = 7\n")
(repo / "tests" / "test_app.py").write_text(
"from app import main\n\n"
"def test_main():\n"
" assert main() == 42\n"
)
genome = genome_mod.generate_genome_markdown(repo, repo_name="org/repo")
for heading in (
"# GENOME.md — org/repo",
"## Project Overview",
"## Architecture",
"```mermaid",
"## Entry Points",
"## Data Flow",
"## Key Abstractions",
"## API Surface",
"## Test Coverage Report",
"## Security Audit Findings",
"## Dead Code Candidates",
"## Performance Bottleneck Analysis",
):
assert heading in genome
assert "app.py" in genome
assert "module.py" in genome
assert "dangerous.py" in genome
assert "extra.py" in genome
assert "shell=True" in genome
def test_nightly_runner_rotates_repos_and_builds_plan() -> None:
nightly_mod = _load_module(NIGHTLY_PATH, "codebase_genome_nightly")
repos = [
{"name": "alpha", "full_name": "Timmy_Foundation/alpha", "clone_url": "https://example/alpha.git"},
{"name": "beta", "full_name": "Timmy_Foundation/beta", "clone_url": "https://example/beta.git"},
]
state = {"last_index": 0, "last_repo": "alpha"}
next_repo = nightly_mod.select_next_repo(repos, state)
assert next_repo["name"] == "beta"
plan = nightly_mod.build_run_plan(
repo=next_repo,
workspace_root=Path("/tmp/repos"),
output_root=Path("/tmp/genomes"),
pipeline_script=Path("/tmp/timmy-home/pipelines/codebase_genome.py"),
)
assert plan.repo_dir == Path("/tmp/repos/beta")
assert plan.output_path == Path("/tmp/genomes/beta/GENOME.md")
assert "codebase_genome.py" in plan.command[1]
assert plan.command[-1] == "/tmp/genomes/beta/GENOME.md"
def test_repo_contains_generated_timmy_home_genome() -> None:
assert GENOME_PATH.exists(), "missing generated GENOME.md for timmy-home"
text = GENOME_PATH.read_text(encoding="utf-8")
for snippet in (
"# GENOME.md — Timmy_Foundation/timmy-home",
"## Project Overview",
"## Architecture",
"## Entry Points",
"## API Surface",
"## Test Coverage Report",
"## Security Audit Findings",
"## Performance Bottleneck Analysis",
):
assert snippet in text

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from pathlib import Path
GENOME = Path('GENOME.md')
def read_genome() -> str:
assert GENOME.exists(), 'GENOME.md must exist at repo root'
return GENOME.read_text(encoding='utf-8')
def test_genome_exists():
assert GENOME.exists(), 'GENOME.md must exist at repo root'
def test_genome_has_required_sections():
text = read_genome()
for heading in [
'# GENOME.md — timmy-config',
'## Project Overview',
'## Architecture Diagram',
'## Entry Points and Data Flow',
'## Key Abstractions',
'## API Surface',
'## Test Coverage Gaps',
'## Security Considerations',
'## Performance Characteristics',
]:
assert heading in text
def test_genome_contains_mermaid_diagram():
text = read_genome()
assert '```mermaid' in text
assert 'graph TD' in text or 'flowchart TD' in text
def test_genome_mentions_core_timmy_config_files():
text = read_genome()
for token in [
'deploy.sh',
'config.yaml',
'gitea_client.py',
'orchestration.py',
'tasks.py',
'bin/',
'playbooks/',
'training/',
]:
assert token in text
def test_genome_explains_sidecar_boundary():
text = read_genome()
assert 'sidecar' in text.lower()
assert 'Hermes' in text
assert 'timmy-home' in text
def test_genome_is_substantial():
text = read_genome()
assert len(text) >= 5000