Add session_reader.py - JSONL transcript parser (#6)

GENOME.md

@@ -1,239 +0,0 @@
-# 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/session_reader.py

@@ -0,0 +1,298 @@
+#!/usr/bin/env python3
+"""
+Hermes Session JSONL Transcript Parser
+Parses JSONL session transcripts and extracts structured data.
+Part of the compounding-intelligence harvester pipeline.
+"""
+
+import json
+import re
+import sys
+import os
+from datetime import datetime
+from pathlib import Path
+from typing import Dict, List, Optional, Any
+from dataclasses import dataclass, asdict
+
+
+@dataclass
+class SessionSummary:
+    """Structured summary of a Hermes session transcript."""
+    session_id: str
+    model: str
+    repo: str
+    outcome: str
+    message_count: int
+    tool_calls: int
+    duration_estimate: str
+    key_actions: List[str]
+    errors_encountered: List[str]
+    start_time: Optional[str] = None
+    end_time: Optional[str] = None
+    total_tokens_estimate: int = 0
+    user_messages: int = 0
+    assistant_messages: int = 0
+    tool_outputs: int = 0
+
+
+def parse_jsonl_session(file_path: str) -> SessionSummary:
+    """
+    Parse a Hermes session JSONL transcript and extract structured data.
+    
+    Args:
+        file_path: Path to the JSONL session file
+        
+    Returns:
+        SessionSummary with extracted data
+    """
+    session_id = Path(file_path).stem
+    messages = []
+    model = "unknown"
+    repo = "unknown"
+    tool_calls_count = 0
+    key_actions = []
+    errors = []
+    start_time = None
+    end_time = None
+    total_tokens = 0
+    
+    # Common repo patterns to look for
+    repo_patterns = [
+        r"(?:the-nexus|compounding-intelligence|timmy-config|hermes-agent)",
+        r"(?:forge\.alexanderwhitestone\.com/([^/]+/[^/\\s]+))",
+        r"(?:github\.com/([^/]+/[^/\\s]+))",
+        r"(?:Timmy_Foundation/([^/\\s]+))",
+    ]
+    
+    # Read JSONL file
+    try:
+        with open(file_path, 'r', encoding='utf-8') as f:
+            for line_num, line in enumerate(f, 1):
+                line = line.strip()
+                if not line:
+                    continue
+                
+                try:
+                    entry = json.loads(line)
+                except json.JSONDecodeError as e:
+                    errors.append(f"Line {line_num}: Invalid JSON - {e}")
+                    continue
+                
+                messages.append(entry)
+                
+                # Extract model from assistant messages
+                if entry.get("role") == "assistant" and entry.get("model"):
+                    model = entry["model"]
+                
+                # Extract timestamps
+                if entry.get("timestamp"):
+                    ts = entry["timestamp"]
+                    if start_time is None:
+                        start_time = ts
+                    end_time = ts
+                
+                # Count tool calls
+                if entry.get("tool_calls"):
+                    tool_calls_count += len(entry["tool_calls"])
+                    for tc in entry["tool_calls"]:
+                        if tc.get("function", {}).get("name"):
+                            action = f"{tc['function']['name']}"
+                            if action not in key_actions:
+                                key_actions.append(action)
+                
+                # Estimate tokens from content length
+                content = entry.get("content", "")
+                if isinstance(content, str):
+                    total_tokens += len(content.split())
+                elif isinstance(content, list):
+                    for item in content:
+                        if isinstance(item, dict) and "text" in item:
+                            total_tokens += len(item["text"].split())
+                
+                # Look for repo mentions in content
+                if entry.get("content"):
+                    content_str = str(entry["content"])
+                    for pattern in repo_patterns:
+                        match = re.search(pattern, content_str, re.IGNORECASE)
+                        if match:
+                            if match.groups():
+                                repo = match.group(1)
+                            else:
+                                repo = match.group(0)
+                            break
+                
+                # Look for error messages
+                if entry.get("role") == "tool" and entry.get("is_error"):
+                    error_msg = entry.get("content", "Unknown error")
+                    if isinstance(error_msg, str) and len(error_msg) < 200:
+                        errors.append(error_msg[:200])
+    
+    except FileNotFoundError:
+        return SessionSummary(
+            session_id=session_id,
+            model="unknown",
+            repo="unknown",
+            outcome="failure",
+            message_count=0,
+            tool_calls=0,
+            duration_estimate="0m",
+            key_actions=[],
+            errors_encountered=[f"File not found: {file_path}"]
+        )
+    
+    # Count message types
+    user_messages = sum(1 for m in messages if m.get("role") == "user")
+    assistant_messages = sum(1 for m in messages if m.get("role") == "assistant")
+    tool_outputs = sum(1 for m in messages if m.get("role") == "tool")
+    
+    # Calculate duration estimate
+    duration_estimate = "unknown"
+    if start_time and end_time:
+        try:
+            # Try to parse timestamps
+            start_dt = None
+            end_dt = None
+            
+            # Handle various timestamp formats
+            for fmt in ["%Y-%m-%dT%H:%M:%S.%fZ", "%Y-%m-%dT%H:%M:%SZ", "%Y-%m-%d %H:%M:%S"]:
+                try:
+                    if start_dt is None:
+                        start_dt = datetime.strptime(start_time, fmt)
+                    if end_dt is None:
+                        end_dt = datetime.strptime(end_time, fmt)
+                except ValueError:
+                    continue
+            
+            if start_dt and end_dt:
+                duration = end_dt - start_dt
+                minutes = duration.total_seconds() / 60
+                duration_estimate = f"{minutes:.0f}m"
+        except Exception:
+            pass
+    
+    # Classify outcome
+    outcome = "unknown"
+    if errors:
+        # Check if any errors are fatal
+        fatal_errors = any("405" in e or "permission" in e.lower() or "authentication" in e.lower() 
+                          for e in errors)
+        if fatal_errors:
+            outcome = "failure"
+        else:
+            outcome = "partial"
+    elif messages:
+        # Check last message for success indicators
+        last_msg = messages[-1]
+        if last_msg.get("role") == "assistant":
+            content = last_msg.get("content", "")
+            if isinstance(content, str):
+                success_indicators = ["done", "completed", "success", "merged", "pushed"]
+                if any(indicator in content.lower() for indicator in success_indicators):
+                    outcome = "success"
+                else:
+                    outcome = "unknown"
+    
+    # Deduplicate key actions (keep unique, limit to 10)
+    unique_actions = []
+    for action in key_actions:
+        if action not in unique_actions:
+            unique_actions.append(action)
+        if len(unique_actions) >= 10:
+            break
+    
+    # Deduplicate errors (keep unique, limit to 5)
+    unique_errors = []
+    for error in errors:
+        if error not in unique_errors:
+            unique_errors.append(error)
+        if len(unique_errors) >= 5:
+            break
+    
+    return SessionSummary(
+        session_id=session_id,
+        model=model,
+        repo=repo,
+        outcome=outcome,
+        message_count=len(messages),
+        tool_calls=tool_calls_count,
+        duration_estimate=duration_estimate,
+        key_actions=unique_actions,
+        errors_encountered=unique_errors,
+        start_time=start_time,
+        end_time=end_time,
+        total_tokens_estimate=total_tokens,
+        user_messages=user_messages,
+        assistant_messages=assistant_messages,
+        tool_outputs=tool_outputs
+    )
+
+
+def process_session_directory(directory_path: str, output_file: Optional[str] = None) -> List[SessionSummary]:
+    """
+    Process all JSONL files in a directory.
+    
+    Args:
+        directory_path: Path to directory containing session JSONL files
+        output_file: Optional path to write JSON output
+        
+    Returns:
+        List of SessionSummary objects
+    """
+    directory = Path(directory_path)
+    if not directory.exists():
+        print(f"Error: Directory {directory_path} does not exist", file=sys.stderr)
+        return []
+    
+    jsonl_files = list(directory.glob("session_*.jsonl"))
+    if not jsonl_files:
+        print(f"Warning: No session_*.jsonl files found in {directory_path}", file=sys.stderr)
+        return []
+    
+    summaries = []
+    for jsonl_file in sorted(jsonl_files):
+        print(f"Processing {jsonl_file.name}...", file=sys.stderr)
+        summary = parse_jsonl_session(str(jsonl_file))
+        summaries.append(summary)
+    
+    if output_file:
+        with open(output_file, 'w', encoding='utf-8') as f:
+            json.dump([asdict(s) for s in summaries], f, indent=2)
+        print(f"Wrote {len(summaries)} summaries to {output_file}", file=sys.stderr)
+    
+    return summaries
+
+
+def main():
+    """CLI entry point."""
+    import argparse
+    
+    parser = argparse.ArgumentParser(description="Parse Hermes session JSONL transcripts")
+    parser.add_argument("path", help="Path to JSONL file or directory of session files")
+    parser.add_argument("-o", "--output", help="Output JSON file (default: stdout)")
+    parser.add_argument("-v", "--verbose", action="store_true", help="Verbose output")
+    
+    args = parser.parse_args()
+    
+    path = Path(args.path)
+    
+    if path.is_file():
+        summary = parse_jsonl_session(str(path))
+        if args.output:
+            with open(args.output, 'w') as f:
+                json.dump(asdict(summary), f, indent=2)
+            print(f"Wrote summary to {args.output}", file=sys.stderr)
+        else:
+            print(json.dumps(asdict(summary), indent=2))
+    
+    elif path.is_dir():
+        summaries = process_session_directory(str(path), args.output)
+        if not args.output:
+            print(json.dumps([asdict(s) for s in summaries], indent=2))
+    
+    else:
+        print(f"Error: {args.path} is not a file or directory", file=sys.stderr)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

scripts/test_harvest_prompt_comprehensive.py

@@ -1,212 +0,0 @@
-#!/usr/bin/env python3
-"""
-Comprehensive test script for knowledge extraction prompt.
-Validates prompt structure, requirements, and consistency.
-"""
-
-import json
-import re
-from pathlib import Path
-
-def test_prompt_structure():
-    """Test that the prompt has the required structure."""
-    prompt_path = Path("templates/harvest-prompt.md")
-    if not prompt_path.exists():
-        return False, "harvest-prompt.md not found"
-    
-    content = prompt_path.read_text()
-    
-    # Check for required sections
-    required_sections = [
-        "System Prompt",
-        "Instructions", 
-        "Categories",
-        "Output Format",
-        "Confidence Scoring",
-        "Constraints",
-        "Example"
-    ]
-    
-    for section in required_sections:
-        if section.lower() not in content.lower():
-            return False, f"Missing required section: {section}"
-    
-    # Check for required categories
-    required_categories = ["fact", "pitfall", "pattern", "tool-quirk", "question"]
-    for category in required_categories:
-        if category not in content:
-            return False, f"Missing required category: {category}"
-    
-    # Check for required output fields
-    required_fields = ["fact", "category", "repo", "confidence"]
-    for field in required_fields:
-        if field not in content:
-            return False, f"Missing required output field: {field}"
-    
-    # Check prompt size (should be ~1k tokens, roughly 4k chars)
-    if len(content) > 5000:
-        return False, f"Prompt too large: {len(content)} chars (max ~5000)"
-    
-    if len(content) < 1000:
-        return False, f"Prompt too small: {len(content)} chars (min ~1000)"
-    
-    return True, "Prompt structure is valid"
-
-def test_confidence_scoring():
-    """Test that confidence scoring is properly defined."""
-    prompt_path = Path("templates/harvest-prompt.md")
-    content = prompt_path.read_text()
-    
-    # Check for confidence scale definitions
-    confidence_levels = [
-        ("0.9-1.0", "explicitly stated"),
-        ("0.7-0.8", "clearly implied"),
-        ("0.5-0.6", "suggested"),
-        ("0.3-0.4", "inferred"),
-        ("0.1-0.2", "speculative")
-    ]
-    
-    for level, description in confidence_levels:
-        if level not in content:
-            return False, f"Missing confidence level: {level}"
-        if description.lower() not in content.lower():
-            return False, f"Missing confidence description: {description}"
-    
-    return True, "Confidence scoring is properly defined"
-
-def test_example_quality():
-    """Test that examples are clear and complete."""
-    prompt_path = Path("templates/harvest-prompt.md")
-    content = prompt_path.read_text()
-    
-    # Check for example input/output
-    if "example" not in content.lower():
-        return False, "No examples provided"
-    
-    # Check that example includes all categories
-    example_section = content[content.lower().find("example"):]
-    
-    # Look for JSON example
-    json_match = re.search(r'\{[\s\S]*"knowledge"[\s\S]*\}', example_section)
-    if not json_match:
-        return False, "No JSON example found"
-    
-    example_json = json_match.group(0)
-    
-    # Check for all categories in example
-    for category in ["fact", "pitfall", "pattern", "tool-quirk", "question"]:
-        if category not in example_json:
-            return False, f"Example missing category: {category}"
-    
-    return True, "Examples are clear and complete"
-
-def test_constraint_coverage():
-    """Test that constraints cover all requirements."""
-    prompt_path = Path("templates/harvest-prompt.md")
-    content = prompt_path.read_text()
-    
-    required_constraints = [
-        "No hallucination",
-        "only extract",
-        "explicitly",
-        "partial",
-        "failed sessions",
-        "1k tokens"
-    ]
-    
-    for constraint in required_constraints:
-        if constraint.lower() not in content.lower():
-            return False, f"Missing constraint: {constraint}"
-    
-    return True, "Constraints cover all requirements"
-
-def test_test_sessions():
-    """Test that test sessions exist and are valid."""
-    test_sessions_dir = Path("test_sessions")
-    if not test_sessions_dir.exists():
-        return False, "test_sessions directory not found"
-    
-    session_files = list(test_sessions_dir.glob("*.jsonl"))
-    if len(session_files) < 5:
-        return False, f"Only {len(session_files)} test sessions found, need 5"
-    
-    # Check each session file
-    for session_file in session_files:
-        content = session_file.read_text()
-        lines = content.strip().split("\n")
-        
-        # Check that each line is valid JSON
-        for i, line in enumerate(lines, 1):
-            try:
-                json.loads(line)
-            except json.JSONDecodeError as e:
-                return False, f"Invalid JSON in {session_file.name}, line {i}: {e}"
-    
-    return True, f"Found {len(session_files)} valid test sessions"
-
-def run_all_tests():
-    """Run all tests and return results."""
-    tests = [
-        ("Prompt Structure", test_prompt_structure),
-        ("Confidence Scoring", test_confidence_scoring),
-        ("Example Quality", test_example_quality),
-        ("Constraint Coverage", test_constraint_coverage),
-        ("Test Sessions", test_test_sessions)
-    ]
-    
-    results = []
-    all_passed = True
-    
-    for test_name, test_func in tests:
-        try:
-            passed, message = test_func()
-            results.append({
-                "test": test_name,
-                "passed": passed,
-                "message": message
-            })
-            if not passed:
-                all_passed = False
-        except Exception as e:
-            results.append({
-                "test": test_name,
-                "passed": False,
-                "message": f"Error: {str(e)}"
-            })
-            all_passed = False
-    
-    # Print results
-    print("=" * 60)
-    print("HARVEST PROMPT TEST RESULTS")
-    print("=" * 60)
-    
-    for result in results:
-        status = "✓ PASS" if result["passed"] else "✗ FAIL"
-        print(f"{status}: {result['test']}")
-        print(f"  {result['message']}")
-        print()
-    
-    print("=" * 60)
-    if all_passed:
-        print("ALL TESTS PASSED!")
-    else:
-        print("SOME TESTS FAILED!")
-    print("=" * 60)
-    
-    return all_passed, results
-
-if __name__ == "__main__":
-    all_passed, results = run_all_tests()
-    
-    # Save results to file
-    with open("test_results.json", "w") as f:
-        json.dump({
-            "all_passed": all_passed,
-            "results": results,
-            "timestamp": "2026-04-14T19:05:00Z"
-        }, f, indent=2)
-    
-    print(f"Results saved to test_results.json")
-    
-    # Exit with appropriate code
-    exit(0 if all_passed else 1)

test_sessions/session_failure.jsonl

@@ -1,18 +0,0 @@
-{"role": "user", "content": "Deploy the application to production"}
-{"role": "assistant", "content": "I'll deploy the application to production.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ssh deploy@prod-server 'cd /app && git pull && docker-compose up -d'"}}]}
-{"role": "tool", "content": "ssh: connect to host prod-server port 22: Connection refused"}
-{"role": "assistant", "content": "Connection refused. Let me check the server status.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ping -c 3 prod-server"}}]}
-{"role": "tool", "content": "PING prod-server (192.168.1.100): 56 data bytes\nRequest timeout for icmp_seq 0\nRequest timeout for icmp_seq 1\nRequest timeout for icmp_seq 2\n--- prod-server ping statistics ---\n3 packets transmitted, 0 packets received, 100.0% packet loss"}
-{"role": "assistant", "content": "The server appears to be down. Let me check if there's an alternative deployment method."}
-{"role": "user", "content": "Try using the VPS instead"}
-{"role": "assistant", "content": "I'll try deploying to the VPS.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ssh deploy@vps-server 'cd /app && git pull && docker-compose up -d'"}}]}
-{"role": "tool", "content": "Permission denied (publickey)."}
-{"role": "assistant", "content": "Permission denied. The SSH key might not be set up correctly. Let me check the SSH configuration.", "tool_calls": [{"function": "terminal", "arguments": {"command": "cat ~/.ssh/config"}}]}
-{"role": "tool", "content": "Host vps-server\n    HostName 167.99.126.228\n    User deploy\n    IdentityFile ~/.ssh/id_rsa_vps"}
-{"role": "assistant", "content": "The SSH config looks correct. Let me check if the key exists.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ls -la ~/.ssh/id_rsa_vps"}}]}
-{"role": "tool", "content": "ls: /Users/user/.ssh/id_rsa_vps: No such file or directory"}
-{"role": "assistant", "content": "The SSH key doesn't exist. This is a pitfall - we need to generate the SSH key first."}
-{"role": "user", "content": "Generate a new SSH key for the VPS"}
-{"role": "assistant", "content": "I'll generate a new SSH key.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ssh-keygen -t rsa -b 4096 -f ~/.ssh/id_rsa_vps -N ''"}}]}
-{"role": "tool", "content": "Generating public/private rsa key pair.\nYour identification has been saved in /Users/user/.ssh/id_rsa_vps\nYour public key has been saved in /Users/user/.ssh/id_rsa_vps.pub\nThe key fingerprint is:\nSHA256:abc123... user@machine"}
-{"role": "assistant", "content": "SSH key generated. Now I need to add it to the VPS."}

test_sessions/session_partial.jsonl

@@ -1,14 +0,0 @@
-{"role": "user", "content": "Check the Gitea API for open issues"}
-{"role": "assistant", "content": "I'll check the Gitea API for open issues.", "tool_calls": [{"function": "terminal", "arguments": {"command": "curl -H 'Authorization: token $GITEA_TOKEN' https://forge.alexanderwhitestone.com/api/v1/repos/Timmy_Foundation/compounding-intelligence/issues?state=open"}}]}
-{"role": "tool", "content": "curl: (6) Could not resolve host: forge.alexanderwhitestone.com"}
-{"role": "assistant", "content": "DNS resolution failed. Let me check the network connectivity.", "tool_calls": [{"function": "terminal", "arguments": {"command": "nslookup forge.alexanderwhitestone.com"}}]}
-{"role": "tool", "content": "Server:		8.8.8.8\nAddress:	8.8.8.8#53\n\n** server can't find forge.alexanderwhitestone.com: NXDOMAIN"}
-{"role": "assistant", "content": "The domain doesn't resolve. This might be a DNS issue. Let me try using the IP address directly.", "tool_calls": [{"function": "terminal", "arguments": {"command": "curl -H 'Authorization: token $GITEA_TOKEN' https://167.99.126.228/api/v1/repos/Timmy_Foundation/compounding-intelligence/issues?state=open"}}]}
-{"role": "tool", "content": "curl: (60) SSL certificate problem: self signed certificate"}
-{"role": "assistant", "content": "SSL certificate issue. The server is using a self-signed certificate. Let me try with -k flag to skip SSL verification.", "tool_calls": [{"function": "terminal", "arguments": {"command": "curl -k -H 'Authorization: token $GITEA_TOKEN' https://167.99.126.228/api/v1/repos/Timmy_Foundation/compounding-intelligence/issues?state=open"}}]}
-{"role": "tool", "content": "[]"}
-{"role": "assistant", "content": "No open issues found. The API returned an empty array."}
-{"role": "user", "content": "Check if there are any pull requests"}
-{"role": "assistant", "content": "Let me check for pull requests.", "tool_calls": [{"function": "terminal", "arguments": {"command": "curl -k -H 'Authorization: token $GITEA_TOKEN' https://167.99.126.228/api/v1/repos/Timmy_Foundation/compounding-intelligence/pulls?state=open"}}]}
-{"role": "tool", "content": "[{"id": 20, "title": "feat: add harvester.py + session_reader.py — session knowledge extractor (closes #8)", "state": "open", "user": {"login": "Rockachopa"}, "created_at": "2026-04-14T17:28:20Z"}]"}
-{"role": "assistant", "content": "Found 1 open pull request: PR #20 - "feat: add harvester.py + session_reader.py — session knowledge extractor (closes #8)" by Rockachopa."}

test_sessions/session_patterns.jsonl

@@ -1,10 +0,0 @@
-{"role": "user", "content": "How do I deploy a new version of the application?"}
-{"role": "assistant", "content": "Here's the deployment process:\n1. Run tests: pytest\n2. Build Docker image: docker build -t app:latest .\n3. Push to registry: docker push registry.example.com/app:latest\n4. Update production: ssh prod 'cd /app && docker-compose pull && docker-compose up -d'\n5. Verify: curl https://app.example.com/health"}
-{"role": "user", "content": "What if tests fail?"}
-{"role": "assistant", "content": "If tests fail:\n1. Check the error logs: pytest -v\n2. Fix the failing tests\n3. Re-run tests: pytest\n4. If still failing, check recent changes: git log --oneline -10\n5. Consider reverting: git revert HEAD"}
-{"role": "user", "content": "What if the Docker build fails?"}
-{"role": "assistant", "content": "If Docker build fails:\n1. Check Dockerfile syntax: docker build --no-cache -t app:latest .\n2. Check for missing dependencies: cat requirements.txt\n3. Check disk space: df -h\n4. Clean up Docker: docker system prune -f\n5. Try building with verbose output: docker build --progress=plain -t app:latest ."}
-{"role": "user", "content": "What if the push to registry fails?"}
-{"role": "assistant", "content": "If push to registry fails:\n1. Check registry credentials: docker login registry.example.com\n2. Check registry space: curl https://registry.example.com/v2/_catalog\n3. Check image size: docker images app:latest\n4. Try tagging with version: docker tag app:latest registry.example.com/app:v1.0.0\n5. Push with version tag: docker push registry.example.com/app:v1.0.0"}
-{"role": "user", "content": "What if the production update fails?"}
-{"role": "assistant", "content": "If production update fails:\n1. Check SSH connection: ssh prod 'echo connected'\n2. Check disk space on prod: ssh prod 'df -h'\n3. Check Docker status: ssh prod 'docker ps -a'\n4. Check logs: ssh prod 'docker-compose logs --tail=100'\n5. Rollback: ssh prod 'cd /app && git checkout HEAD~1 && docker-compose up -d'"}

test_sessions/session_questions.jsonl

@@ -1,12 +0,0 @@
-{"role": "user", "content": "I need to implement a new feature for the application"}
-{"role": "assistant", "content": "I can help you implement a new feature. What feature would you like to add?"}
-{"role": "user", "content": "I want to add user authentication"}
-{"role": "assistant", "content": "User authentication is a good feature. I have a few questions:\n1. What authentication method do you prefer? (JWT, OAuth, Session-based)\n2. Do you need social login? (Google, GitHub, etc.)\n3. What user data do you need to store?\n4. Do you need role-based access control?\n5. What's your database? (PostgreSQL, MySQL, SQLite)"}
-{"role": "user", "content": "I prefer JWT, no social login, just email and password, no roles, PostgreSQL"}
-{"role": "assistant", "content": "Great choices. Here's the implementation plan:\n1. Create user model with email and password hash\n2. Create JWT token generation and validation\n3. Create login endpoint: POST /api/auth/login\n4. Create register endpoint: POST /api/auth/register\n5. Create middleware for protected routes\n6. Add password hashing with bcrypt\n7. Add rate limiting for login attempts\n8. Add password reset functionality\n9. Add email verification\n10. Test all endpoints"}
-{"role": "user", "content": "What about password reset?"}
-{"role": "assistant", "content": "For password reset:\n1. Create reset token table\n2. Create forgot password endpoint: POST /api/auth/forgot-password\n3. Send reset email with token\n4. Create reset password endpoint: POST /api/auth/reset-password\n5. Validate reset token and expiration\n6. Update password and delete token\n7. Send confirmation email"}
-{"role": "user", "content": "What about email verification?"}
-{"role": "assistant", "content": "For email verification:\n1. Add email_verified field to user model\n2. Create verification token table\n3. Send verification email on registration\n4. Create verify email endpoint: GET /api/auth/verify-email?token=...\n5. Validate token and update email_verified\n6. Add middleware to check email_verified for certain routes\n7. Add resend verification email endpoint"}
-{"role": "user", "content": "What about rate limiting?"}
-{"role": "assistant", "content": "For rate limiting:\n1. Use Redis for rate limit storage\n2. Create rate limit middleware\n3. Set limits: 5 login attempts per minute, 3 password resets per hour\n4. Return 429 Too Many Requests when limit exceeded\n5. Add X-RateLimit headers to responses\n6. Log rate limit violations\n7. Add whitelist for trusted IPs"}

test_sessions/session_success.jsonl

@@ -1,13 +0,0 @@
-{"role": "user", "content": "Clone the repo at forge.alexanderwhitestone.com/Timmy_Foundation/compounding-intelligence"}
-{"role": "assistant", "content": "I'll clone the repository for you.", "tool_calls": [{"function": "terminal", "arguments": {"command": "git clone https://forge.alexanderwhitestone.com/Timmy_Foundation/compounding-intelligence.git"}}]}
-{"role": "tool", "content": "Cloning into 'compounding-intelligence'...\nremote: Enumerating objects: 15, done.\nremote: Counting objects: 100% (15/15), done.\nremote: Compressing objects: 100% (12/12), done.\nremote: Total 15 (delta 2), reused 0 (delta 0), pack-reused 0\nReceiving objects: 100% (15/15), done.\nResolving deltas: 100% (2/2), done."}
-{"role": "assistant", "content": "Repository cloned successfully. Let me check the structure.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ls -la compounding-intelligence/"}}]}
-{"role": "tool", "content": "total 8\ndrwxr-xr-x   5 user  staff  160 Apr 14 17:21 .\ndrwxr-xr-x  12 user  staff  384 Apr 14 17:21 ..\ndrwxr-xr-x  13 user  staff  416 Apr 14 17:21 .git\n-rw-r--r--   1 user  staff  1234 Apr 14 17:21 README.md\ndrwxr-xr-x   3 user  staff   96 Apr 14 17:21 knowledge\n-rw-r--r--   1 user  staff   456 Apr 14 17:21 metrics\ndrwxr-xr-x   4 user  staff  128 Apr 14 17:21 scripts\ndrwxr-xr-x   3 user  staff   96 Apr 14 17:21 templates"}
-{"role": "user", "content": "What files are in the templates directory?"}
-{"role": "assistant", "content": "Let me check the templates directory.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ls -la compounding-intelligence/templates/"}}]}
-{"role": "tool", "content": "total 0\ndrwxr-xr-x  3 user  staff   96 Apr 14 17:21 .\ndrwxr-xr-x  5 user  staff  160 Apr 14 17:21 ..\n-rw-r--r--  1 user  staff    0 Apr 14 17:21 .gitkeep"}
-{"role": "assistant", "content": "The templates directory currently only contains a .gitkeep file. No templates have been added yet."}
-{"role": "user", "content": "Create a harvest-prompt.md template in the templates directory."}
-{"role": "assistant", "content": "I'll create the harvest-prompt.md template for you.", "tool_calls": [{"function": "terminal", "arguments": {"command": "cat > compounding-intelligence/templates/harvest-prompt.md << 'EOF'\n# Knowledge Extraction Prompt\n\nExtract knowledge from session transcripts.\nEOF"}}]}
-{"role": "tool", "content": ""}
-{"role": "assistant", "content": "Template created successfully. The harvest-prompt.md file is now in the templates directory."}