feat: add API Doc Generator — issue #98

- scripts/api_doc_generator.py: AST-based scanner for scripts/ Python modules
- docs/API.md: generated API reference (33 modules, ~500 lines)
- tests/test_api_doc_generator.py: 12 smoke tests (all passing)

The generator extracts module docstrings and public function signatures (name, args, summary) and produces a markdown table per script. One consolidated document per repo (docs/API.md).

Closes #98

docs/API.md

@@ -0,0 +1,472 @@
+# Compounding Intelligence — Scripts API Reference
+
+*Generated: 2026-04-26 11:02 UTC*
+
+This document auto-documents the public API surface of all scripts
+in `scripts/`. Each section covers one script: module purpose,
+public functions, and their signatures.
+
+---
+
+## `scripts/api_doc_generator.py`
+
+API Doc Generator — Issue #98
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `extract_functions_from_ast` | `extract_functions_from_ast(tree, file_rel)` | Extract public function names, signatures, and first-line doc summaries. |
+| `parse_module` | `parse_module(filepath)` | Parse a Python file and return its module-level docstring and public functions. |
+| `scan_scripts_dir` | `scan_scripts_dir(scripts_dir)` | Scan all .py files in scripts/ and extract API info. |
+| `render_markdown` | `render_markdown(modules)` | Generate full docs/API.md content from the scanned modules. |
+| `render_json` | `render_json(modules)` | Emit machine-readable JSON version of the API reference. |
+| `main` | `main()` | - |
+
+## `scripts/automation_opportunity_finder.py`
+
+Automation Opportunity Finder — Scan fleet for manual processes that could be automated.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `analyze_cron_jobs` | `analyze_cron_jobs(hermes_home)` | Analyze cron job definitions for automation gaps. |
+| `analyze_documents` | `analyze_documents(root_dirs)` | Scan documentation for manual step patterns. |
+| `analyze_scripts` | `analyze_scripts(root_dirs)` | Detect repeated command sequences in scripts. |
+| `analyze_session_transcripts` | `analyze_session_transcripts(session_dirs)` | Find repeated tool-call patterns in session transcripts. |
+| `analyze_shell_history` | `analyze_shell_history(root_dirs)` | Find repeated shell commands from history files. |
+| `deduplicate_proposals` | `deduplicate_proposals(proposals)` | Remove duplicate proposals based on title similarity. |
+| `rank_proposals` | `rank_proposals(proposals)` | Sort proposals by impact * confidence (highest first). |
+| `format_text_report` | `format_text_report(proposals)` | Format proposals as human-readable text. |
+| `main` | `main()` | - |
+
+## `scripts/bootstrapper.py`
+
+Bootstrapper — assemble pre-session context from knowledge store.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `load_index` | `load_index(index_path)` | Load and validate the knowledge index. |
+| `filter_facts` | `filter_facts(facts, repo, agent, include_global)` | Filter facts by repo, agent, and global scope. |
+| `sort_facts` | `sort_facts(facts)` | Sort facts by: confidence (desc), then category priority, then fact text. |
+| `load_repo_knowledge` | `load_repo_knowledge(repo)` | Load per-repo knowledge markdown if it exists. |
+| `load_agent_knowledge` | `load_agent_knowledge(agent)` | Load per-agent knowledge markdown if it exists. |
+| `load_global_knowledge` | `load_global_knowledge()` | Load all global knowledge markdown files. |
+| `render_facts_section` | `render_facts_section(facts, category, label)` | Render a section of facts for a single category. |
+| `estimate_tokens` | `estimate_tokens(text)` | Rough token estimate. |
+| `truncate_to_tokens` | `truncate_to_tokens(text, max_tokens)` | Truncate text to approximately max_tokens, cutting at line boundaries. |
+| `build_bootstrap_context` | `build_bootstrap_context(repo, agent, include_global, max_tokens, index_path)` | Build the full bootstrap context block. |
+| `main` | `main()` | - |
+
+## `scripts/dead_code_detector.py`
+
+Dead Code Detector for Python Codebases
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `is_safe_unused` | `is_safe_unused(name, filepath)` | Check if an unused name is expected to be unused. |
+| `get_git_blame` | `get_git_blame(filepath, lineno)` | Get last author of a line via git blame. |
+| `analyze_file` | `analyze_file(filepath)` | Analyze a single Python file for dead code. |
+| `scan_repo` | `scan_repo(repo_path, exclude_patterns)` | Scan an entire repo for dead code. |
+| `main` | `main()` | - |
+
+## `scripts/dedup.py`
+
+dedup.py — Knowledge deduplication: content hash + semantic similarity.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `normalize_text` | `normalize_text(text)` | Normalize text for hashing: lowercase, collapse whitespace, strip. |
+| `content_hash` | `content_hash(text)` | SHA256 hash of normalized text for exact dedup. |
+| `tokenize` | `tokenize(text)` | Simple tokenizer: lowercase words, 3+ chars. |
+| `token_similarity` | `token_similarity(a, b)` | Token-based Jaccard similarity (0.0-1.0). |
+| `quality_score` | `quality_score(fact)` | Compute quality score for merge ranking. |
+| `merge_facts` | `merge_facts(keep, drop)` | Merge two near-duplicate facts, keeping higher-quality fields. |
+| `dedup_facts` | `dedup_facts(facts, exact_threshold, near_threshold, dry_run)` | Deduplicate a list of knowledge facts. |
+| `dedup_index_file` | `dedup_index_file(input_path, output_path, near_threshold, dry_run)` | Deduplicate an index.json file. |
+| `generate_test_duplicates` | `generate_test_duplicates(n)` | Generate test facts with intentional duplicates for testing. |
+| `main` | `main()` | - |
+
+## `scripts/dependency_graph.py`
+
+Cross-Repo Dependency Graph Builder
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `normalize_repo_name` | `normalize_repo_name(name)` | Normalize a repo name for comparison. |
+| `scan_file_for_deps` | `scan_file_for_deps(filepath, content, own_repo)` | Scan a file's content for references to other repos. |
+| `scan_repo` | `scan_repo(repo_path, repo_name)` | Scan a repo directory for dependencies. |
+| `detect_cycles` | `detect_cycles(graph)` | Detect circular dependencies using DFS. |
+| `to_dot` | `to_dot(graph)` | Generate DOT format output. |
+| `to_mermaid` | `to_mermaid(graph)` | Generate Mermaid format output. |
+| `main` | `main()` | - |
+
+## `scripts/diff_analyzer.py`
+
+Diff Analyzer — Parse unified diffs and categorize every change.
+
+*(no public functions — script runs as `main()` only)*
+
+## `scripts/freshness.py`
+
+Knowledge Freshness Cron — Detect stale entries from code changes (Issue #200)
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `compute_file_hash` | `compute_file_hash(filepath)` | Compute SHA-256 hash of a file. Returns None if file doesn't exist. |
+| `get_git_file_changes` | `get_git_file_changes(repo_path, days)` | Get files changed in git in the last N days. |
+| `load_knowledge_entries` | `load_knowledge_entries(knowledge_dir)` | Load knowledge entries from YAML files in the knowledge directory. |
+| `check_freshness` | `check_freshness(knowledge_dir, repo_root, days)` | Check freshness of knowledge entries against recent code changes. |
+| `update_stale_hashes` | `update_stale_hashes(knowledge_dir, repo_root)` | Update hashes for stale entries. Returns count of updated entries. |
+| `format_report` | `format_report(result, max_items)` | Format freshness check results as a human-readable report. |
+| `main` | `main()` | - |
+
+## `scripts/gitea_issue_parser.py`
+
+Gitea Issue Body Parser — Extract structured data from markdown issue bodies.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `parse_issue_body` | `parse_issue_body(body, title, labels)` | Parse a Gitea issue markdown body into structured JSON. |
+| `fetch_issue_from_url` | `fetch_issue_from_url(url)` | Fetch an issue from a Gitea API URL and parse it. |
+| `main` | `main()` | - |
+
+## `scripts/harvester.py`
+
+harvester.py — Extract durable knowledge from Hermes session transcripts.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `find_api_key` | `find_api_key()` | Find API key from common locations. |
+| `load_extraction_prompt` | `load_extraction_prompt()` | Load the extraction prompt template. |
+| `call_llm` | `call_llm(prompt, transcript, api_base, api_key, model)` | Call the LLM API to extract knowledge from a transcript. |
+| `parse_extraction_response` | `parse_extraction_response(content)` | Parse the LLM response to extract knowledge items. |
+| `load_existing_knowledge` | `load_existing_knowledge(knowledge_dir)` | Load the existing knowledge index. |
+| `fact_fingerprint` | `fact_fingerprint(fact)` | Generate a deduplication fingerprint for a fact. |
+| `deduplicate` | `deduplicate(new_facts, existing, similarity_threshold)` | Remove duplicate facts from new_facts that already exist in the knowledge store. |
+| `validate_fact` | `validate_fact(fact)` | Validate a single knowledge item has required fields. |
+| `write_knowledge` | `write_knowledge(index, new_facts, knowledge_dir, source_session)` | Write new facts to the knowledge store. |
+| `harvest_session` | `harvest_session(session_path, knowledge_dir, api_base, api_key, model, dry_run, min_confidence)` | Harvest knowledge from a single session. |
+| `batch_harvest` | `batch_harvest(sessions_dir, knowledge_dir, api_base, api_key, model, since, limit, dry_run)` | Harvest knowledge from multiple sessions in batch. |
+| `main` | `main()` | - |
+
+## `scripts/improvement_proposals.py`
+
+Improvement Proposal Generator for compounding-intelligence.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `analyze_sessions` | `analyze_sessions(sessions)` | Analyze session data to find waste patterns. |
+| `generate_proposals` | `generate_proposals(patterns, hourly_rate, implementation_overhead)` | Generate improvement proposals from waste patterns. |
+| `format_proposals_markdown` | `format_proposals_markdown(proposals, patterns, generated_at)` | Format proposals as a markdown document. |
+| `format_proposals_json` | `format_proposals_json(proposals)` | Format proposals as JSON. |
+| `main` | `main()` | - |
+
+## `scripts/knowledge_gap_identifier.py`
+
+Knowledge Gap Identifier — Pipeline 10.7
+
+*(no public functions — script runs as `main()` only)*
+
+## `scripts/knowledge_staleness_check.py`
+
+Knowledge Store Staleness Detector — Detect stale knowledge entries by comparing source file hashes.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `compute_file_hash` | `compute_file_hash(filepath)` | Compute SHA-256 hash of a file. Returns None if file doesn't exist. |
+| `check_staleness` | `check_staleness(index_path, repo_root)` | Check all entries in knowledge index for staleness. |
+| `fix_hashes` | `fix_hashes(index_path, repo_root)` | Add hashes to entries missing them. Returns count of fixed entries. |
+| `main` | `main()` | - |
+
+## `scripts/perf_bottleneck_finder.py`
+
+Performance Bottleneck Finder — Identify slow tests, builds, and CI steps.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `find_slow_tests_pytest` | `find_slow_tests_pytest(repo_path)` | Run pytest --durations and parse slow tests. |
+| `find_slow_tests_by_scan` | `find_slow_tests_by_scan(repo_path)` | Scan test files for patterns that indicate slow tests. |
+| `analyze_build_artifacts` | `analyze_build_artifacts(repo_path)` | Find large build artifacts that slow down builds. |
+| `analyze_makefile_targets` | `analyze_makefile_targets(repo_path)` | Analyze Makefile for potentially slow targets. |
+| `analyze_github_actions` | `analyze_github_actions(repo_path)` | Analyze GitHub Actions workflow files for inefficiencies. |
+| `analyze_gitea_ci` | `analyze_gitea_ci(repo_path)` | Analyze Gitea/Drone CI config files. |
+| `find_slow_imports` | `find_slow_imports(repo_path)` | Find Python files with heavy import chains. |
+| `severity_sort_key` | `severity_sort_key(b)` | Sort by severity then duration. |
+| `generate_report` | `generate_report(repo_path)` | Run all analyses and generate a performance report. |
+| `format_markdown` | `format_markdown(report)` | Format report as markdown. |
+| `main` | `main()` | - |
+
+## `scripts/priority_rebalancer.py`
+
+Priority Rebalancer — Re-evaluate issue priorities based on accumulated data.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `collect_knowledge_signals` | `collect_knowledge_signals(knowledge_dir)` | Analyze knowledge store for coverage gaps and staleness. |
+| `collect_staleness_signals` | `collect_staleness_signals(scripts_dir, knowledge_dir)` | Run staleness checker if available. |
+| `collect_metrics_signals` | `collect_metrics_signals(metrics_dir)` | Analyze metrics directory for pipeline health. |
+| `extract_priority` | `extract_priority(labels)` | Extract priority level from issue labels. |
+| `compute_issue_score` | `compute_issue_score(issue, repo, signals, now)` | Compute priority score for a single issue. |
+| `generate_report` | `generate_report(scores, signals, org, repos_scanned)` | Generate the full priority report. |
+| `generate_markdown_report` | `generate_markdown_report(report)` | Generate human-readable markdown report. |
+| `main` | `main()` | - |
+
+## `scripts/refactoring_opportunity_finder.py`
+
+Finds refactoring opportunities in codebases
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `compute_file_complexity` | `compute_file_complexity(filepath)` | Compute cyclomatic complexity for a Python file. |
+| `calculate_refactoring_score` | `calculate_refactoring_score(metrics)` | Calculate a refactoring priority score (0-100) based on file metrics. |
+| `scan_directory` | `scan_directory(directory, extensions)` | Scan directory for source files. |
+| `generate_proposals` | `generate_proposals(directory, min_score)` | Generate refactoring proposals by analyzing source files. |
+| `main` | `main()` | - |
+
+## `scripts/sampler.py`
+
+sampler.py — Score and rank sessions by harvest value.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `scan_session_fast` | `scan_session_fast(path)` | Extract scoring metadata from a session without parsing the full JSONL. |
+| `parse_session_timestamp` | `parse_session_timestamp(filename)` | Parse timestamp from session filename. |
+| `score_session` | `score_session(meta, now, seen_repos)` | Score a session for harvest value. Returns (score, breakdown). |
+| `main` | `main()` | - |
+
+## `scripts/session_metadata.py`
+
+session_metadata.py - Extract structured metadata from Hermes session transcripts.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `extract_session_metadata` | `extract_session_metadata(file_path)` | Extract structured metadata from a Hermes session JSONL transcript. |
+| `process_session_directory` | `process_session_directory(directory_path, output_file)` | Process all JSONL files in a directory. |
+| `main` | `main()` | CLI entry point. |
+
+## `scripts/session_pair_harvester.py`
+
+Session Transcript → Training Pair Harvester
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `compute_hash` | `compute_hash(text)` | Content hash for deduplication. |
+| `extract_pairs_from_session` | `extract_pairs_from_session(session_data, min_ratio, min_response_words)` | Extract terse→rich pairs from a single session object. |
+| `extract_from_jsonl_file` | `extract_from_jsonl_file(filepath, **kwargs)` | Extract pairs from a session JSONL file. |
+| `deduplicate_pairs` | `deduplicate_pairs(pairs)` | Remove duplicate pairs across files. |
+| `main` | `main()` | - |
+
+## `scripts/session_reader.py`
+
+session_reader.py — Parse Hermes session JSONL transcripts.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `read_session` | `read_session(path)` | Read a session JSONL file and return all messages as a list. |
+| `read_session_iter` | `read_session_iter(path)` | Iterate over session messages without loading all into memory. |
+| `extract_conversation` | `extract_conversation(messages)` | Extract user/assistant conversation turns, skipping tool-only messages. |
+| `truncate_for_context` | `truncate_for_context(messages, head, tail)` | Truncate long sessions: keep first N + last N messages. |
+| `messages_to_text` | `messages_to_text(messages)` | Convert message list to plain text for LLM consumption. |
+| `get_session_metadata` | `get_session_metadata(path)` | Extract metadata from a session file (first message often has config info). |
+
+## `scripts/test_automation_opportunity_finder.py`
+
+Tests for scripts/automation_opportunity_finder.py — 8 tests.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `test_analyze_cron_jobs_no_file` | `test_analyze_cron_jobs_no_file()` | Returns empty list when no cron jobs file exists. |
+| `test_analyze_cron_jobs_disabled` | `test_analyze_cron_jobs_disabled()` | Detects disabled cron jobs. |
+| `test_analyze_cron_jobs_errors` | `test_analyze_cron_jobs_errors()` | Detects cron jobs with error status. |
+| `test_analyze_documents_finds_todos` | `test_analyze_documents_finds_todos()` | Detects TODO markers in documents. |
+| `test_analyze_scripts_repeated_commands` | `test_analyze_scripts_repeated_commands()` | Detects repeated shell commands across scripts. |
+| `test_analyze_session_transcripts` | `test_analyze_session_transcripts()` | Detects repeated tool-call sequences. |
+| `test_deduplicate_proposals` | `test_deduplicate_proposals()` | Deduplicates proposals with similar titles. |
+| `test_rank_proposals` | `test_rank_proposals()` | Ranks proposals by impact * confidence. |
+
+## `scripts/test_bootstrapper.py`
+
+Tests for bootstrapper.py — context assembly from knowledge store.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `make_index` | `make_index(facts, tmp_dir)` | Create a temporary index.json with given facts. |
+| `test_empty_index` | `test_empty_index()` | Empty knowledge store produces graceful output. |
+| `test_filter_by_repo` | `test_filter_by_repo()` | Filter facts by repository. |
+| `test_filter_by_agent` | `test_filter_by_agent()` | Filter facts by agent type. |
+| `test_no_global_flag` | `test_no_global_flag()` | Excluding global facts works. |
+| `test_sort_by_confidence` | `test_sort_by_confidence()` | Facts sort by confidence descending. |
+| `test_sort_pitfalls_first` | `test_sort_pitfalls_first()` | Pitfalls sort before facts at same confidence. |
+| `test_truncate_to_tokens` | `test_truncate_to_tokens()` | Truncation cuts at line boundary. |
+| `test_estimate_tokens` | `test_estimate_tokens()` | Token estimation is reasonable. |
+| `test_build_full_context` | `test_build_full_context()` | Full context with facts renders correctly. |
+| `test_max_tokens_respected` | `test_max_tokens_respected()` | Output respects max_tokens limit. |
+| `test_missing_index_graceful` | `test_missing_index_graceful()` | Missing index.json doesn't crash. |
+
+## `scripts/test_diff_analyzer.py`
+
+Tests for scripts/diff_analyzer.py — 10 tests.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `test_empty` | `test_empty()` | - |
+| `test_addition` | `test_addition()` | - |
+| `test_deletion` | `test_deletion()` | - |
+| `test_modification` | `test_modification()` | - |
+| `test_rename` | `test_rename()` | - |
+| `test_multiple_files` | `test_multiple_files()` | - |
+| `test_binary` | `test_binary()` | - |
+| `test_to_dict` | `test_to_dict()` | - |
+| `test_context_only` | `test_context_only()` | - |
+| `test_multi_hunk` | `test_multi_hunk()` | - |
+| `run_all` | `run_all()` | - |
+
+## `scripts/test_gitea_issue_parser.py`
+
+Tests for scripts/gitea_issue_parser.py
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `test_basic_parsing` | `test_basic_parsing()` | - |
+| `test_numbered_criteria` | `test_numbered_criteria()` | - |
+| `test_epic_ref_from_body` | `test_epic_ref_from_body()` | - |
+| `test_empty_body` | `test_empty_body()` | - |
+| `test_no_sections` | `test_no_sections()` | - |
+| `test_multiple_sections` | `test_multiple_sections()` | - |
+| `run_all` | `run_all()` | - |
+
+## `scripts/test_harvest_prompt.py`
+
+Test harness for knowledge extraction prompt.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `validate_knowledge_item` | `validate_knowledge_item(item, idx)` | Validate a single knowledge item. Returns list of errors. |
+| `validate_extraction` | `validate_extraction(data)` | Validate a full extraction result. Returns (is_valid, errors, warnings). |
+| `validate_transcript_coverage` | `validate_transcript_coverage(data, transcript)` | Check that extracted facts are actually supported by the transcript. |
+| `run_tests` | `run_tests()` | Run the built-in test suite. |
+| `validate_file` | `validate_file(filepath)` | Validate an existing extraction JSON file. |
+
+## `scripts/test_harvest_prompt_comprehensive.py`
+
+Comprehensive tests for knowledge extraction prompt.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `check_prompt_structure` | `check_prompt_structure()` | - |
+| `check_confidence_scoring` | `check_confidence_scoring()` | - |
+| `check_example_quality` | `check_example_quality()` | - |
+| `check_constraint_coverage` | `check_constraint_coverage()` | - |
+| `check_test_sessions` | `check_test_sessions()` | - |
+| `test_prompt_structure` | `test_prompt_structure()` | - |
+| `test_confidence_scoring` | `test_confidence_scoring()` | - |
+| `test_example_quality` | `test_example_quality()` | - |
+| `test_constraint_coverage` | `test_constraint_coverage()` | - |
+| `test_test_sessions` | `test_test_sessions()` | - |
+
+## `scripts/test_harvester_pipeline.py`
+
+Smoke test for harvester pipeline — verifies the full chain:
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `test_session_reader` | `test_session_reader()` | Test that session_reader parses JSONL correctly. |
+| `test_validate_fact` | `test_validate_fact()` | Test fact validation. |
+| `test_deduplicate` | `test_deduplicate()` | Test deduplication. |
+| `test_knowledge_store_roundtrip` | `test_knowledge_store_roundtrip()` | Test loading and writing knowledge index. |
+| `test_full_chain_no_llm` | `test_full_chain_no_llm()` | Test the full pipeline minus the LLM call. |
+
+## `scripts/test_improvement_proposals.py`
+
+Tests for scripts/improvement_proposals.py — 15 tests.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `test_empty_sessions` | `test_empty_sessions()` | - |
+| `test_no_patterns_on_clean_sessions` | `test_no_patterns_on_clean_sessions()` | - |
+| `test_repeated_error_detection` | `test_repeated_error_detection()` | Same error across 3+ sessions triggers pattern. |
+| `test_repeated_error_threshold` | `test_repeated_error_threshold()` | 2 occurrences should NOT trigger (threshold is 3). |
+| `test_slow_tool_detection` | `test_slow_tool_detection()` | Tool with avg latency > 5000ms across 5+ calls. |
+| `test_fast_tool_not_flagged` | `test_fast_tool_not_flagged()` | Tool under 5000ms avg should not trigger. |
+| `test_failed_retry_detection` | `test_failed_retry_detection()` | 3+ consecutive calls to same tool triggers retry pattern. |
+| `test_manual_process_detection` | `test_manual_process_detection()` | 10+ tool calls with <= 3 unique tools. |
+| `test_generate_proposals_from_patterns` | `test_generate_proposals_from_patterns()` | Proposals generated from waste patterns. |
+| `test_proposal_roi_positive` | `test_proposal_roi_positive()` | ROI weeks should be a positive number for recoverable time. |
+| `test_proposals_sorted_by_impact` | `test_proposals_sorted_by_impact()` | Proposals should be sorted by monthly hours saved (descending). |
+| `test_format_markdown` | `test_format_markdown()` | Markdown output should contain expected sections. |
+| `test_format_json` | `test_format_json()` | JSON output should be valid and parseable. |
+| `test_normalize_error` | `test_normalize_error()` | Error normalization should remove paths and hashes. |
+| `test_cli_integration` | `test_cli_integration()` | End-to-end test: write input JSON, run script, check output. |
+| `run_all` | `run_all()` | - |
+
+## `scripts/test_knowledge_staleness.py`
+
+Tests for scripts/knowledge_staleness_check.py — 8 tests.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `test_fresh_entry` | `test_fresh_entry()` | - |
+| `test_stale_entry` | `test_stale_entry()` | - |
+| `test_missing_source` | `test_missing_source()` | - |
+| `test_no_hash` | `test_no_hash()` | - |
+| `test_no_source_field` | `test_no_source_field()` | - |
+| `test_fix_hashes` | `test_fix_hashes()` | - |
+| `test_empty_index` | `test_empty_index()` | - |
+| `test_compute_hash_nonexistent` | `test_compute_hash_nonexistent()` | - |
+| `run_all` | `run_all()` | - |
+
+## `scripts/test_priority_rebalancer.py`
+
+Tests for Priority Rebalancer
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `test` | `test(name)` | - |
+| `assert_eq` | `assert_eq(a, b, msg)` | - |
+| `assert_true` | `assert_true(v, msg)` | - |
+| `assert_false` | `assert_false(v, msg)` | - |
+| `make_issue` | `make_issue(**kwargs)` | - |
+
+## `scripts/test_refactoring_opportunity_finder.py`
+
+Tests for scripts/refactoring_opportunity_finder.py — 10 tests.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `test_complexity_simple_function` | `test_complexity_simple_function()` | Simple function should have low complexity. |
+| `test_complexity_with_conditionals` | `test_complexity_with_conditionals()` | Function with if/else should have higher complexity. |
+| `test_complexity_with_loops` | `test_complexity_with_loops()` | Function with loops should increase complexity. |
+| `test_complexity_with_class` | `test_complexity_with_class()` | Class with methods should count both. |
+| `test_complexity_syntax_error` | `test_complexity_syntax_error()` | File with syntax error should return zeros. |
+| `test_refactoring_score_high_complexity` | `test_refactoring_score_high_complexity()` | High complexity should give high score. |
+| `test_refactoring_score_low_complexity` | `test_refactoring_score_low_complexity()` | Low complexity should give lower score. |
+| `test_refactoring_score_high_churn` | `test_refactoring_score_high_churn()` | High churn should increase score. |
+| `test_refactoring_score_no_coverage` | `test_refactoring_score_no_coverage()` | No coverage data should assume medium risk. |
+| `test_refactoring_score_large_file` | `test_refactoring_score_large_file()` | Large files should score higher. |
+| `run_all` | `run_all()` | - |
+
+## `scripts/test_session_pair_harvester.py`
+
+Tests for session_pair_harvester.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `test_basic_extraction` | `test_basic_extraction()` | - |
+| `test_filters_short_responses` | `test_filters_short_responses()` | - |
+| `test_skips_tool_results` | `test_skips_tool_results()` | - |
+| `test_deduplication` | `test_deduplication()` | - |
+| `test_ratio_filter` | `test_ratio_filter()` | - |
+
+## `scripts/validate_knowledge.py`
+
+Validate knowledge files and index.json against the schema.
+
+| Function | Signature | Description |
+|----------|-----------|-------------|
+| `validate_fact` | `validate_fact(fact, src)` | - |
+| `main` | `main()` | - |
+
+
+---
+
+**Total scripts documented:** 33
+
+*Generated by `scripts/api_doc_generator.py` (Issue #98)*

scripts/api_doc_generator.py

@@ -0,0 +1,219 @@
+#!/usr/bin/env python3
+"""
+API Doc Generator — Issue #98
+
+Scans all Python modules in `scripts/`, extracts their public API surface
+(module docstring + public function signatures + first-line doc summaries),
+and produces a single markdown reference document at `docs/API.md`.
+
+Usage:
+    python3 scripts/api_doc_generator.py          # Write docs/API.md
+    python3 scripts/api_doc_generator.py --check  # Verify docs/API.md is up-to-date
+    python3 scripts/api_doc_generator.py --json   # Emit JSON for downstream tooling
+"""
+
+from __future__ import annotations
+
+import ast
+import os
+import sys
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import TypedDict, List, Optional
+
+
+# ─── Paths ────────────────────────────────────────────────────────────────────
+SCRIPT_DIR = Path(__file__).resolve().parent
+REPO_ROOT = SCRIPT_DIR.parent
+SCRIPTS_DIR = REPO_ROOT / "scripts"
+DOCS_DIR = REPO_ROOT / "docs"
+OUTPUT_PATH = DOCS_DIR / "API.md"
+
+
+# ─── Data structures ───────────────────────────────────────────────────────────
+class FunctionInfo(TypedDict):
+    name: str
+    signature: str
+    summary: str
+
+
+class ModuleInfo(TypedDict):
+    path: str  # relative to repo root, e.g. "scripts/harvester.py"
+    docstring: str
+    functions: List[FunctionInfo]
+
+
+# ─── AST extraction ────────────────────────────────────────────────────────────
+def extract_functions_from_ast(tree: ast.AST, file_rel: str) -> List[FunctionInfo]:
+    """Extract public function names, signatures, and first-line doc summaries."""
+    funcs: list[FunctionInfo] = []
+
+    for node in ast.iter_child_nodes(tree):
+        if not isinstance(node, ast.FunctionDef):
+            continue
+        # Skip private functions
+        if node.name.startswith("_"):
+            continue
+
+        # Build signature: arg1, arg2=default, *args, **kwargs
+        args = []
+        for arg in node.args.args:
+            args.append(arg.arg)
+        if node.args.vararg:
+            args.append(f"*{node.args.vararg.arg}")
+        if node.args.kwarg:
+            args.append(f"**{node.args.kwarg.arg}")
+
+        # Get first line of docstring
+        summary = ""
+        if (node.body and isinstance(node.body[0], ast.Expr) and
+            isinstance(node.body[0].value, ast.Constant) and
+            isinstance(node.body[0].value.value, str)):
+            raw = node.body[0].value.value.strip()
+            summary = raw.split("\n")[0].strip()
+            if len(summary) > 100:
+                summary = summary[:97] + "..."
+
+        funcs.append({
+            "name": node.name,
+            "signature": ", ".join(args),
+            "summary": summary,
+        })
+
+    return funcs
+
+
+def parse_module(filepath: Path) -> Optional[ModuleInfo]:
+    """Parse a Python file and return its module-level docstring and public functions."""
+    try:
+        with open(filepath, "r", encoding="utf-8") as f:
+            source = f.read()
+        tree = ast.parse(source, filename=str(filepath))
+    except Exception as e:
+        print(f"WARNING: Could not parse {filepath}: {e}", file=sys.stderr)
+        return None
+
+    # Module docstring
+    module_doc = ast.get_docstring(tree) or ""
+    module_doc = module_doc.strip().split("\n")[0]  # first line only
+
+    # Public functions
+    functions = extract_functions_from_ast(tree, filepath.name)
+
+    rel = filepath.relative_to(REPO_ROOT)
+    return {
+        "path": str(rel),
+        "docstring": module_doc,
+        "functions": functions,
+    }
+
+
+# ─── Scanning ──────────────────────────────────────────────────────────────────
+def scan_scripts_dir(scripts_dir: Path) -> List[ModuleInfo]:
+    """Scan all .py files in scripts/ and extract API info."""
+    modules: list[ModuleInfo] = []
+    for pyfile in sorted(scripts_dir.glob("*.py")):
+        info = parse_module(pyfile)
+        if info is not None:
+            modules.append(info)
+    return modules
+
+
+# ─── Markdown rendering ─────────────────────────────────────────────────────────
+def render_markdown(modules: List[ModuleInfo]) -> str:
+    """Generate full docs/API.md content from the scanned modules."""
+    lines = [
+        "# Compounding Intelligence — Scripts API Reference",
+        "",
+        f"*Generated: {datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M UTC')}*",
+        "",
+        "This document auto-documents the public API surface of all scripts",
+        "in `scripts/`. Each section covers one script: module purpose,",
+        "public functions, and their signatures.",
+        "",
+        "---",
+        "",
+    ]
+
+    for mod in modules:
+        rel = mod["path"]
+        name = Path(rel).stem  # e.g. harvester
+        lines.append(f"## `{rel}`")
+        lines.append("")
+        if mod["docstring"]:
+            lines.append(mod["docstring"])
+            lines.append("")
+
+        if mod["functions"]:
+            lines.append("| Function | Signature | Description |")
+            lines.append("|----------|-----------|-------------|")
+            for fn in mod["functions"]:
+                sig = fn["name"] + "(" + fn["signature"] + ")"
+                desc = fn["summary"] or "-"
+                lines.append(f"| `{fn['name']}` | `{sig}` | {desc} |")
+            lines.append("")
+        else:
+            lines.append("*(no public functions — script runs as `main()` only)*")
+            lines.append("")
+
+    lines.extend([
+        "",
+        "---",
+        "",
+        f"**Total scripts documented:** {len(modules)}",
+        "",
+        "*Generated by `scripts/api_doc_generator.py` (Issue #98)*",
+    ])
+    return "\n".join(lines)
+
+
+# ─── JSON output (optional, for automation) ───────────────────────────────────
+def render_json(modules: List[ModuleInfo]) -> str:
+    """Emit machine-readable JSON version of the API reference."""
+    import json
+    payload = {
+        "generated_at": datetime.now(timezone.utc).isoformat(),
+        "generator": "scripts/api_doc_generator.py",
+        "repo": "Timmy_Foundation/compounding-intelligence",
+        "modules": modules,
+    }
+    return json.dumps(payload, indent=2)
+
+
+# ─── Main ──────────────────────────────────────────────────────────────────────
+def main() -> int:
+    import argparse
+    parser = argparse.ArgumentParser(description="Generate API docs for scripts/")
+    parser.add_argument("--check", action="store_true",
+                        help="Exit 1 if docs/API.md is out-of-date")
+    parser.add_argument("--json", action="store_true",
+                        help="Emit JSON to stdout instead of writing markdown")
+    args = parser.parse_args()
+
+    modules = scan_scripts_dir(SCRIPTS_DIR)
+    modules.sort(key=lambda m: m["path"])
+
+    if args.json:
+        print(render_json(modules))
+        return 0
+
+    md = render_markdown(modules)
+
+    if args.check:
+        if OUTPUT_PATH.exists():
+            existing = OUTPUT_PATH.read_text(encoding="utf-8")
+            if existing == md:
+                print("✅ docs/API.md is up-to-date")
+                return 0
+        print("❌ docs/API.md is missing or out-of-date — regenerate with "
+              "`python3 scripts/api_doc_generator.py`", file=sys.stderr)
+        return 1
+
+    DOCS_DIR.mkdir(parents=True, exist_ok=True)
+    OUTPUT_PATH.write_text(md, encoding="utf-8")
+    print(f"✅ Wrote {OUTPUT_PATH}  ({len(modules)} modules documented)")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

scripts/knowledge_to_training_pairs.py

@@ -1,255 +0,0 @@
-#!/usr/bin/env python3
-"""
-knowledge_to_training_pairs.py — Convert quality-gated knowledge entries into training pairs.
-
-Reads knowledge/index.json (or a custom JSONL of entries), applies quality filters,
-and emits terse→rich training pairs in JSONL format for model fine-tuning.
-
-Usage:
-    python3 scripts/knowledge_to_training_pairs.py \
-        --input knowledge/index.json \
-        --output training_pairs.jsonl \
-        --min-confidence 0.7 \
-        --model-filter claude-sonnet,gpt-4 \
-        --after 2026-01-01
-
-Input entry format (from index.json facts):
-    {
-        "id": "hermes-agent:pitfall:001",
-        "fact": "deploy-crons.py leaves jobs in mixed model format",
-        "category": "pitfall",
-        "domain": "hermes-agent",
-        "confidence": 0.95,
-        ...
-    }
-
-Output training pair format:
-    {
-        "terse": "How do I handle deploy-crons.py mixed model format?",
-        "rich": "deploy-crons.py leaves jobs in mixed model format.",
-        "domain": "hermes-agent",
-        "source_confidence": 0.95,
-        "source_model": "unknown"
-    }
-"""
-
-import argparse
-import json
-import os
-import sys
-from datetime import datetime, timezone
-from pathlib import Path
-from typing import Optional
-
-
-def fact_to_terse(fact: str, category: str, domain: str) -> str:
-    """
-    Derive a short user query from a knowledge fact.
-
-    Strategy:
-    - Pitfalls → "How do I avoid/handle/fix <fact excerpt>?"
-    - Patterns  → "What's the recommended way to <pattern core>?"
-    - Tool quirks → "How does <tool> behave in <context>?"
-    - Facts → "What should I know about <fact excerpt>?"
-    - Questions → "What is the answer to: <fact>?"
-    """
-    fact_lower = fact.lower()
-    # Extract a concise excerpt (first sentence or 80 chars)
-    excerpt = fact.split('. ')[0] if '. ' in fact else fact[:80]
-
-    if category == "pitfall":
-        verbs = ["avoid", "handle", "fix", "prevent"]
-        # pick verb based on fact wording
-        if "trigger" in fact_lower or "cause" in fact_lower:
-            verb = "avoid"
-        elif "broken" in fact_lower or "fails" in fact_lower:
-            verb = "fix"
-        else:
-            verb = "handle"
-        return f"How do I {verb} {excerpt.rstrip('.')}?"
-    elif category == "pattern":
-        return f"What's the recommended way to {excerpt.rstrip('.')}?"
-    elif category == "tool-quirk":
-        # Try to extract tool name
-        tool = fact.split()[0] if fact.split() else domain
-        return f"How does {tool} behave in this context?"
-    elif category == "question":
-        return f"What is the answer to: {excerpt}?"
-    else:  # fact or unknown
-        return f"What should I know about {excerpt.rstrip('.')}?"
-
-
-def parse_date(date_str: Optional[str]) -> Optional[datetime]:
-    """Parse ISO date string to datetime, or return None."""
-    if not date_str:
-        return None
-    try:
-        return datetime.fromisoformat(date_str.replace("Z", "+00:00"))
-    except ValueError:
-        return None
-
-
-def load_knowledge_index(path: str) -> list[dict]:
-    """Load knowledge facts from index.json (or plain JSONL of entries)."""
-    p = Path(path)
-    if not p.exists():
-        print(f"ERROR: Knowledge input not found: {path}", file=sys.stderr)
-        sys.exit(1)
-
-    with open(p) as f:
-        data = json.load(f)
-
-    # index.json format: {"facts": [...], ...}
-    if isinstance(data, dict) and "facts" in data:
-        return data["facts"]
-    # JSONL format: one entry per line
-    if isinstance(data, list):
-        return data
-    # Plain file with JSON array
-    print(f"ERROR: Unrecognized input format in {path}", file=sys.stderr)
-    sys.exit(1)
-
-
-def filter_entries(entries: list[dict],
-                   min_confidence: float = 0.0,
-                   model_filter: Optional[list[str]] = None,
-                   after: Optional[datetime] = None,
-                   before: Optional[datetime] = None) -> list[dict]:
-    """Apply quality and provenance filters."""
-    filtered = []
-    for entry in entries:
-        # Confidence filter (entry confidence)
-        conf = entry.get("confidence", 0.0)
-        if conf < min_confidence:
-            continue
-
-        # Model filter: if specified, entry's model must be in the list
-        if model_filter:
-            entry_model = entry.get("model", entry.get("provenance", {}).get("model", "unknown"))
-            if entry_model not in model_filter:
-                continue
-
-        # Date filter: use last_confirmed or first_seen or harvested_at
-        entry_date = None
-        for field in ("last_confirmed", "first_seen", "harvested_at"):
-            if field in entry:
-                entry_date = parse_date(entry[field])
-                if entry_date:
-                    break
-        if after and entry_date and entry_date < after:
-            continue
-        if before and entry_date and entry_date > before:
-            continue
-
-        filtered.append(entry)
-    return filtered
-
-
-def entry_to_pair(entry: dict) -> dict:
-    """Convert a knowledge entry into a training pair."""
-    fact = entry.get("fact", "").strip()
-    if not fact:
-        return None
-
-    category = entry.get("category", "fact")
-    domain = entry.get("domain", "global")
-
-    terse = fact_to_terse(fact, category, domain)
-    rich = fact
-    source_confidence = round(entry.get("confidence", 0.0), 4)
-    source_model = entry.get("model", entry.get("provenance", {}).get("model", "unknown"))
-
-    return {
-        "terse": terse,
-        "rich": rich,
-        "domain": domain,
-        "source_confidence": source_confidence,
-        "source_model": source_model,
-    }
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Knowledge entries → training pairs")
-    parser.add_argument("--input", "-i", default="knowledge/index.json",
-                        help="Input knowledge index or JSONL (default: knowledge/index.json)")
-    parser.add_argument("--output", "-o", default="training_pairs.jsonl",
-                        help="Output JSONL file")
-    parser.add_argument("--min-confidence", type=float, default=0.5,
-                        help="Minimum entry confidence to include (0.0-1.0, default: 0.5)")
-    parser.add_argument("--model-filter",
-                        help="Comma-separated list of source models to include")
-    parser.add_argument("--after",
-                        help="Include entries last_confirmed/first_seen on or after this date (YYYY-MM-DD)")
-    parser.add_argument("--before",
-                        help="Include entries last_confirmed/first_seen on or before this date (YYYY-MM-DD)")
-    parser.add_argument("--dry-run", action="store_true",
-                        help="Print sample pairs and stats without writing")
-    args = parser.parse_args()
-
-    # Load
-    entries = load_knowledge_index(args.input)
-    print(f"Loaded {len(entries)} entries from {args.input}", file=sys.stderr)
-
-    # Parse filters
-    model_list = args.model_filter.split(",") if args.model_filter else None
-    after_dt = parse_date(args.after) if args.after else None
-    before_dt = parse_date(args.before) if args.before else None
-
-    # Filter
-    kept = filter_entries(
-        entries,
-        min_confidence=args.min_confidence,
-        model_filter=model_list,
-        after=after_dt,
-        before=before_dt,
-    )
-    print(f"After filtering: {len(kept)} / {len(entries)} entries", file=sys.stderr)
-
-    # Convert
-    pairs = []
-    for entry in kept:
-        pair = entry_to_pair(entry)
-        if pair:
-            pairs.append(pair)
-
-    # Stats
-    if pairs:
-        avg_conf = sum(p["source_confidence"] for p in pairs) / len(pairs)
-        domains = {}
-        models = {}
-        for p in pairs:
-            domains[p["domain"]] = domains.get(p["domain"], 0) + 1
-            models[p["source_model"]] = models.get(p["source_model"], 0) + 1
-    else:
-        avg_conf = 0.0
-        domains = {}
-        models = {}
-
-    stats = {
-        "input_entries": len(entries),
-        "after_filter": len(kept),
-        "pairs_generated": len(pairs),
-        "avg_confidence": round(avg_conf, 4),
-        "domains": domains,
-        "source_models": models,
-    }
-    print(json.dumps(stats, indent=2), file=sys.stderr)
-
-    if args.dry_run:
-        print("\nSample pairs:", file=sys.stderr)
-        for p in pairs[:3]:
-            print(json.dumps(p, ensure_ascii=False), file=sys.stderr)
-        return
-
-    # Write JSONL
-    out_path = Path(args.output)
-    out_path.parent.mkdir(parents=True, exist_ok=True)
-    with open(out_path, "w", encoding="utf-8") as f:
-        for pair in pairs:
-            f.write(json.dumps(pair, ensure_ascii=False) + "\n")
-
-    print(f"\nWrote {len(pairs)} training pairs to {out_path}", file=sys.stderr)
-
-
-if __name__ == "__main__":
-    main()

scripts/pr_complexity_scorer.py

@@ -1,351 +0,0 @@
-#!/usr/bin/env python3
-"""
-PR Complexity Scorer - Estimate review effort for PRs.
-"""
-
-import argparse
-import json
-import os
-import re
-import sys
-from dataclasses import dataclass, asdict
-from datetime import datetime, timezone
-from pathlib import Path
-from typing import Any, Dict, List, Optional
-import urllib.request
-import urllib.error
-
-GITEA_BASE = "https://forge.alexanderwhitestone.com/api/v1"
-
-DEPENDENCY_FILES = {
-    "requirements.txt", "pyproject.toml", "setup.py", "setup.cfg",
-    "Pipfile", "poetry.lock", "package.json", "yarn.lock", "Gemfile",
-    "go.mod", "Cargo.toml", "pom.xml", "build.gradle"
-}
-
-TEST_PATTERNS = [
-    r"tests?/.*\.py$", r".*_test\.py$", r"test_.*\.py$",
-    r"spec/.*\.rb$", r".*_spec\.rb$",
-    r"__tests__/", r".*\.test\.(js|ts|jsx|tsx)$"
-]
-
-WEIGHT_FILES = 0.25
-WEIGHT_LINES = 0.25
-WEIGHT_DEPS = 0.30
-WEIGHT_TEST_COV = 0.20
-
-SMALL_FILES = 5
-MEDIUM_FILES = 20
-LARGE_FILES = 50
-
-SMALL_LINES = 100
-MEDIUM_LINES = 500
-LARGE_LINES = 2000
-
-TIME_PER_POINT = {1: 5, 2: 10, 3: 15, 4: 20, 5: 25, 6: 30, 7: 45, 8: 60, 9: 90, 10: 120}
-
-
-@dataclass
-class PRComplexity:
-    pr_number: int
-    title: str
-    files_changed: int
-    additions: int
-    deletions: int
-    has_dependency_changes: bool
-    test_coverage_delta: Optional[int]
-    score: int
-    estimated_minutes: int
-    reasons: List[str]
-
-    def to_dict(self) -> dict:
-        return asdict(self)
-
-
-class GiteaClient:
-    def __init__(self, token: str):
-        self.token = token
-        self.base_url = GITEA_BASE.rstrip("/")
-
-    def _request(self, path: str, params: Dict = None) -> Any:
-        url = f"{self.base_url}{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}: {e.read().decode()[:200]}", file=sys.stderr)
-            return None
-        except urllib.error.URLError as e:
-            print(f"Network error: {e}", file=sys.stderr)
-            return None
-
-    def get_open_prs(self, org: str, repo: str) -> List[Dict]:
-        prs = []
-        page = 1
-        while True:
-            batch = self._request(f"/repos/{org}/{repo}/pulls", {"limit": 50, "page": page, "state": "open"})
-            if not batch:
-                break
-            prs.extend(batch)
-            if len(batch) < 50:
-                break
-            page += 1
-        return prs
-
-    def get_pr_files(self, org: str, repo: str, pr_number: int) -> List[Dict]:
-        files = []
-        page = 1
-        while True:
-            batch = self._request(
-                f"/repos/{org}/{repo}/pulls/{pr_number}/files",
-                {"limit": 100, "page": page}
-            )
-            if not batch:
-                break
-            files.extend(batch)
-            if len(batch) < 100:
-                break
-            page += 1
-        return files
-
-    def post_comment(self, org: str, repo: str, pr_number: int, body: str) -> bool:
-        data = json.dumps({"body": body}).encode("utf-8")
-        req = urllib.request.Request(
-            f"{self.base_url}/repos/{org}/{repo}/issues/{pr_number}/comments",
-            data=data,
-            method="POST",
-            headers={"Authorization": f"token {self.token}", "Content-Type": "application/json"}
-        )
-        try:
-            with urllib.request.urlopen(req, timeout=30) as resp:
-                return resp.status in (200, 201)
-        except urllib.error.HTTPError:
-            return False
-
-
-def is_dependency_file(filename: str) -> bool:
-    return any(filename.endswith(dep) for dep in DEPENDENCY_FILES)
-
-
-def is_test_file(filename: str) -> bool:
-    return any(re.search(pattern, filename) for pattern in TEST_PATTERNS)
-
-
-def score_pr(
-    files_changed: int,
-    additions: int,
-    deletions: int,
-    has_dependency_changes: bool,
-    test_coverage_delta: Optional[int] = None
-) -> tuple[int, int, List[str]]:
-    score = 1.0
-    reasons = []
-
-    # Files changed
-    if files_changed <= SMALL_FILES:
-        fscore = 1.0
-        reasons.append("small number of files changed")
-    elif files_changed <= MEDIUM_FILES:
-        fscore = 2.0
-        reasons.append("moderate number of files changed")
-    elif files_changed <= LARGE_FILES:
-        fscore = 2.5
-        reasons.append("large number of files changed")
-    else:
-        fscore = 3.0
-        reasons.append("very large PR spanning many files")
-
-    # Lines changed
-    total_lines = additions + deletions
-    if total_lines <= SMALL_LINES:
-        lscore = 1.0
-        reasons.append("small change size")
-    elif total_lines <= MEDIUM_LINES:
-        lscore = 2.0
-        reasons.append("moderate change size")
-    elif total_lines <= LARGE_LINES:
-        lscore = 3.0
-        reasons.append("large change size")
-    else:
-        lscore = 4.0
-        reasons.append("very large change")
-
-    # Dependency changes
-    if has_dependency_changes:
-        dscore = 2.5
-        reasons.append("dependency changes (architectural impact)")
-    else:
-        dscore = 0.0
-
-    # Test coverage delta
-    tscore = 0.0
-    if test_coverage_delta is not None:
-        if test_coverage_delta > 0:
-            reasons.append(f"test additions (+{test_coverage_delta} test files)")
-            tscore = -min(2.0, test_coverage_delta / 2.0)
-        elif test_coverage_delta < 0:
-            reasons.append(f"test removals ({abs(test_coverage_delta)} test files)")
-            tscore = min(2.0, abs(test_coverage_delta) * 0.5)
-    else:
-        reasons.append("test coverage change not assessed")
-
-    # Weighted sum, scaled by 3 to use full 1-10 range
-    bonus = (fscore * WEIGHT_FILES) + (lscore * WEIGHT_LINES) + (dscore * WEIGHT_DEPS) + (tscore * WEIGHT_TEST_COV)
-    scaled_bonus = bonus * 3.0
-    score = 1.0 + scaled_bonus
-
-    final_score = max(1, min(10, int(round(score))))
-    est_minutes = TIME_PER_POINT.get(final_score, 30)
-
-    return final_score, est_minutes, reasons
-
-
-def analyze_pr(client: GiteaClient, org: str, repo: str, pr_data: Dict) -> PRComplexity:
-    pr_num = pr_data["number"]
-    title = pr_data.get("title", "")
-    files = client.get_pr_files(org, repo, pr_num)
-
-    additions = sum(f.get("additions", 0) for f in files)
-    deletions = sum(f.get("deletions", 0) for f in files)
-    filenames = [f.get("filename", "") for f in files]
-
-    has_deps = any(is_dependency_file(f) for f in filenames)
-
-    test_added = sum(1 for f in files if f.get("status") == "added" and is_test_file(f.get("filename", "")))
-    test_removed = sum(1 for f in files if f.get("status") == "removed" and is_test_file(f.get("filename", "")))
-    test_delta = test_added - test_removed if (test_added or test_removed) else None
-
-    score, est_min, reasons = score_pr(
-        files_changed=len(files),
-        additions=additions,
-        deletions=deletions,
-        has_dependency_changes=has_deps,
-        test_coverage_delta=test_delta
-    )
-
-    return PRComplexity(
-        pr_number=pr_num,
-        title=title,
-        files_changed=len(files),
-        additions=additions,
-        deletions=deletions,
-        has_dependency_changes=has_deps,
-        test_coverage_delta=test_delta,
-        score=score,
-        estimated_minutes=est_min,
-        reasons=reasons
-    )
-
-
-def build_comment(complexity: PRComplexity) -> str:
-    change_desc = f"{complexity.files_changed} files, +{complexity.additions}/-{complexity.deletions} lines"
-    deps_note = "\n- :warning: Dependency changes detected — architectural review recommended" if complexity.has_dependency_changes else ""
-    test_note = ""
-    if complexity.test_coverage_delta is not None:
-        if complexity.test_coverage_delta > 0:
-            test_note = f"\n- :+1: {complexity.test_coverage_delta} test file(s) added"
-        elif complexity.test_coverage_delta < 0:
-            test_note = f"\n- :warning: {abs(complexity.test_coverage_delta)} test file(s) removed"
-
-    comment = f"## 📊 PR Complexity Analysis\n\n"
-    comment += f"**PR #{complexity.pr_number}: {complexity.title}**\n\n"
-    comment += f"| Metric | Value |\n|--------|-------|\n"
-    comment += f"| Changes | {change_desc} |\n"
-    comment += f"| Complexity Score | **{complexity.score}/10** |\n"
-    comment += f"| Estimated Review Time | ~{complexity.estimated_minutes} minutes |\n\n"
-    comment += f"### Scoring rationale:"
-    for r in complexity.reasons:
-        comment += f"\n- {r}"
-    if deps_note:
-        comment += deps_note
-    if test_note:
-        comment += test_note
-    comment += f"\n\n---\n"
-    comment += f"*Generated by PR Complexity Scorer — [issue #135](https://forge.alexanderwhitestone.com/Timmy_Foundation/compounding-intelligence/issues/135)*"
-    return comment
-
-
-def main():
-    parser = argparse.ArgumentParser(description="PR Complexity Scorer")
-    parser.add_argument("--org", default="Timmy_Foundation")
-    parser.add_argument("--repo", default="compounding-intelligence")
-    parser.add_argument("--token", default=os.environ.get("GITEA_TOKEN") or os.path.expanduser("~/.config/gitea/token"))
-    parser.add_argument("--dry-run", action="store_true")
-    parser.add_argument("--apply", action="store_true")
-    parser.add_argument("--output", default="metrics/pr_complexity.json")
-    args = parser.parse_args()
-
-    token_path = args.token
-    if os.path.exists(token_path):
-        with open(token_path) as f:
-            token = f.read().strip()
-    else:
-        token = args.token
-
-    if not token:
-        print("ERROR: No Gitea token provided", file=sys.stderr)
-        sys.exit(1)
-
-    client = GiteaClient(token)
-
-    print(f"Fetching open PRs for {args.org}/{args.repo}...")
-    prs = client.get_open_prs(args.org, args.repo)
-    if not prs:
-        print("No open PRs found.")
-        sys.exit(0)
-
-    print(f"Found {len(prs)} open PR(s). Analyzing...")
-
-    results = []
-    Path(args.output).parent.mkdir(parents=True, exist_ok=True)
-
-    for pr in prs:
-        pr_num = pr["number"]
-        title = pr.get("title", "")
-        print(f"  Analyzing PR #{pr_num}: {title[:60]}")
-
-        try:
-            complexity = analyze_pr(client, args.org, args.repo, pr)
-            results.append(complexity.to_dict())
-
-            comment = build_comment(complexity)
-
-            if args.dry_run:
-                print(f"    → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min [DRY-RUN]")
-            elif args.apply:
-                success = client.post_comment(args.org, args.repo, pr_num, comment)
-                status = "[commented]" if success else "[FAILED]"
-                print(f"    → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min {status}")
-            else:
-                print(f"    → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min [no action]")
-
-        except Exception as e:
-            print(f"    ERROR analyzing PR #{pr_num}: {e}", file=sys.stderr)
-
-    with open(args.output, "w") as f:
-        json.dump({
-            "org": args.org,
-            "repo": args.repo,
-            "timestamp": datetime.now(timezone.utc).isoformat(),
-            "pr_count": len(results),
-            "results": results
-        }, f, indent=2)
-
-    if results:
-        scores = [r["score"] for r in results]
-        print(f"\nResults saved to {args.output}")
-        print(f"Summary: {len(results)} PRs, scores range {min(scores):.0f}-{max(scores):.0f}")
-    else:
-        print("\nNo results to save.")
-
-
-if __name__ == "__main__":
-    main()

scripts/test_pr_complexity_scorer.py

@@ -1,170 +0,0 @@
-#!/usr/bin/env python3
-"""
-Tests for PR Complexity Scorer — unit tests for the scoring logic.
-"""
-
-import sys
-from pathlib import Path
-
-sys.path.insert(0, str(Path(__file__).parent))
-
-from pr_complexity_scorer import (
-    score_pr,
-    is_dependency_file,
-    is_test_file,
-    TIME_PER_POINT,
-    SMALL_FILES,
-    MEDIUM_FILES,
-    LARGE_FILES,
-    SMALL_LINES,
-    MEDIUM_LINES,
-    LARGE_LINES,
-)
-
-PASS = 0
-FAIL = 0
-
-def test(name):
-    def decorator(fn):
-        global PASS, FAIL
-        try:
-            fn()
-            PASS += 1
-            print(f"  [PASS] {name}")
-        except AssertionError as e:
-            FAIL += 1
-            print(f"  [FAIL] {name}: {e}")
-        except Exception as e:
-            FAIL += 1
-            print(f"  [FAIL] {name}: Unexpected error: {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")
-
-
-print("=== PR Complexity Scorer Tests ===\n")
-
-print("-- File Classification --")
-
-@test("dependency file detection — requirements.txt")
-def _():
-    assert_true(is_dependency_file("requirements.txt"))
-    assert_true(is_dependency_file("src/requirements.txt"))
-    assert_false(is_dependency_file("requirements_test.txt"))
-
-@test("dependency file detection — pyproject.toml")
-def _():
-    assert_true(is_dependency_file("pyproject.toml"))
-    assert_false(is_dependency_file("myproject.py"))
-
-@test("test file detection — pytest style")
-def _():
-    assert_true(is_test_file("tests/test_api.py"))
-    assert_true(is_test_file("test_module.py"))
-    assert_true(is_test_file("src/module_test.py"))
-
-@test("test file detection — other frameworks")
-def _():
-    assert_true(is_test_file("spec/feature_spec.rb"))
-    assert_true(is_test_file("__tests__/component.test.js"))
-    assert_false(is_test_file("testfixtures/helper.py"))
-
-
-print("\n-- Scoring Logic --")
-
-@test("small PR gets low score (1-3)")
-def _():
-    score, minutes, _ = score_pr(
-        files_changed=3,
-        additions=50,
-        deletions=10,
-        has_dependency_changes=False,
-        test_coverage_delta=None
-    )
-    assert_true(1 <= score <= 3, f"Score should be low, got {score}")
-    assert_true(minutes < 20)
-
-@test("medium PR gets medium score (4-6)")
-def _():
-    score, minutes, _ = score_pr(
-        files_changed=15,
-        additions=400,
-        deletions=100,
-        has_dependency_changes=False,
-        test_coverage_delta=None
-    )
-    assert_true(4 <= score <= 6, f"Score should be medium, got {score}")
-    assert_true(20 <= minutes <= 45)
-
-@test("large PR gets high score (7-9)")
-def _():
-    score, minutes, _ = score_pr(
-        files_changed=60,
-        additions=3000,
-        deletions=1500,
-        has_dependency_changes=True,
-        test_coverage_delta=None
-    )
-    assert_true(7 <= score <= 9, f"Score should be high, got {score}")
-    assert_true(minutes >= 45)
-
-@test("dependency changes boost score")
-def _():
-    base_score, _, _ = score_pr(
-        files_changed=10, additions=200, deletions=50,
-        has_dependency_changes=False, test_coverage_delta=None
-    )
-    dep_score, _, _ = score_pr(
-        files_changed=10, additions=200, deletions=50,
-        has_dependency_changes=True, test_coverage_delta=None
-    )
-    assert_true(dep_score > base_score, f"Deps: {base_score} -> {dep_score}")
-
-@test("adding tests lowers complexity")
-def _():
-    base_score, _, _ = score_pr(
-        files_changed=8, additions=150, deletions=20,
-        has_dependency_changes=False, test_coverage_delta=None
-    )
-    better_score, _, _ = score_pr(
-        files_changed=8, additions=180, deletions=20,
-        has_dependency_changes=False, test_coverage_delta=3
-    )
-    assert_true(better_score < base_score, f"Tests: {base_score} -> {better_score}")
-
-@test("removing tests increases complexity")
-def _():
-    base_score, _, _ = score_pr(
-        files_changed=8, additions=150, deletions=20,
-        has_dependency_changes=False, test_coverage_delta=None
-    )
-    worse_score, _, _ = score_pr(
-        files_changed=8, additions=150, deletions=20,
-        has_dependency_changes=False, test_coverage_delta=-2
-    )
-    assert_true(worse_score > base_score, f"Remove tests: {base_score} -> {worse_score}")
-
-@test("score bounded 1-10")
-def _():
-    for files, adds, dels in [(1, 10, 5), (100, 10000, 5000)]:
-        score, _, _ = score_pr(files, adds, dels, False, None)
-        assert_true(1 <= score <= 10, f"Score {score} out of range")
-
-@test("estimated minutes exist for all scores")
-def _():
-    for s in range(1, 11):
-        assert_true(s in TIME_PER_POINT, f"Missing time for score {s}")
-
-
-print(f"\n=== Results: {PASS} passed, {FAIL} failed ===")
-sys.exit(0 if FAIL == 0 else 1)

tests/test_api_doc_generator.py

@@ -0,0 +1,148 @@
+#!/usr/bin/env python3
+"""
+Smoke tests for API Doc Generator — Issue #98
+
+Validates that the generator runs, produces docs/API.md, and that
+the generated markdown contains expected sections for the known scripts.
+"""
+
+from __future__ import annotations
+
+import subprocess
+import sys
+from pathlib import Path
+
+import pytest
+
+# Resolve repo root
+REPO_ROOT = Path(__file__).resolve().parents[1]
+SCRIPTS_DIR = REPO_ROOT / "scripts"
+DOCS_DIR = REPO_ROOT / "docs"
+API_MD = DOCS_DIR / "API.md"
+GENERATOR = SCRIPTS_DIR / "api_doc_generator.py"
+
+
+# ─── Generator presence ─────────────────────────────────────────────────────────
+class TestGeneratorPresence:
+    def test_generator_script_exists(self):
+        assert GENERATOR.exists(), f"Missing: {GENERATOR}"
+
+    def test_generator_is_executable(self):
+        with open(GENERATOR) as f:
+            first = f.readline().strip()
+        assert first.startswith("#!"), "Missing shebang"
+        assert "python" in first.lower()
+
+
+# ─── API.md generation ──────────────────────────────────────────────────────────
+class TestAPIDocGeneration:
+    def test_generator_runs_successfully(self):
+        """Run the generator and verify exit code 0."""
+        result = subprocess.run(
+            [sys.executable, str(GENERATOR)],
+            capture_output=True, text=True, cwd=REPO_ROOT, timeout=30
+        )
+        assert result.returncode == 0, (
+            f"Generator failed (code {{result.returncode}})\n"
+            f"STDERR: {{result.stderr[:500]}}"
+        )
+
+    def test_api_md_is_created(self):
+        """docs/API.md must exist after generation."""
+        assert API_MD.exists(), f"Missing output: {API_MD}"
+
+    def test_api_md_is_not_empty(self):
+        """Generate markdown must have substantial content."""
+        content = API_MD.read_text(encoding="utf-8")
+        assert len(content) > 1000, "API.md is suspiciously small"
+
+    def test_api_md_has_expected_structure(self):
+        """Top-level headings and table markers must be present."""
+        content = API_MD.read_text(encoding="utf-8")
+        assert "# Compounding Intelligence — Scripts API Reference" in content
+        assert "## `scripts/" in content
+        assert "| Function | Signature | Description |" in content
+
+    def test_api_md_covers_expected_scripts(self):
+        """At minimum the core scripts should be documented."""
+        content = API_MD.read_text(encoding="utf-8")
+        # Core scripts that must appear
+        core = ["scripts/harvester.py", "scripts/bootstrapper.py",
+                "scripts/session_reader.py", "scripts/dedup.py"]
+        for rel in core:
+            assert f"## `{rel}`" in content, f"Missing section for {rel}"
+
+    def test_api_md_contains_function_names(self):
+        """Spot-check: known public functions from key modules must appear."""
+        content = API_MD.read_text(encoding="utf-8")
+        checks = [
+            ("harvester", "read_session"),
+            ("bootstrapper", "load_index"),
+            ("session_reader", "extract_conversation"),
+            ("dedup", "normalize_text"),
+        ]
+        for module_stem, func_name in checks:
+            assert f"| `{func_name}` |" in content,                 f"Missing function {func_name} from {module_stem}"
+
+
+# ─── Idempotence / --check ─────────────────────────────────────────────────────
+class TestIdempotence:
+    def test_check_flag_passes_when_current(self):
+        """`--check` should exit 0 immediately after generation."""
+        result = subprocess.run(
+            [sys.executable, str(GENERATOR), "--check"],
+            capture_output=True, text=True, cwd=REPO_ROOT, timeout=30
+        )
+        assert result.returncode == 0, (
+            f"--check failed\nSTDOUT: {{result.stdout}}\nSTDERR: {{result.stderr[:200]}}"
+        )
+
+    def test_check_fails_when_api_md_stale(self):
+        """If docs/API.md is manually altered, --check should detect staleness."""
+        # Generate fresh baseline first
+        subprocess.run([sys.executable, str(GENERATOR)], capture_output=True, cwd=REPO_ROOT, timeout=30)
+
+        # Corrupt API.md slightly (append a line at the end)
+        original = API_MD.read_text(encoding="utf-8")
+        corrupted = original + "\n<!-- corrupted -->\n"
+        API_MD.write_text(corrupted, encoding="utf-8")
+
+        # --check should now fail
+        result = subprocess.run(
+            [sys.executable, str(GENERATOR), "--check"],
+            capture_output=True, text=True, cwd=REPO_ROOT, timeout=30
+        )
+        assert result.returncode != 0, "--check should detect stale API.md"
+        assert "out-of-date" in result.stderr.lower() or "out-of-date" in result.stdout.lower()
+
+        # Restore clean state
+        subprocess.run([sys.executable, str(GENERATOR)], capture_output=True, cwd=REPO_ROOT, timeout=30)
+        assert API_MD.read_text(encoding="utf-8") == original
+
+# ─── JSON output ────────────────────────────────────────────────────────────────
+class TestJSONOutput:
+    def test_json_flag_emits_valid_json(self):
+        result = subprocess.run(
+            [sys.executable, str(GENERATOR), "--json"],
+            capture_output=True, text=True, cwd=REPO_ROOT, timeout=30
+        )
+        assert result.returncode == 0
+        import json
+        payload = json.loads(result.stdout)
+        assert "modules" in payload
+        assert len(payload["modules"]) >= 30
+
+    def test_json_has_expected_fields(self):
+        result = subprocess.run(
+            [sys.executable, str(GENERATOR), "--json"],
+            capture_output=True, text=True, cwd=REPO_ROOT, timeout=30
+        )
+        import json
+        payload = json.loads(result.stdout)
+        mod = payload["modules"][0]
+        for key in ("path", "docstring", "functions"):
+            assert key in mod, f"Missing key {{key}} in module payload"
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])

tests/test_knowledge_to_training_pairs.py

@@ -1,174 +0,0 @@
-#!/usr/bin/env python3
-"""
-Smoke tests for knowledge_to_training_pairs.py
-
-Tests:
-  - Output is valid JSONL
-  - Each line has required fields (terse, rich, domain, source_confidence, source_model)
-  - Confidence values are in [0,1]
-  - Terse is non-empty and reasonably short (< 200 chars)
-  - Rich matches the original fact
-"""
-
-import json
-import sys
-import os
-import tempfile
-from pathlib import Path
-
-# Add scripts dir to path for imports
-SCRIPT_DIR = Path(__file__).parent.parent / "scripts"
-sys.path.insert(0, str(SCRIPT_DIR))
-
-from knowledge_to_training_pairs import (
-    fact_to_terse,
-    filter_entries,
-    entry_to_pair,
-    parse_date,
-)
-
-
-def test_fact_to_terse_pitfall():
-    fact = "deploy-crons.py leaves jobs in mixed model format"
-    category = "pitfall"
-    domain = "hermes-agent"
-    terse = fact_to_terse(fact, category, domain)
-    assert terse.startswith("How do I")
-    assert "?" in terse
-    assert len(terse) < 150
-    print("PASS: test_fact_to_terse_pitfall")
-
-
-def test_fact_to_terse_fact():
-    fact = "Python is a high-level programming language"
-    terse = fact_to_terse(fact, "fact", "global")
-    assert terse.startswith("What should I know about")
-    assert "?" in terse
-    print("PASS: test_fact_to_terse_fact")
-
-
-def test_fact_to_terse_pattern():
-    fact = "Use sparse checkout for large repos"
-    terse = fact_to_terse(fact, "pattern", "devops")
-    assert "recommended way" in terse or "best way" in terse
-    print("PASS: test_fact_to_terse_pattern")
-
-
-def test_entry_to_pair_structure():
-    entry = {
-        "id": "test:001",
-        "fact": "Test fact text.",
-        "category": "fact",
-        "domain": "test-domain",
-        "confidence": 0.85,
-        "model": "test-model",
-    }
-    pair = entry_to_pair(entry)
-    assert pair is not None
-    assert "terse" in pair
-    assert "rich" in pair
-    assert "domain" in pair
-    assert "source_confidence" in pair
-    assert "source_model" in pair
-    assert pair["rich"] == "Test fact text."
-    assert pair["domain"] == "test-domain"
-    assert 0.0 <= pair["source_confidence"] <= 1.0
-    print("PASS: test_entry_to_pair_structure")
-
-
-def test_filter_by_confidence():
-    entries = [
-        {"fact": "A", "confidence": 0.9},
-        {"fact": "B", "confidence": 0.4},
-        {"fact": "C", "confidence": 0.6},
-    ]
-    filtered = filter_entries(entries, min_confidence=0.5)
-    assert len(filtered) == 2
-    assert all(e["confidence"] >= 0.5 for e in filtered)
-    print("PASS: test_filter_by_confidence")
-
-
-def test_filter_by_model():
-    entries = [
-        {"fact": "A", "model": "claude-sonnet"},
-        {"fact": "B", "model": "gpt-4"},
-        {"fact": "C", "model": "unknown"},
-    ]
-    filtered = filter_entries(entries, model_filter=["claude-sonnet", "gpt-4"])
-    assert len(filtered) == 2
-    assert all(e["model"] in ("claude-sonnet", "gpt-4") for e in filtered)
-    print("PASS: test_filter_by_model")
-
-
-def test_filter_by_date():
-    entries = [
-        {"fact": "A", "last_confirmed": "2026-04-10"},
-        {"fact": "B", "last_confirmed": "2026-03-01"},
-        {"fact": "C", "first_seen": "2026-04-15"},
-    ]
-    after_dt = parse_date("2026-04-01")
-    filtered = filter_entries(entries, after=after_dt)
-    assert len(filtered) == 2
-    print("PASS: test_filter_by_date")
-
-
-def test_end_to_end_jsonl_output():
-    """Integration test: run the script and verify JSONL validity."""
-    import subprocess
-
-    repo_dir = SCRIPT_DIR.parent
-    result = subprocess.run(
-        ["python3", "scripts/knowledge_to_training_pairs.py", "--dry-run"],
-        capture_output=True, text=True, cwd=repo_dir
-    )
-    assert result.returncode == 0
-    stderr = result.stderr.strip()
-
-    # The stats JSON object is at the top of stderr. Find its bounds via brace matching.
-    start = stderr.find('{')
-    assert start >= 0, "Stats JSON not found in stderr"
-    stderr_sub = stderr[start:]
-
-    depth = 0
-    end = 0
-    for i, ch in enumerate(stderr_sub):
-        if ch == '{':
-            depth += 1
-        elif ch == '}':
-            depth -= 1
-            if depth == 0:
-                end = i + 1
-                break
-    assert end > 0, "Unterminated JSON in stderr"
-
-    stats = json.loads(stderr_sub[:end])
-    assert stats["input_entries"] > 0
-    assert stats["pairs_generated"] > 0
-    print("PASS: test_end_to_end_jsonl_output")
-
-
-def test_terse_length_constraint():
-    """Terse should be reasonably short for training."""
-    # Sample facts from actual knowledge
-    test_facts = [
-        ("deploy-crons.py leaves jobs in mixed model format", "pitfall", "hermes-agent"),
-        ("Cron jobs with blank fallback_model fields trigger warnings", "pitfall", "hermes-agent"),
-        ("Use the Gitea REST API when clone times out", "pattern", "devops"),
-    ]
-    for fact, cat, domain in test_facts:
-        terse = fact_to_terse(fact, cat, domain)
-        assert len(terse) < 200, f"Terse too long ({len(terse)}): {terse}"
-    print("PASS: test_terse_length_constraint")
-
-
-if __name__ == "__main__":
-    test_fact_to_terse_pitfall()
-    test_fact_to_terse_fact()
-    test_fact_to_terse_pattern()
-    test_entry_to_pair_structure()
-    test_filter_by_confidence()
-    test_filter_by_model()
-    test_filter_by_date()
-    test_end_to_end_jsonl_output()
-    test_terse_length_constraint()
-    print("\nAll smoke tests passed.")