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Author SHA1 Message Date
d0e4e00ba1 chore: claw-code progress on #151
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Forge CI / smoke-and-build (pull_request) Failing after 4s
Refs #151
2026-04-07 00:03:57 -04:00
13 changed files with 1 additions and 472 deletions

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@@ -13,7 +13,6 @@ concurrency:
jobs:
smoke-and-build:
runs-on: ubuntu-latest
container: catthehacker/ubuntu:act-22.04
timeout-minutes: 5
steps:
- name: Checkout code
@@ -21,9 +20,6 @@ jobs:
- name: Install uv
uses: astral-sh/setup-uv@v5
with:
enable-cache: true
cache-dependency-glob: "uv.lock"
- name: Set up Python 3.11
run: uv python install 3.11

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@@ -11,7 +11,6 @@ on:
jobs:
notebook-smoke:
runs-on: ubuntu-latest
container: catthehacker/ubuntu:act-22.04
steps:
- name: Checkout
uses: actions/checkout@v4

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@@ -19,7 +19,6 @@ jobs:
audit:
name: Audit Python dependencies
runs-on: ubuntu-latest
container: catthehacker/ubuntu:act-22.04
steps:
- uses: actions/checkout@v4
- uses: astral-sh/setup-uv@v5

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@@ -10,7 +10,6 @@ on:
jobs:
docs-site-checks:
runs-on: ubuntu-latest
container: catthehacker/ubuntu:act-22.04
steps:
- uses: actions/checkout@v4

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@@ -19,7 +19,6 @@ jobs:
create-audit-issue:
name: Create quarterly security audit issue
runs-on: ubuntu-latest
container: catthehacker/ubuntu:act-22.04
steps:
- uses: actions/checkout@v4

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@@ -12,7 +12,6 @@ jobs:
scan:
name: Scan for secrets
runs-on: ubuntu-latest
container: catthehacker/ubuntu:act-22.04
steps:
- uses: actions/checkout@v4
with:

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@@ -12,7 +12,6 @@ jobs:
scan:
name: Scan PR for supply chain risks
runs-on: ubuntu-latest
container: catthehacker/ubuntu:act-22.04
steps:
- name: Checkout
uses: actions/checkout@v4

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@@ -14,7 +14,6 @@ concurrency:
jobs:
test:
runs-on: ubuntu-latest
container: catthehacker/ubuntu:act-22.04
timeout-minutes: 10
steps:
- name: Checkout code

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@@ -1,113 +0,0 @@
# Mempalace Technique Evaluation Report
**Date:** 2026-04-07
**Author:** Allegro
**Refs:** hermes-agent Issue #190
---
## Executive Summary
A controlled benchmark evaluated the effectiveness of applying memory palace (mempalace) spatial-organisation techniques to repetitive Gitea issue-analysis workflows. A 19% reduction in elapsed time was observed with no degradation in analytical accuracy. Assignee coverage (76.6%) remains below the 80% operational target and is flagged for follow-up.
---
## Methodology
Two consecutive passes of the same analytical workflow were performed over an identical dataset:
| Pass | Technique | Description |
|------|-----------|-------------|
| Baseline | None | Standard linear scan of repos and issues |
| Experimental | Mempalace | Four-room palace layout applied (see §3) |
**Dataset:**
- Repositories sampled: 5 (`the-nexus`, `timmy-config`, `timmy-home`, `the-door`, `turboquant`)
- Total repos in organisation: 11
- API endpoint: `https://forge.alexanderwhitestone.com/api/v1`
- Evaluation timestamp: 2026-04-07 03:09:12 UTC
---
## Results
### Quantitative Metrics
| Metric | Baseline | Mempalace | Delta |
|--------|----------|-----------|-------|
| Time elapsed | 1.02 s | 0.83 s | **19.0%** |
| Repos sampled | 5 | 5 | 0% |
| Total open issues | 94 | 94 | 0% |
| Repos with issues | 4 | 4 | 0% |
| Issues with assignee | 72 | 72 | 0% |
| Issues without assignee | 22 | 22 | 0% |
| Avg issues per repo | 18.8 | 18.8 | 0% |
| Assignee coverage rate | 76.6% | 76.6% | 0% |
### Key Findings
- **Time efficiency improved by 19.0%** — consistent with the hypothesis that spatially-organised traversal reduces context-switching overhead within the analytical loop.
- **Issue detection accuracy unchanged (+0.0%)** — the technique does not distort observations; it only changes the order and framing of data ingestion.
- **Assignee coverage (76.6%) is below the 80% target** — this is a data/process finding, not a technique artefact.
---
## Mempalace Layout (Four-Room Model)
The palace layout used in this evaluation:
```
┌─────────────────────────────────────────────────────────────────┐
│ 🏛️ MEMPALACE — Issue Analysis Domain │
├──────────────────────┬──────────────────────────────────────────┤
│ Room 1 │ Room 2 │
│ Repository │ Issue Assignment │
│ Architecture │ Status │
│ ────────────────── │ ────────────────────────────────────────│
│ · Repo structure │ · Assigned vs unassigned counts │
│ · Inter-repo links │ · Coverage rate vs target │
│ · Issue density │ · Per-repo assignment gaps │
├──────────────────────┼──────────────────────────────────────────┤
│ Room 3 │ Room 4 │
│ Triage Priority │ Resolution Patterns │
│ ────────────────── │ ────────────────────────────────────────│
│ · Priority levels │ · Historical velocity │
│ · Urgency signals │ · Common fix categories │
│ · Staleness flags │ · Recurring blockers │
└──────────────────────┴──────────────────────────────────────────┘
```
Each room is entered in a fixed order. Entering a room activates a consistent set of retrieval cues — removing the need to re-derive analytical framing on each pass.
---
## Implementation
A reference implementation is available at `skills/memory/mempalace.py`. It provides:
- `Mempalace` class with typed `PalaceRoom` containers
- `Mempalace.for_issue_analysis()` — pre-wired four-room palace matching this evaluation
- `Mempalace.for_health_check()` — CI / deployment monitoring variant
- `Mempalace.for_code_review()` — PR triage variant
- `analyse_issues(repos_data, target_assignee_rate)` — skill entry-point for automated issue analysis
---
## Recommendations
1. **Continue mempalace technique for issue-analysis workflows.** The 19% improvement is reproducible and imposes no accuracy cost.
2. **Extend to health-check and code-review workflows.** Factory constructors are already provided in the reference implementation.
3. **Develop domain-specific palace layouts** for each recurring task type. Consistent room names accelerate future evaluations by enabling direct A/B comparison.
4. **Measure longitudinal effects.** A single session comparison is encouraging; multi-session data will confirm whether gains compound or plateau.
5. **Address assignee coverage gap separately.** The 76.6% coverage rate is a backlog-health issue independent of the mempalace technique. Target: ≥ 80%.
---
## Action Items
| Item | Owner | Priority |
|------|-------|----------|
| Deploy mempalace skill to fleet | Claude | P1 |
| Extend to health-check workflow | Ezra | P2 |
| Extend to code-review workflow | Ezra | P2 |
| Triage 22 unassigned issues | Allegro | P1 |
| Re-run evaluation after 30 days | Allegro | P2 |

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@@ -98,23 +98,9 @@ class HealthReport:
self.passed = False
EXCLUDED_PATH_SEGMENTS = frozenset({
".cache", "__pycache__", ".venv", "venv", "site-packages",
".local/share/uv", "node_modules", ".git", ".tox",
})
def _is_excluded_path(path: Path) -> bool:
"""Skip cache, venv, and package-manager directories."""
parts = set(path.parts)
return not parts.isdisjoint(EXCLUDED_PATH_SEGMENTS)
def scan_orphaned_bytecode(root: Path, report: HealthReport) -> None:
"""Detect .pyc files without corresponding .py source files."""
for pyc in root.rglob("*.pyc"):
if _is_excluded_path(pyc):
continue
py = pyc.with_suffix(".py")
if not py.exists():
# Also check __pycache__ naming convention
@@ -156,12 +142,6 @@ def _is_sensitive_filename(name: str) -> bool:
lower = name.lower()
if lower == ".env.example":
return False
# Skip stylesheet and documentation artifacts
if lower.endswith(".css"):
return False
# Skip scanner tooling — these are detectors, not secrets
if lower in {"secret_scan.py", "secret_scanner.py"}:
return False
if any(pat in lower for pat in SENSITIVE_FILE_PATTERNS):
return True
if any(lower.startswith(pref) for pref in SENSITIVE_NAME_PREFIXES):
@@ -176,8 +156,6 @@ def scan_sensitive_file_permissions(root: Path, report: HealthReport, fix: bool
for fpath in root.rglob("*"):
if not fpath.is_file():
continue
if _is_excluded_path(fpath):
continue
# Skip test files — real secrets should never live in tests/
if "/tests/" in str(fpath) or str(fpath).startswith(str(root / "tests")):
continue

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@@ -1,100 +0,0 @@
---
name: gitea-workflow-automation
title: Gitea Workflow Automation
description: Automate Gitea issues, PRs, and repository workflows via the API for forge CI and backlog tracking.
trigger: When creating Gitea issues, pull requests, or automating forge repository workflows.
---
# Gitea Workflow Automation
## Trigger
Use this skill when automating Gitea operations: creating issues, opening PRs, checking repository state, or integrating Gitea into CI/backlog workflows.
## Prerequisites
- `GITEA_URL` environment variable set (e.g., `https://forge.alexanderwhitestone.com`)
- `GITEA_TOKEN` environment variable with a valid API token
- `GITEA_USER` or explicit owner/org name
- `curl` and `jq` available in the environment
## Step-by-Step Workflow
### 1. Verify Environment
```bash
: "${GITEA_URL?}" "${GITEA_TOKEN?}" "${GITEA_USER?}"
echo "Gitea env OK"
```
### 2. List Issues in a Repository
```bash
curl -s -H "Authorization: token ${GITEA_TOKEN}" \
"${GITEA_URL}/api/v1/repos/${OWNER}/${REPO}/issues?state=open&limit=50" | jq '.[] | {number, title, state}'
```
### 3. Create an Issue
```bash
curl -s -X POST -H "Authorization: token ${GITEA_TOKEN}" \
-H "Content-Type: application/json" \
"${GITEA_URL}/api/v1/repos/${OWNER}/${REPO}/issues" \
-d "{\"title\":\"${TITLE}\",\"body\":\"${BODY}\",\"assignees\":[\"${ASSIGNEE}\"]}
```
- Escape newlines in `BODY` if passing inline; prefer a JSON file for multi-line bodies.
### 4. Create a Pull Request
```bash
curl -s -X POST -H "Authorization: token ${GITEA_TOKEN}" \
-H "Content-Type: application/json" \
"${GITEA_URL}/api/v1/repos/${OWNER}/${REPO}/pulls" \
-d "{\"title\":\"${TITLE}\",\"body\":\"${BODY}\",\"head\":\"${BRANCH}\",\"base\":\"${BASE_BRANCH}\"}"
```
### 5. Check PR Status / Diff
```bash
curl -s -H "Authorization: token ${GITEA_TOKEN}" \
"${GITEA_URL}/api/v1/repos/${OWNER}/${REPO}/pulls/${PR_NUMBER}" | jq '{number, title, state, mergeable}'
```
### 6. Push Code Before Opening PR
```bash
git checkout -b "${BRANCH}"
git add .
git commit -m "${COMMIT_MSG}"
git push origin "${BRANCH}"
```
### 7. Add Comments to Issues/PRs
```bash
curl -s -X POST -H "Authorization: token ${GITEA_TOKEN}" \
-H "Content-Type: application/json" \
"${GITEA_URL}/api/v1/repos/${OWNER}/${REPO}/issues/${NUMBER}/comments" \
-d "{\"body\":\"${COMMENT_BODY}\"}"
```
## Verification Checklist
- [ ] Environment variables are exported and non-empty
- [ ] API responses are parsed with `jq` to confirm success
- [ ] Issue/PR numbers are captured from the JSON response for cross-linking
- [ ] Branch exists on remote before creating a PR
- [ ] Multi-line bodies are written to a temp JSON file to avoid escaping hell
## Pitfalls
- **Trailing slashes in `GITEA_URL`:** Ensure `GITEA_URL` does not end with `/` or double slashes break URLs.
- **Branch not pushed:** Creating a PR for a local-only branch returns 422.
- **Escape hell:** For multi-line issue/PR bodies, write JSON to a file with `cat <<EOF > /tmp/payload.json` and pass `@/tmp/payload.json` to curl instead of inline strings.
- **Token scope:** If operations fail with 403, verify the token has `repo` or `write:issue` scope.
- **Pagination:** Default limit is 30 issues; use `?limit=100` or paginate with `page=` for large backlogs.
## Example: Full Issue Creation with File Body
```bash
cat <<'EOF' > /tmp/issue.json
{
"title": "[Bezalel] Forge Health Check",
"body": "Build a diagnostic scanner for artifact integrity and permissions.\n\n- Detect .pyc without .py source\n- Detect world-readable sensitive files\n- Output JSON for CI consumption",
"assignees": ["bezalel"],
"labels": ["enhancement", "security"]
}
EOF
curl -s -X POST -H "Authorization: token ${GITEA_TOKEN}" \
-H "Content-Type: application/json" \
"${GITEA_URL}/api/v1/repos/Timmy_Foundation/hermes-agent/issues" \
-d @/tmp/issue.json | jq '.number'
```

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@@ -1,225 +0,0 @@
"""
---
title: Mempalace — Analytical Workflow Memory Framework
description: Applies spatial memory palace organization to analytical tasks (issue triage, repo audits, backlog analysis) for faster, more consistent results.
conditions:
- Analytical workflows over structured data (issues, PRs, repos)
- Repetitive triage or audit tasks where pattern recall improves speed
- Multi-repository scanning requiring consistent mental models
---
"""
from __future__ import annotations
import json
import time
from dataclasses import dataclass, field
from typing import Any
@dataclass
class PalaceRoom:
"""A single 'room' in the memory palace — holds organized facts about one analytical dimension."""
name: str
label: str
contents: dict[str, Any] = field(default_factory=dict)
entered_at: float = field(default_factory=time.time)
def store(self, key: str, value: Any) -> None:
self.contents[key] = value
def retrieve(self, key: str, default: Any = None) -> Any:
return self.contents.get(key, default)
def summary(self) -> str:
lines = [f"## {self.label}"]
for k, v in self.contents.items():
lines.append(f" {k}: {v}")
return "\n".join(lines)
class Mempalace:
"""
Spatial memory palace for analytical workflows.
Organises multi-dimensional data about a domain (e.g. Gitea issues) into
named rooms. Each room models one analytical dimension, making it easy to
traverse observations in a consistent order — the same pattern that produced
a 19% throughput improvement in Allegro's April 2026 evaluation.
Standard rooms for issue-analysis workflows
-------------------------------------------
repo_architecture Repository structure and inter-repo relationships
assignment_status Assigned vs unassigned issue distribution
triage_priority Priority / urgency levels (the "lighting system")
resolution_patterns Historical resolution trends and velocity
Usage
-----
>>> palace = Mempalace.for_issue_analysis()
>>> palace.enter("repo_architecture")
>>> palace.store("total_repos", 11)
>>> palace.store("repos_with_issues", 4)
>>> palace.enter("assignment_status")
>>> palace.store("assigned", 72)
>>> palace.store("unassigned", 22)
>>> print(palace.render())
"""
def __init__(self, domain: str = "general") -> None:
self.domain = domain
self._rooms: dict[str, PalaceRoom] = {}
self._current_room: str | None = None
self._created_at: float = time.time()
# ------------------------------------------------------------------
# Factory constructors for common analytical domains
# ------------------------------------------------------------------
@classmethod
def for_issue_analysis(cls) -> "Mempalace":
"""Pre-wired palace for Gitea / forge issue-analysis workflows."""
p = cls(domain="issue_analysis")
p.add_room("repo_architecture", "Repository Architecture Room")
p.add_room("assignment_status", "Issue Assignment Status Room")
p.add_room("triage_priority", "Triage Priority Room")
p.add_room("resolution_patterns", "Resolution Patterns Room")
return p
@classmethod
def for_health_check(cls) -> "Mempalace":
"""Pre-wired palace for CI / deployment health-check workflows."""
p = cls(domain="health_check")
p.add_room("service_topology", "Service Topology Room")
p.add_room("failure_signals", "Failure Signals Room")
p.add_room("recovery_history", "Recovery History Room")
return p
@classmethod
def for_code_review(cls) -> "Mempalace":
"""Pre-wired palace for code-review / PR triage workflows."""
p = cls(domain="code_review")
p.add_room("change_scope", "Change Scope Room")
p.add_room("risk_surface", "Risk Surface Room")
p.add_room("test_coverage", "Test Coverage Room")
p.add_room("reviewer_context", "Reviewer Context Room")
return p
# ------------------------------------------------------------------
# Room management
# ------------------------------------------------------------------
def add_room(self, key: str, label: str) -> PalaceRoom:
room = PalaceRoom(name=key, label=label)
self._rooms[key] = room
return room
def enter(self, room_key: str) -> PalaceRoom:
if room_key not in self._rooms:
raise KeyError(f"No room '{room_key}' in palace. Available: {list(self._rooms)}")
self._current_room = room_key
return self._rooms[room_key]
def store(self, key: str, value: Any) -> None:
"""Store a value in the currently active room."""
if self._current_room is None:
raise RuntimeError("Enter a room before storing values.")
self._rooms[self._current_room].store(key, value)
def retrieve(self, room_key: str, key: str, default: Any = None) -> Any:
if room_key not in self._rooms:
return default
return self._rooms[room_key].retrieve(key, default)
# ------------------------------------------------------------------
# Rendering
# ------------------------------------------------------------------
def render(self) -> str:
"""Return a human-readable summary of the entire palace."""
elapsed = time.time() - self._created_at
lines = [
f"# Mempalace — {self.domain}",
f"_traversal time: {elapsed:.2f}s | rooms: {len(self._rooms)}_",
"",
]
for room in self._rooms.values():
lines.append(room.summary())
lines.append("")
return "\n".join(lines)
def to_dict(self) -> dict:
return {
"domain": self.domain,
"elapsed_seconds": round(time.time() - self._created_at, 3),
"rooms": {k: v.contents for k, v in self._rooms.items()},
}
def to_json(self) -> str:
return json.dumps(self.to_dict(), indent=2)
# ---------------------------------------------------------------------------
# Skill entry-point
# ---------------------------------------------------------------------------
def analyse_issues(
repos_data: list[dict],
target_assignee_rate: float = 0.80,
) -> str:
"""
Applies the mempalace technique to a list of repo issue summaries.
Parameters
----------
repos_data:
List of dicts, each with keys: ``repo``, ``open_issues``,
``assigned``, ``unassigned``.
target_assignee_rate:
Minimum acceptable assignee-coverage ratio (default 0.80).
Returns
-------
str
Rendered palace summary with coverage assessment.
"""
palace = Mempalace.for_issue_analysis()
# --- Repository Architecture Room ---
palace.enter("repo_architecture")
total_issues = sum(r.get("open_issues", 0) for r in repos_data)
repos_with_issues = sum(1 for r in repos_data if r.get("open_issues", 0) > 0)
palace.store("repos_sampled", len(repos_data))
palace.store("repos_with_issues", repos_with_issues)
palace.store("total_open_issues", total_issues)
palace.store(
"avg_issues_per_repo",
round(total_issues / len(repos_data), 1) if repos_data else 0,
)
# --- Assignment Status Room ---
palace.enter("assignment_status")
total_assigned = sum(r.get("assigned", 0) for r in repos_data)
total_unassigned = sum(r.get("unassigned", 0) for r in repos_data)
coverage = total_assigned / total_issues if total_issues else 0
palace.store("assigned", total_assigned)
palace.store("unassigned", total_unassigned)
palace.store("coverage_rate", round(coverage, 3))
palace.store(
"coverage_status",
"OK" if coverage >= target_assignee_rate else f"BELOW TARGET ({target_assignee_rate:.0%})",
)
# --- Triage Priority Room ---
palace.enter("triage_priority")
unassigned_repos = [r["repo"] for r in repos_data if r.get("unassigned", 0) > 0]
palace.store("repos_needing_triage", unassigned_repos)
palace.store("triage_count", total_unassigned)
# --- Resolution Patterns Room ---
palace.enter("resolution_patterns")
palace.store("technique", "mempalace")
palace.store("target_assignee_rate", target_assignee_rate)
return palace.render()

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@@ -279,7 +279,7 @@ class TestSkillViewFilePathSecurity:
"""Tests for file_path parameter security in skill_view."""
@pytest.fixture
def setup_skill_with_files(self, tmp_path):
def setup_skill_with_files(self, tmp_path):
"""Create a skill with supporting files."""
skills_dir = tmp_path / "skills"
skills_dir.mkdir()