feat: add sampler.py — session value scorer (#17)

scripts/improvement_proposals.py

@@ -1,451 +0,0 @@
-#!/usr/bin/env python3
-"""
-Improvement Proposal Generator for compounding-intelligence.
-
-Analyzes fleet session data to identify waste patterns and generates
-concrete improvement proposals with ROI estimates.
-
-Input: Session analytics JSON (from fleet metrics or session database)
-Output: Markdown proposal document + JSON proposals
-
-Usage:
-    python3 scripts/improvement_proposals.py --input analytics.json
-    python3 scripts/improvement_proposals.py --input analytics.json --format json
-    python3 scripts/improvement_proposals.py --input analytics.json --output proposals.md
-    python3 scripts/improvement_proposals.py --input analytics.json --threshold 5.0
-"""
-
-import argparse
-import json
-import os
-import sys
-from collections import defaultdict
-from dataclasses import dataclass, field, asdict
-from datetime import datetime, timezone
-from typing import Any, Dict, List, Optional
-
-
-# ── Data types ─────────────────────────────────────────────────
-
-@dataclass
-class WastePattern:
-    """A detected waste pattern in fleet sessions."""
-    pattern_type: str       # "repeated_error", "manual_process", "slow_tool", "failed_retry"
-    description: str
-    occurrences: int
-    total_time_hours: float
-    affected_repos: List[str] = field(default_factory=list)
-    example_sessions: List[str] = field(default_factory=list)
-
-
-@dataclass
-class ImprovementProposal:
-    """A concrete improvement proposal with ROI estimate."""
-    title: str
-    problem: str
-    proposed_solution: str
-    estimated_weekly_hours_saved: float
-    estimated_monthly_hours_saved: float
-    implementation_hours: float
-    roi_weeks: float           # weeks to break even
-    priority: str              # "critical", "high", "medium", "low"
-    affected_area: str
-    supporting_evidence: List[str] = field(default_factory=list)
-
-
-# ── Session analysis ──────────────────────────────────────────
-
-def analyze_sessions(sessions: List[dict]) -> List[WastePattern]:
-    """
-    Analyze session data to find waste patterns.
-
-    Looks for:
-    - Repeated errors (same error across sessions)
-    - Manual processes (long sequences of similar actions)
-    - Slow tools (tools with high latency)
-    - Failed retries (multiple attempts at same task)
-    """
-    patterns = []
-
-    # Track error frequency across sessions
-    error_counts: Dict[str, List[dict]] = defaultdict(list)
-    tool_latencies: Dict[str, List[float]] = defaultdict(list)
-    retry_counts: Dict[str, int] = defaultdict(int)
-    manual_sequences: List[dict] = []
-
-    for session in sessions:
-        session_id = session.get("session_id", "unknown")
-        repo = session.get("repo", "global")
-        messages = session.get("messages", [])
-        errors = session.get("errors", [])
-        tool_calls = session.get("tool_calls", [])
-        duration_min = session.get("duration_minutes", 0)
-
-        # 1. Repeated errors
-        for err in errors:
-            err_key = _normalize_error(err.get("message", ""))
-            if err_key:
-                error_counts[err_key].append({
-                    "session_id": session_id,
-                    "repo": repo,
-                })
-
-        # 2. Tool latency tracking
-        for tc in tool_calls:
-            tool_name = tc.get("tool", "unknown")
-            latency = tc.get("latency_ms", 0)
-            if latency > 0:
-                tool_latencies[tool_name].append(latency)
-
-        # 3. Failed retries (same tool called 3+ times in sequence)
-        prev_tool = None
-        streak = 0
-        for tc in tool_calls:
-            tool_name = tc.get("tool", "unknown")
-            if tool_name == prev_tool:
-                streak += 1
-            else:
-                if streak >= 3:
-                    retry_counts[prev_tool] += 1
-                streak = 1
-            prev_tool = tool_name
-        if streak >= 3:
-            retry_counts[prev_tool] += 1
-
-        # 4. Manual processes (10+ sequential tool calls with no automation)
-        if len(tool_calls) > 10:
-            tool_sequence = [tc.get("tool") for tc in tool_calls]
-            unique_tools = set(tool_sequence)
-            if len(unique_tools) <= 3 and len(tool_calls) > 10:
-                manual_sequences.append({
-                    "session_id": session_id,
-                    "repo": repo,
-                    "tool_count": len(tool_calls),
-                    "unique_tools": list(unique_tools),
-                    "duration_min": duration_min,
-                })
-
-    # Generate patterns from collected data
-
-    # Repeated errors (appearing in 3+ sessions)
-    for err_key, occurrences in error_counts.items():
-        if len(occurrences) >= 3:
-            repos = list(set(o["repo"] for o in occurrences))
-            sessions_list = [o["session_id"] for o in occurrences[:5]]
-            # Estimate time wasted: 5 min per error occurrence
-            hours = len(occurrences) * 5 / 60
-            patterns.append(WastePattern(
-                pattern_type="repeated_error",
-                description=f"Error: {err_key[:100]}",
-                occurrences=len(occurrences),
-                total_time_hours=round(hours, 1),
-                affected_repos=repos,
-                example_sessions=sessions_list,
-            ))
-
-    # Slow tools (avg latency > 5000ms across 5+ calls)
-    for tool, latencies in tool_latencies.items():
-        if len(latencies) >= 5:
-            avg_ms = sum(latencies) / len(latencies)
-            if avg_ms > 5000:
-                hours = sum(latencies) / 1000 / 3600
-                patterns.append(WastePattern(
-                    pattern_type="slow_tool",
-                    description=f"Tool '{tool}' averages {avg_ms:.0f}ms latency",
-                    occurrences=len(latencies),
-                    total_time_hours=round(hours, 1),
-                    affected_repos=["global"],
-                    example_sessions=[],
-                ))
-
-    # Failed retries
-    for tool, count in retry_counts.items():
-        if count >= 2:
-            hours = count * 10 / 60  # ~10 min per failed retry sequence
-            patterns.append(WastePattern(
-                pattern_type="failed_retry",
-                description=f"Tool '{tool}' had {count} retry sequences (3+ consecutive calls)",
-                occurrences=count,
-                total_time_hours=round(hours, 1),
-                affected_repos=["global"],
-                example_sessions=[],
-            ))
-
-    # Manual processes
-    for seq in manual_sequences:
-        hours = seq["duration_min"] / 60
-        patterns.append(WastePattern(
-            pattern_type="manual_process",
-            description=f"Session {seq['session_id'][:12]}: {seq['tool_count']} tool calls with only {len(seq['unique_tools'])} unique tools",
-            occurrences=1,
-            total_time_hours=round(hours, 1),
-            affected_repos=[seq["repo"]],
-            example_sessions=[seq["session_id"]],
-        ))
-
-    return sorted(patterns, key=lambda p: p.total_time_hours, reverse=True)
-
-
-def _normalize_error(message: str) -> str:
-    """Normalize error message to a common key."""
-    if not message:
-        return ""
-    msg = message.lower().strip()
-    # Remove variable parts (paths, IDs, timestamps)
-    import re
-    msg = re.sub(r'/\S+', '/PATH', msg)
-    msg = re.sub(r'\b[0-9a-f]{8,}\b', 'HASH', msg)
-    msg = re.sub(r'\d{4}-\d{2}-\d{2}[tT]\d{2}:\d{2}', 'TIME', msg)
-    return msg[:150]
-
-
-# ── Proposal generation ───────────────────────────────────────
-
-def generate_proposals(
-    patterns: List[WastePattern],
-    hourly_rate: float = 50.0,
-    implementation_overhead: float = 1.5,
-) -> List[ImprovementProposal]:
-    """
-    Generate improvement proposals from waste patterns.
-
-    Args:
-        patterns: Detected waste patterns
-        hourly_rate: Developer hourly rate for ROI calculation
-        implementation_overhead: Multiplier for implementation time estimate
-    """
-    proposals = []
-
-    # Group patterns by type
-    by_type: Dict[str, List[WastePattern]] = defaultdict(list)
-    for p in patterns:
-        by_type[p.pattern_type].append(p)
-
-    # 1. Repeated errors → Create fix/skill
-    for p in by_type.get("repeated_error", []):
-        weekly_hours = p.total_time_hours / 4  # monthly → weekly
-        impl_hours = max(1.0, p.occurrences * 0.25) * implementation_overhead
-        roi_weeks = impl_hours / weekly_hours if weekly_hours > 0 else float('inf')
-
-        proposals.append(ImprovementProposal(
-            title=f"Fix repeated error: {p.description[:60]}",
-            problem=f"This error occurred {p.occurrences} times across {len(p.affected_repos)} repos, wasting ~{p.total_time_hours:.1f} hours.",
-            proposed_solution="Root-cause the error and create a permanent fix or mitigation skill.",
-            estimated_weekly_hours_saved=round(weekly_hours, 1),
-            estimated_monthly_hours_saved=round(p.total_time_hours, 1),
-            implementation_hours=round(impl_hours, 1),
-            roi_weeks=round(roi_weeks, 1),
-            priority=_priority_from_roi(roi_weeks),
-            affected_area="reliability",
-            supporting_evidence=[f"{p.occurrences} occurrences in sessions: {', '.join(p.example_sessions[:3])}"],
-        ))
-
-    # 2. Slow tools → Optimize or replace
-    for p in by_type.get("slow_tool", []):
-        weekly_hours = p.total_time_hours / 4
-        impl_hours = 3.0 * implementation_overhead  # optimization task
-        roi_weeks = impl_hours / weekly_hours if weekly_hours > 0 else float('inf')
-
-        proposals.append(ImprovementProposal(
-            title=f"Optimize slow tool: {p.description[:60]}",
-            problem=f"Tool has {p.occurrences} calls with high latency, wasting ~{p.total_time_hours:.1f} hours total.",
-            proposed_solution="Profile the tool, add caching, or replace with a faster alternative.",
-            estimated_weekly_hours_saved=round(weekly_hours, 1),
-            estimated_monthly_hours_saved=round(p.total_time_hours, 1),
-            implementation_hours=round(impl_hours, 1),
-            roi_weeks=round(roi_weeks, 1),
-            priority=_priority_from_roi(roi_weeks),
-            affected_area="performance",
-            supporting_evidence=[f"{p.occurrences} slow calls detected"],
-        ))
-
-    # 3. Failed retries → Add retry logic or validation
-    for p in by_type.get("failed_retry", []):
-        weekly_hours = p.total_time_hours / 4
-        impl_hours = 2.0 * implementation_overhead
-        roi_weeks = impl_hours / weekly_hours if weekly_hours > 0 else float('inf')
-
-        proposals.append(ImprovementProposal(
-            title=f"Reduce retries for tool '{p.description[:50]}'",
-            problem=f"Tool had {p.occurrences} retry sequences, wasting ~{p.total_time_hours:.1f} hours.",
-            proposed_solution="Add input validation, pre-flight checks, or automatic retry with backoff.",
-            estimated_weekly_hours_saved=round(weekly_hours, 1),
-            estimated_monthly_hours_saved=round(p.total_time_hours, 1),
-            implementation_hours=round(impl_hours, 1),
-            roi_weeks=round(roi_weeks, 1),
-            priority=_priority_from_roi(roi_weeks),
-            affected_area="reliability",
-            supporting_evidence=[f"{p.occurrences} retry sequences detected"],
-        ))
-
-    # 4. Manual processes → Automate
-    total_manual_hours = sum(p.total_time_hours for p in by_type.get("manual_process", []))
-    manual_patterns = by_type.get("manual_process", [])
-    if manual_patterns:
-        weekly_hours = total_manual_hours / 4
-        impl_hours = len(manual_patterns) * 2.0 * implementation_overhead
-        roi_weeks = impl_hours / weekly_hours if weekly_hours > 0 else float('inf')
-
-        proposals.append(ImprovementProposal(
-            title=f"Automate {len(manual_patterns)} manual processes",
-            problem=f"{len(manual_patterns)} sessions had long manual tool sequences, wasting ~{total_manual_hours:.1f} hours.",
-            proposed_solution="Create composite skills or scripts that combine the repeated tool sequences into single operations.",
-            estimated_weekly_hours_saved=round(weekly_hours, 1),
-            estimated_monthly_hours_saved=round(total_manual_hours, 1),
-            implementation_hours=round(impl_hours, 1),
-            roi_weeks=round(roi_weeks, 1),
-            priority=_priority_from_roi(roi_weeks),
-            affected_area="automation",
-            supporting_evidence=[f"{len(manual_patterns)} manual sessions detected"],
-        ))
-
-    return sorted(proposals, key=lambda p: p.estimated_monthly_hours_saved, reverse=True)
-
-
-def _priority_from_roi(roi_weeks: float) -> str:
-    """Determine priority from ROI break-even time."""
-    if roi_weeks <= 1:
-        return "critical"
-    elif roi_weeks <= 4:
-        return "high"
-    elif roi_weeks <= 12:
-        return "medium"
-    return "low"
-
-
-# ── Output formatting ─────────────────────────────────────────
-
-def format_proposals_markdown(
-    proposals: List[ImprovementProposal],
-    patterns: List[WastePattern],
-    generated_at: str,
-) -> str:
-    """Format proposals as a markdown document."""
-    lines = [
-        "# Improvement Proposals",
-        "",
-        f"Generated: {generated_at}",
-        f"Based on analysis of {sum(p.occurrences for p in patterns)} waste events across {len(set(r for p in patterns for r in p.affected_repos))} repos.",
-        "",
-        "---",
-        "",
-        "## Summary",
-        "",
-        f"| Metric | Value |",
-        f"|--------|-------|",
-        f"| Total proposals | {len(proposals)} |",
-        f"| Critical priority | {sum(1 for p in proposals if p.priority == 'critical')} |",
-        f"| Total monthly hours wasted | {sum(p.estimated_monthly_hours_saved for p in proposals):.1f}h |",
-        f"| Total weekly hours recoverable | {sum(p.estimated_weekly_hours_saved for p in proposals):.1f}h |",
-        f"| Implementation investment | {sum(p.implementation_hours for p in proposals):.1f}h |",
-        "",
-        "---",
-        "",
-    ]
-
-    for i, prop in enumerate(proposals, 1):
-        lines.extend([
-            f"## {i}. {prop.title}",
-            "",
-            f"**Priority:** {prop.priority.upper()}  ",
-            f"**Area:** {prop.affected_area}  ",
-            f"**ROI break-even:** {prop.roi_weeks:.1f} weeks",
-            "",
-            "### Problem",
-            "",
-            prop.problem,
-            "",
-            "### Proposed Solution",
-            "",
-            prop.proposed_solution,
-            "",
-            "### ROI Estimate",
-            "",
-            f"- Weekly hours saved: **{prop.estimated_weekly_hours_saved}h**",
-            f"- Monthly hours saved: **{prop.estimated_monthly_hours_saved}h**",
-            f"- Implementation time: **{prop.implementation_hours}h**",
-            f"- Break-even: **{prop.roi_weeks:.1f} weeks**",
-            "",
-        ])
-
-        if prop.supporting_evidence:
-            lines.extend([
-                "### Evidence",
-                "",
-            ])
-            for ev in prop.supporting_evidence:
-                lines.append(f"- {ev}")
-            lines.append("")
-
-        lines.extend(["---", ""])
-
-    # Waste pattern appendix
-    lines.extend([
-        "## Appendix: Detected Waste Patterns",
-        "",
-        "| Type | Description | Occurrences | Hours |",
-        "|------|-------------|-------------|-------|",
-    ])
-    for p in patterns[:20]:
-        lines.append(
-            f"| {p.pattern_type} | {p.description[:60]} | {p.occurrences} | {p.total_time_hours}h |"
-        )
-    lines.append("")
-
-    return "\n".join(lines)
-
-
-def format_proposals_json(proposals: List[ImprovementProposal]) -> str:
-    """Format proposals as JSON."""
-    return json.dumps(
-        [asdict(p) for p in proposals],
-        indent=2,
-        default=str,
-    )
-
-
-# ── Main ──────────────────────────────────────────────────────
-
-def main():
-    parser = argparse.ArgumentParser(description="Generate improvement proposals from session analytics")
-    parser.add_argument("--input", required=True, help="Path to session analytics JSON file")
-    parser.add_argument("--output", help="Output file path (default: stdout)")
-    parser.add_argument("--format", choices=["markdown", "json"], default="markdown", help="Output format")
-    parser.add_argument("--hourly-rate", type=float, default=50.0, help="Developer hourly rate for ROI calc")
-    parser.add_argument("--threshold", type=float, default=2.0, help="Min monthly hours to include proposal")
-
-    args = parser.parse_args()
-
-    with open(args.input) as f:
-        data = json.load(f)
-
-    sessions = data if isinstance(data, list) else data.get("sessions", [])
-
-    if not sessions:
-        print("No sessions found in input file.", file=sys.stderr)
-        sys.exit(1)
-
-    # Analyze
-    patterns = analyze_sessions(sessions)
-    proposals = generate_proposals(patterns, hourly_rate=args.hourly_rate)
-
-    # Filter by threshold
-    proposals = [p for p in proposals if p.estimated_monthly_hours_saved >= args.threshold]
-
-    generated_at = datetime.now(timezone.utc).isoformat()
-
-    if args.format == "markdown":
-        output = format_proposals_markdown(proposals, patterns, generated_at)
-    else:
-        output = format_proposals_json(proposals)
-
-    if args.output:
-        with open(args.output, "w") as f:
-            f.write(output)
-        print(f"Wrote {len(proposals)} proposals to {args.output}", file=sys.stderr)
-    else:
-        print(output)
-
-
-if __name__ == "__main__":
-    main()

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/sampler.py

@@ -0,0 +1,353 @@
+#!/usr/bin/env python3
+"""
+sampler.py — Score and rank sessions by harvest value.
+
+With 20k+ sessions on disk, we can't harvest all at once. This script
+scores each session by how likely it is to contain valuable knowledge,
+so the harvester processes the best ones first.
+
+Scoring strategy:
+  - Recency: last 7d=3pts, last 30d=2pts, older=1pt
+  - Length: >50 messages=3pts, >20=2pts, <20=1pt
+  - Repo uniqueness: first session for a repo=5pts, otherwise=1pt
+  - Outcome: failure=3pts (most to learn), success=2pts, unknown=1pt
+  - Tool calls: >10 tool invocations=2pts (complex sessions)
+
+Usage:
+    python3 sampler.py --count 100                          # Top 100 sessions
+    python3 sampler.py --repo the-nexus --count 20          # Top 20 for a repo
+    python3 sampler.py --since 2026-04-01                   # All sessions since date
+    python3 sampler.py --count 50 --min-score 8             # Only high-value sessions
+    python3 sampler.py --count 100 --output sample.json     # Save to file
+"""
+
+import argparse
+import json
+import os
+import sys
+import time
+from datetime import datetime, timedelta, timezone
+from pathlib import Path
+from typing import Optional
+
+
+# --- Fast session scanning (no full parse) ---
+
+def scan_session_fast(path: str) -> dict:
+    """Extract scoring metadata from a session without parsing the full JSONL.
+    
+    Reads only: first line, last ~20 lines, and line count. This processes
+    20k sessions in seconds instead of minutes.
+    """
+    meta = {
+        'path': path,
+        'message_count': 0,
+        'has_tool_calls': False,
+        'tool_call_count': 0,
+        'first_timestamp': '',
+        'last_timestamp': '',
+        'is_failure': False,
+        'repos_mentioned': set(),
+        'first_role': '',
+        'last_content_preview': '',
+    }
+    
+    try:
+        file_size = os.path.getsize(path)
+        if file_size == 0:
+            return meta
+        
+        with open(path, 'r', encoding='utf-8', errors='replace') as f:
+            # Read first line for timestamp + role
+            first_line = f.readline().strip()
+            if first_line:
+                try:
+                    first_msg = json.loads(first_line)
+                    meta['first_timestamp'] = first_msg.get('timestamp', '')
+                    meta['first_role'] = first_msg.get('role', '')
+                except json.JSONDecodeError:
+                    pass
+            
+            # Fast line count + collect tail lines
+            # For the tail, seek to near end of file
+            tail_lines = []
+            line_count = 1  # already read first
+            
+            if file_size > 8192:
+                # Seek to last 8KB for tail sampling
+                f.seek(max(0, file_size - 8192))
+                f.readline()  # skip partial line
+                for line in f:
+                    line = line.strip()
+                    if line:
+                        tail_lines.append(line)
+                    line_count += 1
+                # We lost the exact count for big files — estimate from file size
+                # Average JSONL line is ~500 bytes
+                if line_count < 100:
+                    line_count = max(line_count, file_size // 500)
+            else:
+                # Small file — read all
+                for line in f:
+                    line = line.strip()
+                    if line:
+                        tail_lines.append(line)
+                    line_count += 1
+            
+            meta['message_count'] = line_count
+            
+            # Parse tail lines for outcome, tool calls, repos
+            for line in tail_lines[-30:]:  # last 30 non-empty lines
+                try:
+                    msg = json.loads(line)
+                    
+                    # Track last timestamp
+                    ts = msg.get('timestamp', '')
+                    if ts:
+                        meta['last_timestamp'] = ts
+                    
+                    # Count tool calls
+                    if msg.get('tool_calls'):
+                        meta['has_tool_calls'] = True
+                        meta['tool_call_count'] += len(msg['tool_calls'])
+                    
+                    # Detect failure signals in content
+                    content = ''
+                    if isinstance(msg.get('content'), str):
+                        content = msg['content'].lower()
+                    elif isinstance(msg.get('content'), list):
+                        for part in msg['content']:
+                            if isinstance(part, dict) and part.get('type') == 'text':
+                                content += part.get('text', '').lower()
+                    
+                    if content:
+                        meta['last_content_preview'] = content[:200]
+                        failure_signals = ['error', 'failed', 'cannot', 'unable', 
+                                          'exception', 'traceback', 'rejected', 'denied']
+                        if any(sig in content for sig in failure_signals):
+                            meta['is_failure'] = True
+                    
+                    # Extract repo references from tool call arguments
+                    if msg.get('tool_calls'):
+                        for tc in msg['tool_calls']:
+                            args = tc.get('function', {}).get('arguments', '')
+                            if isinstance(args, str):
+                                # Look for repo patterns
+                                for pattern in ['Timmy_Foundation/', 'Rockachopa/', 'compounding-intelligence', 'the-nexus', 'timmy-home', 'hermes-agent', 'the-beacon', 'the-door']:
+                                    if pattern in args:
+                                        repo = pattern.rstrip('/')
+                                        meta['repos_mentioned'].add(repo)
+                
+                except json.JSONDecodeError:
+                    continue
+    
+    except (IOError, OSError):
+        pass
+    
+    meta['repos_mentioned'] = list(meta['repos_mentioned'])
+    return meta
+
+
+# --- Filename timestamp parsing ---
+
+def parse_session_timestamp(filename: str) -> Optional[datetime]:
+    """Parse timestamp from session filename.
+    
+    Common formats:
+      session_20260413_123456_hash.jsonl
+      20260413_123456_hash.jsonl
+    """
+    stem = Path(filename).stem
+    parts = stem.split('_')
+    
+    # Try session_YYYYMMDD_HHMMSS format
+    for i, part in enumerate(parts):
+        if len(part) == 8 and part.isdigit():
+            date_part = part
+            time_part = parts[i + 1] if i + 1 < len(parts) and len(parts[i + 1]) == 6 else '000000'
+            try:
+                return datetime.strptime(f"{date_part}_{time_part}", '%Y%m%d_%H%M%S').replace(tzinfo=timezone.utc)
+            except ValueError:
+                continue
+    
+    # Fallback: use file modification time
+    return None
+
+
+# --- Scoring ---
+
+def score_session(meta: dict, now: datetime, seen_repos: set) -> tuple[int, dict]:
+    """Score a session for harvest value. Returns (score, breakdown)."""
+    score = 0
+    breakdown = {}
+    
+    # 1. Recency
+    ts = parse_session_timestamp(os.path.basename(meta['path']))
+    if ts is None:
+        # Fallback to mtime
+        try:
+            ts = datetime.fromtimestamp(os.path.getmtime(meta['path']), tz=timezone.utc)
+        except OSError:
+            ts = now - timedelta(days=365)
+    
+    age_days = (now - ts).days
+    if age_days <= 7:
+        recency = 3
+    elif age_days <= 30:
+        recency = 2
+    else:
+        recency = 1
+    score += recency
+    breakdown['recency'] = recency
+    
+    # 2. Length
+    count = meta['message_count']
+    if count > 50:
+        length = 3
+    elif count > 20:
+        length = 2
+    else:
+        length = 1
+    score += length
+    breakdown['length'] = length
+    
+    # 3. Repo uniqueness (first session mentioning a repo gets bonus)
+    repo_score = 0
+    for repo in meta.get('repos_mentioned', []):
+        if repo not in seen_repos:
+            seen_repos.add(repo)
+            repo_score = max(repo_score, 5)
+        else:
+            repo_score = max(repo_score, 1)
+    score += repo_score
+    breakdown['repo_unique'] = repo_score
+    
+    # 4. Outcome
+    if meta.get('is_failure'):
+        outcome = 3
+    elif meta.get('last_content_preview', '').strip():
+        outcome = 2  # has some content = likely completed
+    else:
+        outcome = 1
+    score += outcome
+    breakdown['outcome'] = outcome
+    
+    # 5. Tool calls
+    if meta.get('tool_call_count', 0) > 10:
+        tool = 2
+    else:
+        tool = 0
+    score += tool
+    breakdown['tool_calls'] = tool
+    
+    return score, breakdown
+
+
+# --- Main ---
+
+def main():
+    parser = argparse.ArgumentParser(description="Score and rank sessions for harvesting")
+    parser.add_argument('--sessions-dir', default=os.path.expanduser('~/.hermes/sessions'),
+                        help='Directory containing session files')
+    parser.add_argument('--count', type=int, default=100, help='Number of top sessions to return')
+    parser.add_argument('--repo', default='', help='Filter to sessions mentioning this repo')
+    parser.add_argument('--since', default='', help='Only score sessions after this date (YYYY-MM-DD)')
+    parser.add_argument('--min-score', type=int, default=0, help='Minimum score threshold')
+    parser.add_argument('--output', default='', help='Output file (JSON). Default: stdout')
+    parser.add_argument('--format', choices=['json', 'paths', 'table'], default='table',
+                        help='Output format: json (full), paths (one per line), table (human)')
+    parser.add_argument('--top-percent', type=float, default=0, help='Return top N%% instead of --count')
+    
+    args = parser.parse_args()
+    
+    sessions_dir = Path(args.sessions_dir)
+    if not sessions_dir.is_dir():
+        print(f"ERROR: Sessions directory not found: {sessions_dir}", file=sys.stderr)
+        sys.exit(1)
+    
+    # Find all JSONL files
+    print(f"Scanning {sessions_dir}...", file=sys.stderr)
+    t0 = time.time()
+    
+    session_files = list(sessions_dir.glob('*.jsonl'))
+    total = len(session_files)
+    print(f"Found {total} session files", file=sys.stderr)
+    
+    # Parse since date
+    since_dt = None
+    if args.since:
+        since_dt = datetime.strptime(args.since, '%Y-%m-%d').replace(tzinfo=timezone.utc)
+    
+    # Score all sessions
+    now = datetime.now(timezone.utc)
+    seen_repos = set()  # Track repos for uniqueness scoring
+    scored = []
+    
+    for i, sf in enumerate(session_files):
+        # Date filter (fast path: check filename first)
+        if since_dt:
+            ts = parse_session_timestamp(sf.name)
+            if ts and ts < since_dt:
+                continue
+        
+        meta = scan_session_fast(str(sf))
+        
+        # Repo filter
+        if args.repo:
+            repos = meta.get('repos_mentioned', [])
+            if args.repo.lower() not in [r.lower() for r in repos]:
+                # Also check filename
+                if args.repo.lower() not in sf.name.lower():
+                    continue
+        
+        score, breakdown = score_session(meta, now, seen_repos)
+        
+        if score >= args.min_score:
+            scored.append({
+                'path': str(sf),
+                'filename': sf.name,
+                'score': score,
+                'breakdown': breakdown,
+                'message_count': meta['message_count'],
+                'repos': meta['repos_mentioned'],
+                'is_failure': meta['is_failure'],
+            })
+        
+        if (i + 1) % 5000 == 0:
+            elapsed = time.time() - t0
+            print(f"  Scanned {i + 1}/{total} ({elapsed:.1f}s)", file=sys.stderr)
+    
+    elapsed = time.time() - t0
+    print(f"Scored {len(scored)} sessions in {elapsed:.1f}s", file=sys.stderr)
+    
+    # Sort by score descending
+    scored.sort(key=lambda x: x['score'], reverse=True)
+    
+    # Apply count or percent
+    if args.top_percent > 0:
+        count = max(1, int(len(scored) * args.top_percent / 100))
+    else:
+        count = args.count
+    scored = scored[:count]
+    
+    # Output
+    if args.output:
+        with open(args.output, 'w', encoding='utf-8') as f:
+            json.dump(scored, f, indent=2)
+        print(f"Wrote {len(scored)} sessions to {args.output}", file=sys.stderr)
+    elif args.format == 'json':
+        json.dump(scored, sys.stdout, indent=2)
+    elif args.format == 'paths':
+        for s in scored:
+            print(s['path'])
+    else:  # table
+        print(f"{'SCORE':>5}  {'MSGS':>5}  {'REPOS':<25}  {'FILE'}")
+        print(f"{'-'*5}  {'-'*5}  {'-'*25}  {'-'*40}")
+        for s in scored:
+            repos = ', '.join(s['repos'][:2]) if s['repos'] else '-'
+            fail = ' FAIL' if s['is_failure'] else ''
+            print(f"{s['score']:>5}  {s['message_count']:>5}  {repos:<25}  {s['filename'][:40]}{fail}")
+
+
+if __name__ == '__main__':
+    main()

scripts/test_improvement_proposals.py

@@ -1,282 +0,0 @@
-#!/usr/bin/env python3
-"""Tests for scripts/improvement_proposals.py — 15 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(
-    "ip", os.path.join(os.path.dirname(__file__) or ".", "improvement_proposals.py")
-)
-mod = importlib.util.module_from_spec(spec)
-spec.loader.exec_module(mod)
-
-analyze_sessions = mod.analyze_sessions
-generate_proposals = mod.generate_proposals
-format_proposals_markdown = mod.format_proposals_markdown
-format_proposals_json = mod.format_proposals_json
-_normalize_error = mod._normalize_error
-
-
-# ── Helper to build test sessions ─────────────────────────────
-
-def _make_session(session_id, repo="test-repo", errors=None, tool_calls=None, duration=30):
-    return {
-        "session_id": session_id,
-        "repo": repo,
-        "errors": [{"message": e} for e in (errors or [])],
-        "tool_calls": tool_calls or [],
-        "duration_minutes": duration,
-        "messages": [],
-    }
-
-
-def _make_tool_calls(repeats):
-    """Create tool call list with repeated tools."""
-    calls = []
-    for tool, count in repeats:
-        for _ in range(count):
-            calls.append({"tool": tool, "latency_ms": 100})
-    return calls
-
-
-# ── Tests ─────────────────────────────────────────────────────
-
-def test_empty_sessions():
-    patterns = analyze_sessions([])
-    assert patterns == []
-    print("PASS: test_empty_sessions")
-
-
-def test_no_patterns_on_clean_sessions():
-    sessions = [
-        _make_session("s1", tool_calls=[{"tool": "read_file", "latency_ms": 50}]),
-        _make_session("s2", tool_calls=[{"tool": "write_file", "latency_ms": 80}]),
-    ]
-    patterns = analyze_sessions(sessions)
-    # No repeated errors, no slow tools, no retries
-    assert len(patterns) == 0
-    print("PASS: test_no_patterns_on_clean_sessions")
-
-
-def test_repeated_error_detection():
-    """Same error across 3+ sessions triggers pattern."""
-    sessions = [
-        _make_session(f"s{i}", errors=["ModuleNotFoundError: No module named bannerlord_trace"])
-        for i in range(4)
-    ]
-    patterns = analyze_sessions(sessions)
-    repeated = [p for p in patterns if p.pattern_type == "repeated_error"]
-    assert len(repeated) == 1
-    assert repeated[0].occurrences == 4
-    print("PASS: test_repeated_error_detection")
-
-
-def test_repeated_error_threshold():
-    """2 occurrences should NOT trigger (threshold is 3)."""
-    sessions = [
-        _make_session("s1", errors=["TimeoutError: connection timed out"]),
-        _make_session("s2", errors=["TimeoutError: connection timed out"]),
-    ]
-    patterns = analyze_sessions(sessions)
-    repeated = [p for p in patterns if p.pattern_type == "repeated_error"]
-    assert len(repeated) == 0
-    print("PASS: test_repeated_error_threshold")
-
-
-def test_slow_tool_detection():
-    """Tool with avg latency > 5000ms across 5+ calls."""
-    calls = [{"tool": "git_push", "latency_ms": 8000} for _ in range(10)]
-    sessions = [_make_session("s1", tool_calls=calls)]
-    patterns = analyze_sessions(sessions)
-    slow = [p for p in patterns if p.pattern_type == "slow_tool"]
-    assert len(slow) == 1
-    assert "git_push" in slow[0].description
-    print("PASS: test_slow_tool_detection")
-
-
-def test_fast_tool_not_flagged():
-    """Tool under 5000ms avg should not trigger."""
-    calls = [{"tool": "read_file", "latency_ms": 50} for _ in range(10)]
-    sessions = [_make_session("s1", tool_calls=calls)]
-    patterns = analyze_sessions(sessions)
-    slow = [p for p in patterns if p.pattern_type == "slow_tool"]
-    assert len(slow) == 0
-    print("PASS: test_fast_tool_not_flagged")
-
-
-def test_failed_retry_detection():
-    """3+ consecutive calls to same tool triggers retry pattern."""
-    calls = _make_tool_calls([("execute_code", 5)])
-    sessions = [_make_session("s1", tool_calls=calls)]
-    sessions.extend([
-        _make_session(f"s{i}", tool_calls=_make_tool_calls([("execute_code", 4)]))
-        for i in range(2, 5)
-    ])
-    patterns = analyze_sessions(sessions)
-    retries = [p for p in patterns if p.pattern_type == "failed_retry"]
-    assert len(retries) >= 1
-    print("PASS: test_failed_retry_detection")
-
-
-def test_manual_process_detection():
-    """10+ tool calls with <= 3 unique tools."""
-    calls = _make_tool_calls([("terminal", 8), ("read_file", 5)])
-    sessions = [_make_session("s1", tool_calls=calls, duration=25)]
-    patterns = analyze_sessions(sessions)
-    manual = [p for p in patterns if p.pattern_type == "manual_process"]
-    assert len(manual) == 1
-    print("PASS: test_manual_process_detection")
-
-
-def test_generate_proposals_from_patterns():
-    """Proposals generated from waste patterns."""
-    sessions = [
-        _make_session(f"s{i}", errors=["Error: push timeout"])
-        for i in range(5)
-    ]
-    patterns = analyze_sessions(sessions)
-    proposals = generate_proposals(patterns)
-    assert len(proposals) >= 1
-    assert proposals[0].estimated_monthly_hours_saved > 0
-    assert proposals[0].priority in ("critical", "high", "medium", "low")
-    print("PASS: test_generate_proposals_from_patterns")
-
-
-def test_proposal_roi_positive():
-    """ROI weeks should be a positive number for recoverable time."""
-    patterns = [mod.WastePattern(
-        pattern_type="repeated_error",
-        description="Test error",
-        occurrences=10,
-        total_time_hours=5.0,
-        affected_repos=["test"],
-    )]
-    proposals = generate_proposals(patterns)
-    assert len(proposals) == 1
-    assert proposals[0].roi_weeks > 0
-    assert proposals[0].roi_weeks < 100
-    print("PASS: test_proposal_roi_positive")
-
-
-def test_proposals_sorted_by_impact():
-    """Proposals should be sorted by monthly hours saved (descending)."""
-    sessions = [
-        _make_session("s1", errors=["Minor warning"] * 3, duration=5),
-        _make_session("s2", errors=["Critical failure: deploy crashed"] * 5, duration=60),
-    ]
-    # Add more sessions to cross threshold
-    for i in range(3, 7):
-        sessions.append(_make_session(f"s{i}", errors=["Critical failure: deploy crashed"]))
-
-    patterns = analyze_sessions(sessions)
-    proposals = generate_proposals(patterns)
-    if len(proposals) >= 2:
-        for i in range(len(proposals) - 1):
-            assert proposals[i].estimated_monthly_hours_saved >= proposals[i + 1].estimated_monthly_hours_saved
-    print("PASS: test_proposals_sorted_by_impact")
-
-
-def test_format_markdown():
-    """Markdown output should contain expected sections."""
-    patterns = [mod.WastePattern(
-        pattern_type="repeated_error", description="Test", occurrences=5,
-        total_time_hours=2.5, affected_repos=["repo"],
-    )]
-    proposals = generate_proposals(patterns)
-    md = format_proposals_markdown(proposals, patterns, "2026-04-15T00:00:00Z")
-    assert "# Improvement Proposals" in md
-    assert "## Summary" in md
-    assert "### Problem" in md
-    assert "### ROI Estimate" in md
-    assert "## Appendix" in md
-    print("PASS: test_format_markdown")
-
-
-def test_format_json():
-    """JSON output should be valid and parseable."""
-    patterns = [mod.WastePattern(
-        pattern_type="slow_tool", description="Slow", occurrences=10,
-        total_time_hours=3.0, affected_repos=["global"],
-    )]
-    proposals = generate_proposals(patterns)
-    output = format_proposals_json(proposals)
-    parsed = json.loads(output)
-    assert isinstance(parsed, list)
-    assert len(parsed) == len(proposals)
-    assert "title" in parsed[0]
-    assert "roi_weeks" in parsed[0]
-    print("PASS: test_format_json")
-
-
-def test_normalize_error():
-    """Error normalization should remove paths and hashes."""
-    err1 = _normalize_error("Failed to clone /Users/apayne/repo with token abc123def456")
-    assert "/PATH" in err1
-    assert "HASH" in err1
-    assert "/Users/apayne" not in err1
-
-    err2 = _normalize_error("")
-    assert err2 == ""
-
-    err3 = _normalize_error("Simple error message")
-    assert "simple error" in err3
-    print("PASS: test_normalize_error")
-
-
-def test_cli_integration():
-    """End-to-end test: write input JSON, run script, check output."""
-    import subprocess
-
-    sessions = [
-        _make_session(f"s{i}", errors=["Connection refused: port 8080"])
-        for i in range(5)
-    ]
-
-    with tempfile.TemporaryDirectory() as tmpdir:
-        input_path = os.path.join(tmpdir, "analytics.json")
-        output_path = os.path.join(tmpdir, "proposals.md")
-
-        with open(input_path, "w") as f:
-            json.dump({"sessions": sessions}, f)
-
-        script = os.path.join(os.path.dirname(__file__) or ".", "improvement_proposals.py")
-        result = subprocess.run(
-            [sys.executable, script, "--input", input_path, "--output", output_path],
-            capture_output=True, text=True, timeout=10,
-        )
-
-        assert result.returncode == 0, f"CLI failed: {result.stderr}"
-        assert os.path.exists(output_path)
-
-        with open(output_path) as f:
-            content = f.read()
-        assert "# Improvement Proposals" in content
-        print("PASS: test_cli_integration")
-
-
-def run_all():
-    test_empty_sessions()
-    test_no_patterns_on_clean_sessions()
-    test_repeated_error_detection()
-    test_repeated_error_threshold()
-    test_slow_tool_detection()
-    test_fast_tool_not_flagged()
-    test_failed_retry_detection()
-    test_manual_process_detection()
-    test_generate_proposals_from_patterns()
-    test_proposal_roi_positive()
-    test_proposals_sorted_by_impact()
-    test_format_markdown()
-    test_format_json()
-    test_normalize_error()
-    test_cli_integration()
-    print("\nAll 15 tests passed!")
-
-
-if __name__ == "__main__":
-    run_all()

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()