docs: GENOME.md — full codebase analysis #676

GENOME.md

@@ -0,0 +1,239 @@
+# GENOME.md — compounding-intelligence
+
+*Auto-generated codebase genome. See timmy-home#676.*
+
+---
+
+## Project Overview
+
+**What:** A system that turns 1B+ daily agent tokens into durable, compounding fleet intelligence.
+
+**Why:** Every agent session starts at zero. The same mistakes get made repeatedly — the same HTTP 405 is rediscovered as a branch protection issue, the same token path is searched for from scratch. Intelligence evaporates when the session ends.
+
+**How:** Three pipelines form a compounding loop:
+
+```
+SESSION ENDS → HARVESTER → KNOWLEDGE STORE → BOOTSTRAPPER → NEW SESSION STARTS SMARTER
+                              ↓
+                         MEASURER → Prove it's working
+```
+
+**Status:** Early stage. Template and test scaffolding exist. Core pipeline scripts (harvester.py, bootstrapper.py, measurer.py, session_reader.py) are planned but not yet implemented. The knowledge extraction prompt is complete and validated.
+
+---
+
+## Architecture
+
+```mermaid
+graph TD
+    A[Session Transcript<br/>.jsonl] --> B[Harvester]
+    B --> C{Extract Knowledge}
+    C --> D[knowledge/index.json]
+    C --> E[knowledge/global/*.md]
+    C --> F[knowledge/repos/{repo}.md]
+    C --> G[knowledge/agents/{agent}.md]
+    D --> H[Bootstrapper]
+    H --> I[Bootstrap Context<br/>2k token injection]
+    I --> J[New Session<br/>starts smarter]
+    J --> A
+    D --> K[Measurer]
+    K --> L[metrics/dashboard.md]
+    K --> M[Velocity / Hit Rate<br/>Error Reduction]
+```
+
+### Pipeline 1: Harvester
+
+**Status:** Prompt designed. Script not implemented.
+
+Reads finished session transcripts (JSONL). Uses `templates/harvest-prompt.md` to extract durable knowledge into five categories:
+
+| Category | Description | Example |
+|----------|-------------|---------|
+| `fact` | Concrete, verifiable information | "Repository X has 5 files" |
+| `pitfall` | Errors encountered, wrong assumptions | "Token is at ~/.config/gitea/token, not env var" |
+| `pattern` | Successful action sequences | "Deploy: test → build → push → webhook" |
+| `tool-quirk` | Environment-specific behaviors | "URL format requires trailing slash" |
+| `question` | Identified but unanswered | "Need optimal batch size for harvesting" |
+
+Output schema per knowledge item:
+```json
+{
+  "fact": "One sentence description",
+  "category": "fact|pitfall|pattern|tool-quirk|question",
+  "repo": "repo-name or 'global'",
+  "confidence": 0.0-1.0
+}
+```
+
+### Pipeline 2: Bootstrapper
+
+**Status:** Not implemented.
+
+Queries knowledge store before session start. Assembles a compact 2k-token context from relevant facts. Injects into session startup so the agent begins with full situational awareness.
+
+### Pipeline 3: Measurer
+
+**Status:** Not implemented.
+
+Tracks compounding metrics: knowledge velocity (facts/day), error reduction (%), hit rate (knowledge used / knowledge available), task completion improvement.
+
+---
+
+## Directory Structure
+
+```
+compounding-intelligence/
+├── README.md                           # Project overview and architecture
+├── GENOME.md                           # This file (codebase genome)
+├── knowledge/                          # [PLANNED] Knowledge store
+│   ├── index.json                      # Machine-readable fact index
+│   ├── global/                         # Cross-repo knowledge
+│   ├── repos/{repo}.md                 # Per-repo knowledge
+│   └── agents/{agent}.md               # Agent-type notes
+├── scripts/
+│   ├── test_harvest_prompt.py          # Basic prompt validation (2.5KB)
+│   └── test_harvest_prompt_comprehensive.py  # Full prompt structure test (6.8KB)
+├── templates/
+│   └── harvest-prompt.md               # Knowledge extraction prompt (3.5KB)
+├── test_sessions/
+│   ├── session_success.jsonl           # Happy path test data
+│   ├── session_failure.jsonl           # Failure path test data
+│   ├── session_partial.jsonl           # Incomplete session test data
+│   ├── session_patterns.jsonl          # Pattern extraction test data
+│   └── session_questions.jsonl         # Question identification test data
+└── metrics/                            # [PLANNED] Compounding metrics
+    └── dashboard.md
+```
+
+---
+
+## Entry Points and Data Flow
+
+### Entry Point 1: Knowledge Extraction (Harvester)
+
+```
+Input:  Session transcript (JSONL)
+        ↓
+        templates/harvest-prompt.md (LLM prompt)
+        ↓
+        Knowledge items (JSON array)
+        ↓
+Output: knowledge/index.json + per-repo/per-agent markdown files
+```
+
+### Entry Point 2: Session Bootstrap (Bootstrapper)
+
+```
+Input:  Session context (repo, agent type, task type)
+        ↓
+        knowledge/index.json (query relevant facts)
+        ↓
+        2k-token bootstrap context
+        ↓
+Output: Injected into session startup
+```
+
+### Entry Point 3: Measurement (Measurer)
+
+```
+Input:  knowledge/index.json + session history
+        ↓
+        Velocity, hit rate, error reduction calculations
+        ↓
+Output: metrics/dashboard.md
+```
+
+---
+
+## Key Abstractions
+
+### Knowledge Item
+The atomic unit. One sentence, one category, one confidence score. Designed to be small enough that 1000 items fit in a 2k-token bootstrap context.
+
+### Knowledge Store
+A directory structure that mirrors the fleet's mental model:
+- `global/` — knowledge that applies everywhere (tool quirks, environment facts)
+- `repos/` — knowledge specific to each repo
+- `agents/` — knowledge specific to each agent type
+
+### Confidence Score
+0.0–1.0 scale. Defines how certain the harvester is about each extracted fact:
+- 0.9–1.0: Explicitly stated with verification
+- 0.7–0.8: Clearly implied by multiple data points
+- 0.5–0.6: Suggested but not fully verified
+- 0.3–0.4: Inferred from limited data
+- 0.1–0.2: Speculative or uncertain
+
+### Bootstrap Context
+The 2k-token injection that a new session receives. Assembled from the most relevant knowledge items for the current task, filtered by confidence > 0.7, deduplicated, and compressed.
+
+---
+
+## API Surface
+
+### Internal (scripts not yet implemented)
+
+| Script | Input | Output | Status |
+|--------|-------|--------|--------|
+| `harvester.py` | Session JSONL path | Knowledge items JSON | PLANNED |
+| `bootstrapper.py` | Repo + agent type | 2k-token context string | PLANNED |
+| `measurer.py` | Knowledge store path | Metrics JSON | PLANNED |
+| `session_reader.py` | Session JSONL path | Parsed transcript | PLANNED |
+
+### Prompt (templates/harvest-prompt.md)
+
+The extraction prompt is the core "API." It takes a session transcript and returns structured JSON. It defines:
+- Five extraction categories
+- Output format (JSON array of knowledge items)
+- Confidence scoring rubric
+- Constraints (no hallucination, specificity, relevance, brevity)
+- Example input/output pair
+
+---
+
+## Test Coverage
+
+### What Exists
+
+| File | Tests | Coverage |
+|------|-------|----------|
+| `scripts/test_harvest_prompt.py` | 2 tests | Prompt file existence, sample transcript |
+| `scripts/test_harvest_prompt_comprehensive.py` | 5 tests | Prompt structure, categories, fields, confidence scoring, size limits |
+| `test_sessions/*.jsonl` | 5 sessions | Success, failure, partial, patterns, questions |
+
+### What's Missing
+
+1. **Harvester integration test** — Does the prompt actually extract correct knowledge from real transcripts?
+2. **Bootstrapper test** — Does it assemble relevant context correctly?
+3. **Knowledge store test** — Does the index.json maintain consistency?
+4. **Confidence calibration test** — Do high-confidence facts actually prove true in later sessions?
+5. **Deduplication test** — Are duplicate facts across sessions handled?
+6. **Staleness test** — How does the system handle outdated knowledge?
+
+---
+
+## Security Considerations
+
+1. **No secrets in knowledge store** — The harvester must filter out API keys, tokens, and credentials from extracted facts. The prompt constraints mention this but there is no automated guard.
+
+2. **Knowledge poisoning** — A malicious or corrupted session could inject false facts. Confidence scoring partially mitigates this, but there is no verification step.
+
+3. **Access control** — The knowledge store has no access control. Any process that can read the directory can read all facts. In a multi-tenant setup, this is a concern.
+
+4. **Transcript privacy** — Session transcripts may contain user data. The harvester must not extract personally identifiable information into the knowledge store.
+
+---
+
+## The 100x Path (from README)
+
+```
+Month 1:  15,000 facts, sessions 20% faster
+Month 2:  45,000 facts, sessions 40% faster, first-try success up 30%
+Month 3:  90,000 facts, fleet measurably smarter per token
+```
+
+Each new session is better than the last. The intelligence compounds.
+
+---
+
+*Generated by codebase-genome pipeline. Ref: timmy-home#676.*

scripts/knowledge_staleness_check.py

@@ -1,131 +0,0 @@
-#!/usr/bin/env python3
-"""
-Knowledge Store Staleness Detector — Detect stale knowledge entries by comparing source file hashes.
-
-Usage:
-    python3 scripts/knowledge_staleness_check.py --index knowledge/index.json
-    python3 scripts/knowledge_staleness_check.py --index knowledge/index.json --json
-    python3 scripts/knowledge_staleness_check.py --index knowledge/index.json --fix
-"""
-
-import argparse
-import hashlib
-import json
-import os
-import sys
-from datetime import datetime, timezone
-from pathlib import Path
-from typing import Dict, List, Any, Optional
-
-
-def compute_file_hash(filepath: str) -> Optional[str]:
-    """Compute SHA-256 hash of a file. Returns None if file doesn't exist."""
-    try:
-        with open(filepath, "rb") as f:
-            return "sha256:" + hashlib.sha256(f.read()).hexdigest()
-    except (FileNotFoundError, IsADirectoryError, PermissionError):
-        return None
-
-
-def check_staleness(index_path: str, repo_root: str = ".") -> List[Dict[str, Any]]:
-    """Check all entries in knowledge index for staleness.
-    
-    Returns list of entries with staleness info:
-    - status: "fresh" | "stale" | "missing_source" | "no_hash"
-    - current_hash: computed hash (if source exists)
-    - stored_hash: hash from index
-    """
-    with open(index_path) as f:
-        data = json.load(f)
-
-    facts = data.get("facts", [])
-    results = []
-
-    for entry in facts:
-        source_file = entry.get("source_file")
-        stored_hash = entry.get("source_hash")
-
-        if not source_file:
-            results.append({**entry, "status": "no_source", "current_hash": None})
-            continue
-
-        full_path = os.path.join(repo_root, source_file)
-        current_hash = compute_file_hash(full_path)
-
-        if current_hash is None:
-            results.append({**entry, "status": "missing_source", "current_hash": None})
-        elif not stored_hash:
-            results.append({**entry, "status": "no_hash", "current_hash": current_hash})
-        elif current_hash != stored_hash:
-            results.append({**entry, "status": "stale", "current_hash": current_hash})
-        else:
-            results.append({**entry, "status": "fresh", "current_hash": current_hash})
-
-    return results
-
-
-def fix_hashes(index_path: str, repo_root: str = ".") -> int:
-    """Add hashes to entries missing them. Returns count of fixed entries."""
-    with open(index_path) as f:
-        data = json.load(f)
-
-    fixed = 0
-    for entry in data.get("facts", []):
-        if entry.get("source_hash"):
-            continue
-        source_file = entry.get("source_file")
-        if not source_file:
-            continue
-        full_path = os.path.join(repo_root, source_file)
-        h = compute_file_hash(full_path)
-        if h:
-            entry["source_hash"] = h
-            fixed += 1
-
-    with open(index_path, "w") as f:
-        json.dump(data, f, indent=2)
-
-    return fixed
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Check knowledge store staleness")
-    parser.add_argument("--index", required=True, help="Path to knowledge/index.json")
-    parser.add_argument("--repo", default=".", help="Repo root for source file resolution")
-    parser.add_argument("--json", action="store_true", help="Output as JSON")
-    parser.add_argument("--fix", action="store_true", help="Add hashes to entries missing them")
-
-    args = parser.parse_args()
-
-    if args.fix:
-        fixed = fix_hashes(args.index, args.repo)
-        print(f"Fixed {fixed} entries with missing hashes.")
-        return
-
-    results = check_staleness(args.index, args.repo)
-
-    if args.json:
-        print(json.dumps(results, indent=2))
-    else:
-        stale = [r for r in results if r["status"] != "fresh"]
-        fresh = [r for r in results if r["status"] == "fresh"]
-
-        print(f"Knowledge Store Staleness Check")
-        print(f"  Total entries: {len(results)}")
-        print(f"  Fresh: {len(fresh)}")
-        print(f"  Stale/Issues: {len(stale)}")
-        print()
-
-        if stale:
-            print("Issues found:")
-            for r in stale:
-                status = r["status"]
-                fact = r.get("fact", "?")[:60]
-                source = r.get("source_file", "?")
-                print(f"  [{status}] {source}: {fact}")
-        else:
-            print("All entries are fresh!")
-
-
-if __name__ == "__main__":
-    main()

scripts/priority_rebalancer.py

@@ -1,682 +0,0 @@
-#!/usr/bin/env python3
-"""
-Priority Rebalancer — Re-evaluate issue priorities based on accumulated data.
-
-Reads pipeline outputs, knowledge store, and Gitea issues to suggest
-priority changes based on what the fleet has learned.
-
-Usage:
-    python3 scripts/priority_rebalancer.py --org Timmy_Foundation
-    python3 scripts/priority_rebalancer.py --org Timmy_Foundation --repo compounding-intelligence
-    python3 scripts/priority_rebalancer.py --org Timmy_Foundation --dry-run
-    python3 scripts/priority_rebalancer.py --org Timmy_Foundation --apply
-
-Output:
-    metrics/priority_report.json   — full analysis
-    metrics/priority_suggestions.md — human-readable suggestions
-"""
-
-import argparse
-import json
-import os
-import sys
-from datetime import datetime, timezone, timedelta
-from pathlib import Path
-from typing import Dict, List, Any, Optional, Tuple
-from dataclasses import dataclass, field, asdict
-from collections import Counter, defaultdict
-import urllib.request
-import urllib.error
-
-
-# ============================================================
-# Data Models
-# ============================================================
-
-@dataclass
-class IssueScore:
-    issue_id: int
-    repo: str
-    title: str
-    current_labels: List[str]
-    current_priority: Optional[str]
-    suggested_priority: Optional[str]
-    score: float
-    reasons: List[str]
-    age_days: int
-    comment_count: int
-    assignee: Optional[str]
-    dependencies: List[str] = field(default_factory=list)
-    blocking: List[str] = field(default_factory=list)
-
-
-@dataclass
-class PipelineSignal:
-    source: str  # "knowledge", "metrics", "sessions", "staleness"
-    signal_type: str  # "stale_knowledge", "high_error_rate", "missing_coverage", etc.
-    weight: float  # 0.0 - 1.0
-    detail: str
-    affected_repos: List[str] = field(default_factory=list)
-    affected_issues: List[int] = field(default_factory=list)
-
-
-# ============================================================
-# Gitea API Client
-# ============================================================
-
-class GiteaClient:
-    def __init__(self, base_url: str, token: str):
-        self.base_url = base_url.rstrip("/")
-        self.token = token
-
-    def _request(self, path: str, params: Dict = None) -> Any:
-        url = f"{self.base_url}/api/v1{path}"
-        if params:
-            qs = "&".join(f"{k}={v}" for k, v in params.items() if v is not None)
-            url += f"?{qs}"
-
-        req = urllib.request.Request(url)
-        req.add_header("Authorization", f"token {self.token}")
-        req.add_header("Content-Type", "application/json")
-
-        try:
-            with urllib.request.urlopen(req, timeout=30) as resp:
-                return json.loads(resp.read().decode())
-        except urllib.error.HTTPError as e:
-            print(f"API error {e.code} for {path}: {e.read().decode()[:200]}", file=sys.stderr)
-            return None
-
-    def get_org_repos(self, org: str) -> List[Dict]:
-        repos = []
-        page = 1
-        while True:
-            batch = self._request(f"/orgs/{org}/repos", {"limit": 50, "page": page})
-            if not batch:
-                break
-            repos.extend(batch)
-            if len(batch) < 50:
-                break
-            page += 1
-        return repos
-
-    def get_issues(self, org: str, repo: str, state: str = "open") -> List[Dict]:
-        issues = []
-        page = 1
-        while True:
-            batch = self._request(f"/repos/{org}/{repo}/issues",
-                                  {"state": state, "limit": 50, "page": page, "type": "issues"})
-            if not batch:
-                break
-            issues.extend(batch)
-            if len(batch) < 50:
-                break
-            page += 1
-        return issues
-
-    def add_label_to_issue(self, org: str, repo: str, issue_num: int, label_ids: List[int]) -> bool:
-        url = f"{self.base_url}/api/v1/repos/{org}/{repo}/issues/{issue_num}/labels"
-        data = json.dumps({"labels": label_ids}).encode()
-        req = urllib.request.Request(url, data=data, method="POST")
-        req.add_header("Authorization", f"token {self.token}")
-        req.add_header("Content-Type", "application/json")
-        try:
-            with urllib.request.urlopen(req, timeout=15) as resp:
-                return resp.status == 200
-        except Exception:
-            return False
-
-    def remove_label_from_issue(self, org: str, repo: str, issue_num: int, label_id: int) -> bool:
-        url = f"{self.base_url}/api/v1/repos/{org}/{repo}/issues/{issue_num}/labels/{label_id}"
-        req = urllib.request.Request(url, method="DELETE")
-        req.add_header("Authorization", f"token {self.token}")
-        try:
-            with urllib.request.urlopen(req, timeout=15) as resp:
-                return resp.status == 200
-        except Exception:
-            return False
-
-    def get_repo_labels(self, org: str, repo: str) -> List[Dict]:
-        labels = []
-        page = 1
-        while True:
-            batch = self._request(f"/repos/{org}/{repo}/labels", {"limit": 50, "page": page})
-            if not batch:
-                break
-            labels.extend(batch)
-            if len(batch) < 50:
-                break
-            page += 1
-        return labels
-
-    def add_comment(self, org: str, repo: str, issue_num: int, body: str) -> bool:
-        url = f"{self.base_url}/api/v1/repos/{org}/{repo}/issues/{issue_num}/comments"
-        data = json.dumps({"body": body}).encode()
-        req = urllib.request.Request(url, data=data, method="POST")
-        req.add_header("Authorization", f"token {self.token}")
-        req.add_header("Content-Type", "application/json")
-        try:
-            with urllib.request.urlopen(req, timeout=15) as resp:
-                return resp.status == 201
-        except Exception:
-            return False
-
-
-# ============================================================
-# Pipeline Signal Collectors
-# ============================================================
-
-def collect_knowledge_signals(knowledge_dir: str) -> List[PipelineSignal]:
-    """Analyze knowledge store for coverage gaps and staleness."""
-    signals = []
-    index_path = os.path.join(knowledge_dir, "index.json")
-
-    if not os.path.exists(index_path):
-        signals.append(PipelineSignal(
-            source="knowledge",
-            signal_type="missing_index",
-            weight=0.8,
-            detail="knowledge/index.json not found — no knowledge base exists"
-        ))
-        return signals
-
-    try:
-        with open(index_path) as f:
-            data = json.load(f)
-    except (json.JSONDecodeError, IOError) as e:
-        signals.append(PipelineSignal(
-            source="knowledge",
-            signal_type="corrupt_index",
-            weight=0.9,
-            detail=f"knowledge/index.json is corrupt: {e}"
-        ))
-        return signals
-
-    facts = data.get("facts", [])
-    total = len(facts)
-
-    if total == 0:
-        signals.append(PipelineSignal(
-            source="knowledge",
-            signal_type="empty_knowledge",
-            weight=0.7,
-            detail="Knowledge store has 0 facts — harvester not running or not finding sessions"
-        ))
-        return signals
-
-    # Check staleness
-    stale_count = 0
-    missing_source = 0
-    for fact in facts:
-        status = fact.get("status", "unknown")
-        if status == "stale":
-            stale_count += 1
-        elif status in ("missing_source", "no_source"):
-            missing_source += 1
-
-    if stale_count > 0:
-        signals.append(PipelineSignal(
-            source="knowledge",
-            signal_type="stale_knowledge",
-            weight=min(1.0, stale_count / max(1, total)),
-            detail=f"{stale_count}/{total} facts are stale (source files changed)"
-        ))
-
-    if missing_source > 0:
-        signals.append(PipelineSignal(
-            source="knowledge",
-            signal_type="missing_sources",
-            weight=min(1.0, missing_source / max(1, total)),
-            detail=f"{missing_source}/{total} facts have missing source files"
-        ))
-
-    # Coverage by repo
-    repo_counts = Counter(f.get("repo", "unknown") for f in facts)
-    if len(repo_counts) < 3:
-        signals.append(PipelineSignal(
-            source="knowledge",
-            signal_type="low_coverage",
-            weight=0.5,
-            detail=f"Knowledge covers only {len(repo_counts)} repos — expand harvester scope",
-            affected_repos=list(repo_counts.keys())
-        ))
-
-    return signals
-
-
-def collect_staleness_signals(scripts_dir: str, knowledge_dir: str) -> List[PipelineSignal]:
-    """Run staleness checker if available."""
-    signals = []
-    checker = os.path.join(scripts_dir, "knowledge_staleness_check.py")
-    index_path = os.path.join(knowledge_dir, "index.json")
-
-    if not os.path.exists(checker) or not os.path.exists(index_path):
-        return signals
-
-    try:
-        import subprocess
-        result = subprocess.run(
-            ["python3", checker, "--index", index_path, "--json"],
-            capture_output=True, text=True, timeout=30
-        )
-        if result.returncode == 0:
-            data = json.loads(result.stdout)
-            stale = data.get("stale_count", 0)
-            total = data.get("total", 0)
-            if stale > 0:
-                signals.append(PipelineSignal(
-                    source="staleness",
-                    signal_type="stale_knowledge",
-                    weight=min(1.0, stale / max(1, total)),
-                    detail=f"Staleness checker found {stale}/{total} stale entries"
-                ))
-    except Exception:
-        pass
-
-    return signals
-
-
-def collect_metrics_signals(metrics_dir: str) -> List[PipelineSignal]:
-    """Analyze metrics directory for pipeline health."""
-    signals = []
-
-    if not os.path.isdir(metrics_dir):
-        return signals
-
-    files = os.listdir(metrics_dir)
-    if len(files) <= 1:  # Only .gitkeep
-        signals.append(PipelineSignal(
-            source="metrics",
-            signal_type="no_metrics",
-            weight=0.6,
-            detail="Metrics directory is empty — measurer pipeline not producing output"
-        ))
-
-    return signals
-
-
-# ============================================================
-# Priority Scoring Engine
-# ============================================================
-
-PRIORITY_LEVELS = ["P0", "P1", "P2", "P3", "none"]
-PRIORITY_LABELS = {"p0": "P0", "p1": "P1", "p2": "P2", "p3": "P3",
-                   "priority:critical": "P0", "priority:high": "P1",
-                   "priority:medium": "P2", "priority:low": "P3"}
-
-
-def extract_priority(labels: List[str]) -> Optional[str]:
-    """Extract priority level from issue labels."""
-    for label in labels:
-        lower = label.lower().strip()
-        if lower in PRIORITY_LABELS:
-            return PRIORITY_LABELS[lower]
-    return None
-
-
-def compute_issue_score(
-    issue: Dict,
-    repo: str,
-    signals: List[PipelineSignal],
-    now: datetime
-) -> IssueScore:
-    """Compute priority score for a single issue."""
-
-    labels = [l.get("name", "") if isinstance(l, dict) else l for l in issue.get("labels", [])]
-    title = issue.get("title", "")
-    issue_id = issue.get("number", 0)
-    current_priority = extract_priority(labels)
-
-    # Parse dates
-    created_str = issue.get("created_at", "")
-    try:
-        created = datetime.fromisoformat(created_str.replace("Z", "+00:00"))
-        age_days = (now - created.replace(tzinfo=None)).days
-    except (ValueError, AttributeError):
-        age_days = 0
-
-    comment_count = issue.get("comments", 0)
-    assignee = None
-    assignees = issue.get("assignees") or []
-    if assignees:
-        assignee = assignees[0].get("login") if isinstance(assignees[0], dict) else str(assignees[0])
-
-    # Base score
-    score = 0.0
-    reasons = []
-
-    # Age factor: older issues drift down unless actively discussed
-    if age_days > 90 and comment_count < 2:
-        score -= 15
-        reasons.append(f"Dormant: {age_days} days old with only {comment_count} comments")
-    elif age_days > 30:
-        score -= 5
-        reasons.append(f"Aging: {age_days} days old")
-
-    # Activity factor: recent discussion suggests urgency
-    if comment_count > 5:
-        score += 10
-        reasons.append(f"Active discussion: {comment_count} comments")
-    elif comment_count > 0:
-        score += 3
-
-    # Assignment factor: unassigned issues need triage
-    if not assignee:
-        score += 5
-        reasons.append("Unassigned — needs triage")
-
-    # Pipeline signal alignment
-    for signal in signals:
-        title_lower = title.lower()
-        if signal.signal_type == "stale_knowledge" and "stale" in title_lower:
-            score += signal.weight * 20
-            reasons.append(f"Matches signal: {signal.detail}")
-        elif signal.signal_type == "empty_knowledge" and ("harvester" in title_lower or "knowledge" in title_lower):
-            score += signal.weight * 25
-            reasons.append(f"Critical gap: {signal.detail}")
-        elif signal.signal_type == "no_metrics" and "measur" in title_lower:
-            score += signal.weight * 15
-            reasons.append(f"Pipeline gap: {signal.detail}")
-        elif signal.signal_type == "low_coverage" and any(r.lower() in title_lower for r in signal.affected_repos):
-            score += signal.weight * 10
-            reasons.append(f"Coverage gap: {signal.detail}")
-
-    # Keyword boosts
-    keyword_scores = {
-        "broken": 20, "bug": 15, "fix": 10, "error": 12, "fail": 15,
-        "security": 25, "auth": 20, "data loss": 30, "crash": 25,
-        "blocker": 20, "urgent": 15, "critical": 15,
-        "epic": 8, "feature": -3, "nice to have": -10, "someday": -15
-    }
-    title_lower = title.lower()
-    for keyword, boost in keyword_scores.items():
-        if keyword in title_lower:
-            score += boost
-            if boost > 0:
-                reasons.append(f"Keyword match: '{keyword}' (+{boost})")
-
-    # Label-based adjustments
-    for label in labels:
-        lower = label.lower()
-        if lower == "pipeline":
-            score += 5  # Pipeline issues are infrastructure
-        elif lower == "bug":
-            score += 12
-        elif lower == "enhancement":
-            score -= 2
-        elif lower == "documentation":
-            score -= 5
-        elif "epic" in lower:
-            score += 3
-
-    # Determine suggested priority
-    if score >= 40:
-        suggested = "P0"
-    elif score >= 25:
-        suggested = "P1"
-    elif score >= 10:
-        suggested = "P2"
-    elif score >= 0:
-        suggested = "P3"
-    else:
-        suggested = None  # Consider closing or deprioritizing
-
-    return IssueScore(
-        issue_id=issue_id,
-        repo=repo,
-        title=title,
-        current_labels=labels,
-        current_priority=current_priority,
-        suggested_priority=suggested,
-        score=round(score, 1),
-        reasons=reasons if reasons else ["No strong signals"],
-        age_days=age_days,
-        comment_count=comment_count,
-        assignee=assignee
-    )
-
-
-# ============================================================
-# Report Generation
-# ============================================================
-
-def generate_report(
-    scores: List[IssueScore],
-    signals: List[PipelineSignal],
-    org: str,
-    repos_scanned: List[str]
-) -> Dict[str, Any]:
-    """Generate the full priority report."""
-    now = datetime.now(timezone.utc).isoformat()
-
-    # Categorize changes
-    upgrades = [s for s in scores if s.suggested_priority and s.current_priority and
-                PRIORITY_LEVELS.index(s.suggested_priority) < PRIORITY_LEVELS.index(s.current_priority)]
-    downgrades = [s for s in scores if s.suggested_priority and s.current_priority and
-                  PRIORITY_LEVELS.index(s.suggested_priority) > PRIORITY_LEVELS.index(s.current_priority)]
-    new_assignments = [s for s in scores if s.suggested_priority and not s.current_priority]
-    no_change = [s for s in scores if s.suggested_priority == s.current_priority]
-
-    return {
-        "generated_at": now,
-        "org": org,
-        "repos_scanned": repos_scanned,
-        "total_issues": len(scores),
-        "signals": [asdict(s) for s in signals],
-        "summary": {
-            "suggested_upgrades": len(upgrades),
-            "suggested_downgrades": len(downgrades),
-            "suggested_new_priorities": len(new_assignments),
-            "unchanged": len(no_change)
-        },
-        "top_priority": [asdict(s) for s in sorted(scores, key=lambda x: x.score, reverse=True)[:10]],
-        "upgrades": [asdict(s) for s in upgrades],
-        "downgrades": [asdict(s) for s in downgrades],
-        "new_assignments": [asdict(s) for s in new_assignments],
-        "all_scores": [asdict(s) for s in sorted(scores, key=lambda x: x.score, reverse=True)]
-    }
-
-
-def generate_markdown_report(report: Dict[str, Any]) -> str:
-    """Generate human-readable markdown report."""
-    lines = []
-    lines.append("# Priority Rebalancer Report")
-    lines.append(f"**Generated:** {report['generated_at']}")
-    lines.append(f"**Org:** {report['org']}")
-    lines.append(f"**Repos scanned:** {', '.join(report['repos_scanned'])}")
-    lines.append(f"**Issues analyzed:** {report['total_issues']}")
-    lines.append("")
-
-    # Signals
-    if report["signals"]:
-        lines.append("## Pipeline Signals")
-        for sig in report["signals"]:
-            weight_bar = "█" * int(sig["weight"] * 10) + "░" * (10 - int(sig["weight"] * 10))
-            lines.append(f"- [{weight_bar}] **{sig['source']}/{sig['signal_type']}** — {sig['detail']}")
-        lines.append("")
-
-    # Summary
-    s = report["summary"]
-    lines.append("## Summary")
-    lines.append(f"- Suggested upgrades: **{s['suggested_upgrades']}**")
-    lines.append(f"- Suggested downgrades: **{s['suggested_downgrades']}**")
-    lines.append(f"- New priority assignments: **{s['suggested_new_priorities']}**")
-    lines.append(f"- Unchanged: **{s['unchanged']}**")
-    lines.append("")
-
-    # Top 10
-    lines.append("## Top 10 by Score")
-    for i, item in enumerate(report["top_priority"][:10], 1):
-        cur = item["current_priority"] or "none"
-        sug = item["suggested_priority"] or "none"
-        arrow = "↑" if PRIORITY_LEVELS.index(sug) < PRIORITY_LEVELS.index(cur) else "↓" if PRIORITY_LEVELS.index(sug) > PRIORITY_LEVELS.index(cur) else "→"
-        lines.append(f"{i}. **[{item['repo']}#{item['issue_id']}]** {item['title']}")
-        lines.append(f"   Score: {item['score']} | Current: {cur} {arrow} Suggested: {sug}")
-        lines.append(f"   Reasons: {'; '.join(item['reasons'][:3])}")
-        lines.append("")
-
-    # Upgrades
-    if report["upgrades"]:
-        lines.append("## Suggested Upgrades")
-        for item in report["upgrades"]:
-            lines.append(f"- **[{item['repo']}#{item['issue_id']}]** {item['title']}")
-            lines.append(f"  {item['current_priority']} → {item['suggested_priority']} (score: {item['score']})")
-            lines.append(f"  {'; '.join(item['reasons'][:2])}")
-        lines.append("")
-
-    # Downgrades
-    if report["downgrades"]:
-        lines.append("## Suggested Downgrades")
-        for item in report["downgrades"]:
-            lines.append(f"- **[{item['repo']}#{item['issue_id']}]** {item['title']}")
-            lines.append(f"  {item['current_priority']} → {item['suggested_priority']} (score: {item['score']})")
-            lines.append(f"  {'; '.join(item['reasons'][:2])}")
-        lines.append("")
-
-    # New assignments
-    if report["new_assignments"]:
-        lines.append("## New Priority Suggestions (currently unlabelled)")
-        for item in report["new_assignments"][:20]:
-            lines.append(f"- **[{item['repo']}#{item['issue_id']}]** {item['title']}")
-            lines.append(f"  Suggested: {item['suggested_priority']} (score: {item['score']})")
-            lines.append(f"  {'; '.join(item['reasons'][:2])}")
-        lines.append("")
-
-    return "\n".join(lines)
-
-
-# ============================================================
-# Main
-# ============================================================
-
-def main():
-    parser = argparse.ArgumentParser(description="Priority Rebalancer — re-score issues based on pipeline data")
-    parser.add_argument("--org", default="Timmy_Foundation", help="Gitea org name")
-    parser.add_argument("--repo", help="Single repo to analyze (default: all)")
-    parser.add_argument("--base-url", default="https://forge.alexanderwhitestone.com", help="Gitea base URL")
-    parser.add_argument("--knowledge-dir", default=None, help="Path to knowledge directory")
-    parser.add_argument("--metrics-dir", default=None, help="Path to metrics directory")
-    parser.add_argument("--scripts-dir", default=None, help="Path to scripts directory")
-    parser.add_argument("--output-dir", default=None, help="Path to output directory")
-    parser.add_argument("--dry-run", action="store_true", help="Show what would change without applying")
-    parser.add_argument("--apply", action="store_true", help="Apply priority changes via API")
-    parser.add_argument("--json", action="store_true", help="Output JSON instead of markdown")
-
-    args = parser.parse_args()
-
-    # Resolve paths relative to script location
-    script_dir = Path(__file__).parent
-    repo_root = script_dir.parent
-
-    knowledge_dir = args.knowledge_dir or str(repo_root / "knowledge")
-    metrics_dir = args.metrics_dir or str(repo_root / "metrics")
-    scripts_dir = args.scripts_dir or str(repo_root / "scripts")
-    output_dir = args.output_dir or str(repo_root / "metrics")
-
-    # Get token
-    token = os.environ.get("GITEA_TOKEN")
-    if not token:
-        token_path = os.path.expanduser("~/.config/gitea/token")
-        if os.path.exists(token_path):
-            with open(token_path) as f:
-                token = f.read().strip()
-
-    if not token:
-        print("Error: No Gitea token found. Set GITEA_TOKEN or create ~/.config/gitea/token", file=sys.stderr)
-        sys.exit(1)
-
-    client = GiteaClient(args.base_url, token)
-    now = datetime.utcnow()
-
-    # Collect pipeline signals
-    print("Collecting pipeline signals...", file=sys.stderr)
-    signals = []
-    signals.extend(collect_knowledge_signals(knowledge_dir))
-    signals.extend(collect_staleness_signals(scripts_dir, knowledge_dir))
-    signals.extend(collect_metrics_signals(metrics_dir))
-    print(f"  Found {len(signals)} signals", file=sys.stderr)
-
-    # Get repos
-    if args.repo:
-        repos = [{"name": args.repo}]
-    else:
-        repos = client.get_org_repos(args.org)
-
-    repo_names = [r["name"] for r in repos]
-    print(f"Scanning {len(repo_names)} repos: {', '.join(repo_names[:5])}{'...' if len(repo_names) > 5 else ''}", file=sys.stderr)
-
-    # Score all issues
-    all_scores = []
-    for repo in repos:
-        repo_name = repo["name"]
-        issues = client.get_issues(args.org, repo_name)
-        print(f"  {repo_name}: {len(issues)} open issues", file=sys.stderr)
-
-        for issue in issues:
-            if issue.get("pull_request"):
-                continue
-            score = compute_issue_score(issue, repo_name, signals, now)
-            all_scores.append(score)
-
-    # Generate report
-    report = generate_report(all_scores, signals, args.org, repo_names)
-
-    # Output
-    os.makedirs(output_dir, exist_ok=True)
-
-    if args.json:
-        print(json.dumps(report, indent=2))
-    else:
-        md = generate_markdown_report(report)
-        print(md)
-
-    # Write files
-    report_path = os.path.join(output_dir, "priority_report.json")
-    with open(report_path, "w") as f:
-        json.dump(report, f, indent=2)
-    print(f"\nFull report: {report_path}", file=sys.stderr)
-
-    md_path = os.path.join(output_dir, "priority_suggestions.md")
-    with open(md_path, "w") as f:
-        f.write(generate_markdown_report(report))
-    print(f"Suggestions: {md_path}", file=sys.stderr)
-
-    # Apply changes if requested
-    if args.apply:
-        print("\nApplying priority changes...", file=sys.stderr)
-        applied = 0
-
-        # Get label IDs for priority labels
-        priority_label_map = {}
-        for repo_name in repo_names:
-            labels = client.get_repo_labels(args.org, repo_name)
-            for label in labels:
-                name = label.get("name", "").lower()
-                if name in ("p0", "p1", "p2", "p3"):
-                    priority_label_map[(repo_name, name)] = label["id"]
-
-        for score in all_scores:
-            if score.suggested_priority and score.suggested_priority != score.current_priority:
-                sug_lower = score.suggested_priority.lower()
-                label_id = priority_label_map.get((score.repo, sug_lower))
-                if label_id:
-                    ok = client.add_label_to_issue(args.org, score.repo, score.issue_id, [label_id])
-                    if ok:
-                        applied += 1
-                        print(f"  Applied: [{score.repo}#{score.issue_id}] → {score.suggested_priority}", file=sys.stderr)
-
-                    # Add comment explaining the change
-                    comment = f"**Priority Rebalancer** suggested: **{score.suggested_priority}** (was: {score.current_priority or 'none'})\n\n"
-                    comment += f"Score: {score.score}\n"
-                    comment += f"Reasons:\n"
-                    for r in score.reasons[:5]:
-                        comment += f"- {r}\n"
-                    client.add_comment(args.org, score.repo, score.issue_id, comment)
-
-        print(f"Applied {applied} priority changes", file=sys.stderr)
-
-    elif args.dry_run:
-        print(f"\nDry run — {report['summary']['suggested_upgrades'] + report['summary']['suggested_downgrades'] + report['summary']['suggested_new_priorities']} changes would be applied", file=sys.stderr)
-
-
-if __name__ == "__main__":
-    main()

scripts/test_knowledge_staleness.py

@@ -1,129 +0,0 @@
-#!/usr/bin/env python3
-"""Tests for scripts/knowledge_staleness_check.py — 8 tests."""
-
-import json
-import os
-import sys
-import tempfile
-
-sys.path.insert(0, os.path.dirname(__file__) or ".")
-import importlib.util
-spec = importlib.util.spec_from_file_location("ks", os.path.join(os.path.dirname(__file__) or ".", "knowledge_staleness_check.py"))
-mod = importlib.util.module_from_spec(spec)
-spec.loader.exec_module(mod)
-check_staleness = mod.check_staleness
-fix_hashes = mod.fix_hashes
-compute_file_hash = mod.compute_file_hash
-
-
-def test_fresh_entry():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        src = os.path.join(tmpdir, "source.py")
-        with open(src, "w") as f:
-            f.write("print('hello')")
-        h = compute_file_hash(src)
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            json.dump({"facts": [{"fact": "hello", "source_file": "source.py", "source_hash": h}]}, f)
-        results = check_staleness(idx, tmpdir)
-        assert results[0]["status"] == "fresh"
-        print("PASS: test_fresh_entry")
-
-
-def test_stale_entry():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        src = os.path.join(tmpdir, "source.py")
-        with open(src, "w") as f:
-            f.write("original content")
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            json.dump({"facts": [{"fact": "old", "source_file": "source.py", "source_hash": "sha256:wrong"}]}, f)
-        # Now change the source
-        with open(src, "w") as f:
-            f.write("modified content")
-        results = check_staleness(idx, tmpdir)
-        assert results[0]["status"] == "stale"
-        print("PASS: test_stale_entry")
-
-
-def test_missing_source():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            json.dump({"facts": [{"fact": "gone", "source_file": "nonexistent.py", "source_hash": "sha256:abc"}]}, f)
-        results = check_staleness(idx, tmpdir)
-        assert results[0]["status"] == "missing_source"
-        print("PASS: test_missing_source")
-
-
-def test_no_hash():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        src = os.path.join(tmpdir, "source.py")
-        with open(src, "w") as f:
-            f.write("content")
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            json.dump({"facts": [{"fact": "no hash", "source_file": "source.py"}]}, f)
-        results = check_staleness(idx, tmpdir)
-        assert results[0]["status"] == "no_hash"
-        assert results[0]["current_hash"].startswith("sha256:")
-        print("PASS: test_no_hash")
-
-
-def test_no_source_field():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            json.dump({"facts": [{"fact": "orphan"}]}, f)
-        results = check_staleness(idx, tmpdir)
-        assert results[0]["status"] == "no_source"
-        print("PASS: test_no_source_field")
-
-
-def test_fix_hashes():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        src = os.path.join(tmpdir, "source.py")
-        with open(src, "w") as f:
-            f.write("content for hashing")
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            json.dump({"facts": [{"fact": "needs hash", "source_file": "source.py"}]}, f)
-        fixed = fix_hashes(idx, tmpdir)
-        assert fixed == 1
-        # Verify hash was added
-        with open(idx) as f:
-            data = json.load(f)
-        assert data["facts"][0]["source_hash"].startswith("sha256:")
-        print("PASS: test_fix_hashes")
-
-
-def test_empty_index():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            json.dump({"facts": []}, f)
-        results = check_staleness(idx, tmpdir)
-        assert results == []
-        print("PASS: test_empty_index")
-
-
-def test_compute_hash_nonexistent():
-    h = compute_file_hash("/nonexistent/path/file.py")
-    assert h is None
-    print("PASS: test_compute_hash_nonexistent")
-
-
-def run_all():
-    test_fresh_entry()
-    test_stale_entry()
-    test_missing_source()
-    test_no_hash()
-    test_no_source_field()
-    test_fix_hashes()
-    test_empty_index()
-    test_compute_hash_nonexistent()
-    print("\nAll 8 tests passed!")
-
-
-if __name__ == "__main__":
-    run_all()

scripts/test_priority_rebalancer.py

@@ -1,305 +0,0 @@
-#!/usr/bin/env python3
-"""
-Tests for Priority Rebalancer
-"""
-
-import json
-import os
-import sys
-import tempfile
-from datetime import datetime, timedelta
-from pathlib import Path
-
-# Add script dir to path
-sys.path.insert(0, str(Path(__file__).parent))
-
-from priority_rebalancer import (
-    GiteaClient,
-    IssueScore,
-    PipelineSignal,
-    compute_issue_score,
-    collect_knowledge_signals,
-    collect_metrics_signals,
-    extract_priority,
-    generate_report,
-    generate_markdown_report,
-    PRIORITY_LEVELS,
-)
-
-# ============================================================
-# Test Helpers
-# ============================================================
-
-PASS = 0
-FAIL = 0
-
-def test(name):
-    def decorator(fn):
-        global PASS, FAIL
-        try:
-            fn()
-            PASS += 1
-            print(f"  [PASS] {name}")
-        except Exception as e:
-            FAIL += 1
-            print(f"  [FAIL] {name}: {e}")
-    return decorator
-
-def assert_eq(a, b, msg=""):
-    if a != b:
-        raise AssertionError(f"{msg} expected {b!r}, got {a!r}")
-
-def assert_true(v, msg=""):
-    if not v:
-        raise AssertionError(msg or "Expected True")
-
-def assert_false(v, msg=""):
-    if v:
-        raise AssertionError(msg or "Expected False")
-
-
-# ============================================================
-# Priority Extraction Tests
-# ============================================================
-
-print("=== Priority Rebalancer Tests ===\n")
-
-print("-- Priority Extraction --")
-
-@test("extract P0 from label")
-def _():
-    assert_eq(extract_priority(["P0", "bug"]), "P0")
-
-@test("extract P1 from priority:high")
-def _():
-    assert_eq(extract_priority(["priority:high"]), "P1")
-
-@test("extract P2 from priority:medium")
-def _():
-    assert_eq(extract_priority(["priority:medium"]), "P2")
-
-@test("extract P3 from priority:low")
-def _():
-    assert_eq(extract_priority(["priority:low"]), "P3")
-
-@test("returns None for no priority")
-def _():
-    assert_eq(extract_priority(["bug", "enhancement"]), None)
-
-@test("case insensitive")
-def _():
-    assert_eq(extract_priority(["p1"]), "P1")
-    assert_eq(extract_priority(["PRIORITY:CRITICAL"]), "P0")
-
-
-# ============================================================
-# Issue Scoring Tests
-# ============================================================
-
-print("\n-- Issue Scoring --")
-
-def make_issue(**kwargs):
-    defaults = {
-        "number": 1,
-        "title": "Test issue",
-        "labels": [],
-        "created_at": (datetime.utcnow() - timedelta(days=5)).isoformat() + "Z",
-        "comments": 0,
-        "assignees": None,
-    }
-    defaults.update(kwargs)
-    return defaults
-
-@test("bug gets score boost")
-def _():
-    issue = make_issue(title="Incorrect output format", labels=["bug"])
-    score = compute_issue_score(issue, "test-repo", [], datetime.utcnow())
-    assert_true(score.score > 0, f"Bug should boost score, got {score.score}")
-    # Bug label alone should be P2 or P3 (not P0)
-    assert_true(score.suggested_priority in ("P2", "P3"),
-                f"Bug label alone should be P2/P3, got {score.suggested_priority}")
-
-@test("security gets high score")
-def _():
-    issue = make_issue(title="Security: auth bypass", labels=["bug"])
-    score = compute_issue_score(issue, "test-repo", [], datetime.utcnow())
-    assert_true(score.score >= 25, f"Security should score high, got {score.score}")
-
-@test("old dormant issue gets penalized")
-def _():
-    issue = make_issue(
-        title="Some old feature",
-        created_at=(datetime.utcnow() - timedelta(days=120)).isoformat() + "Z",
-        comments=0
-    )
-    score = compute_issue_score(issue, "test-repo", [], datetime.utcnow())
-    assert_true(score.score < 0, f"Old dormant should be negative, got {score.score}")
-    assert_true(any("Dormant" in r for r in score.reasons), "Should mention dormancy")
-
-@test("active discussion boosts score")
-def _():
-    issue = make_issue(title="Important fix", comments=8)
-    score = compute_issue_score(issue, "test-repo", [], datetime.utcnow())
-    assert_true(score.score > 5, f"Active discussion should boost, got {score.score}")
-    assert_true(any("Active" in r for r in score.reasons))
-
-@test("unassigned gets slight boost")
-def _():
-    issue = make_issue(title="Fix bug", assignees=None)
-    score = compute_issue_score(issue, "test-repo", [], datetime.utcnow())
-    assert_true(any("Unassigned" in r for r in score.reasons))
-
-@test("assigned issue notes assignee")
-def _():
-    issue = make_issue(title="Fix bug", assignees=[{"login": "alice"}])
-    score = compute_issue_score(issue, "test-repo", [], datetime.utcnow())
-    assert_eq(score.assignee, "alice")
-
-@test("nice-to-have gets penalized")
-def _():
-    issue = make_issue(title="Nice to have: fancy animation")
-    score = compute_issue_score(issue, "test-repo", [], datetime.utcnow())
-    assert_true(score.score < 0, f"Nice-to-have should be negative, got {score.score}")
-
-
-# ============================================================
-# Pipeline Signal Tests
-# ============================================================
-
-print("\n-- Pipeline Signals --")
-
-@test("signal alignment boosts matching issues")
-def _():
-    signals = [PipelineSignal(
-        source="knowledge",
-        signal_type="stale_knowledge",
-        weight=0.8,
-        detail="20 stale facts"
-    )]
-    issue = make_issue(title="Fix stale knowledge entries")
-    score = compute_issue_score(issue, "test-repo", signals, datetime.utcnow())
-    assert_true(any("Matches signal" in r for r in score.reasons))
-
-@test("empty knowledge boosts harvester issues")
-def _():
-    signals = [PipelineSignal(
-        source="knowledge",
-        signal_type="empty_knowledge",
-        weight=0.7,
-        detail="0 facts"
-    )]
-    issue = make_issue(title="Implement harvester pipeline")
-    score = compute_issue_score(issue, "test-repo", signals, datetime.utcnow())
-    assert_true(any("Critical gap" in r for r in score.reasons))
-
-
-# ============================================================
-# Knowledge Signal Collection Tests
-# ============================================================
-
-print("\n-- Knowledge Signal Collection --")
-
-@test("missing index generates signal")
-def _():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        signals = collect_knowledge_signals(tmpdir)
-        assert_true(len(signals) > 0)
-        assert_eq(signals[0].signal_type, "missing_index")
-
-@test("empty knowledge generates signal")
-def _():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            json.dump({"facts": []}, f)
-        signals = collect_knowledge_signals(tmpdir)
-        assert_true(any(s.signal_type == "empty_knowledge" for s in signals))
-
-@test("corrupt index generates signal")
-def _():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            f.write("not json {{{")
-        signals = collect_knowledge_signals(tmpdir)
-        assert_true(any(s.signal_type == "corrupt_index" for s in signals))
-
-@test("knowledge with facts passes")
-def _():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        idx = os.path.join(tmpdir, "index.json")
-        with open(idx, "w") as f:
-            json.dump({"facts": [
-                {"id": 1, "repo": "test", "status": "fresh"},
-                {"id": 2, "repo": "test", "status": "fresh"},
-            ]}, f)
-        signals = collect_knowledge_signals(tmpdir)
-        # Should not generate missing_index or empty_knowledge
-        assert_false(any(s.signal_type in ("missing_index", "empty_knowledge") for s in signals))
-
-
-# ============================================================
-# Metrics Signal Collection Tests
-# ============================================================
-
-print("\n-- Metrics Signal Collection --")
-
-@test("empty metrics dir generates signal")
-def _():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        signals = collect_metrics_signals(tmpdir)
-        assert_true(any(s.signal_type == "no_metrics" for s in signals))
-
-@test("metrics with files passes")
-def _():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        # Create files (simulating real metrics dir with .gitkeep + actual files)
-        with open(os.path.join(tmpdir, ".gitkeep"), "w") as f:
-            f.write("")
-        with open(os.path.join(tmpdir, "report.json"), "w") as f:
-            f.write("{}")
-        signals = collect_metrics_signals(tmpdir)
-        assert_false(any(s.signal_type == "no_metrics" for s in signals))
-
-
-# ============================================================
-# Report Generation Tests
-# ============================================================
-
-print("\n-- Report Generation --")
-
-@test("report has correct structure")
-def _():
-    scores = [
-        IssueScore(1, "repo1", "Bug fix", ["bug"], None, "P1", 30.0, ["test"], 5, 3, None),
-        IssueScore(2, "repo1", "Feature", ["enhancement"], "P3", None, -5.0, ["test"], 60, 0, "alice"),
-    ]
-    signals = [PipelineSignal("knowledge", "stale_knowledge", 0.5, "10 stale")]
-    report = generate_report(scores, signals, "test-org", ["repo1"])
-
-    assert_eq(report["org"], "test-org")
-    assert_eq(report["total_issues"], 2)
-    assert_true("generated_at" in report)
-    assert_true("summary" in report)
-    assert_true("top_priority" in report)
-    assert_eq(report["summary"]["suggested_new_priorities"], 1)
-
-@test("markdown report is non-empty")
-def _():
-    scores = [IssueScore(1, "repo1", "Test", ["bug"], None, "P2", 15.0, ["reason"], 5, 0, None)]
-    report = generate_report(scores, [], "test-org", ["repo1"])
-    md = generate_markdown_report(report)
-    assert_true(len(md) > 100)
-    assert_true("Priority Rebalancer Report" in md)
-    assert_true("Top 10" in md)
-
-
-# ============================================================
-# Summary
-# ============================================================
-
-print(f"\n=== Summary ===")
-print(f"Total: {PASS + FAIL} | Passed: {PASS} | Failed: {FAIL}")
-
-if FAIL > 0:
-    sys.exit(1)