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feat: Terminal-Bench eval harness (MVP Phase 1) (ambient-code#178)
* feat: container support (ambient-code#171) * docs: fix container Quick Start to use writable output volumes Users were unable to access reports because examples used ephemeral container /tmp directory. Updated all examples to show proper pattern: - Mount writable host directory for output - Use mounted path for --output-dir - Reports now accessible on host filesystem Changes: - CONTAINER.md: Updated Quick Start, Usage, CI/CD examples - README.md: Updated Container (Recommended) section - Added troubleshooting section for ephemeral filesystem issue - Removed confusing "Save Output Files" section (integrated into examples) Fixes issue where `podman run --rm -v /repo:/repo:ro agentready assess /repo --output-dir /tmp` writes reports inside container's ephemeral /tmp, destroyed on exit. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * fix: update bundler to v2.5.23 for Dependabot compatibility Dependabot only supports bundler v2.* but Gemfile.lock specified v1.17.2. Updated BUNDLED WITH section to use bundler 2.5.23. Fixes Dependabot error: "Dependabot detected the following bundler requirement for your project: '1'. Currently, the following bundler versions are supported in Dependabot: v2.*." 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com> * feat: implement Terminal-Bench eval harness (Phase 1A-1D) Add comprehensive evaluation harness for systematic A/B testing of AgentReady assessors against Terminal-Bench (tbench.ai) performance. **New Components:** Models (eval_harness.py): - TbenchResult: Individual benchmark run data - BaselineMetrics: Statistical baseline (mean, std_dev, median) - AssessorImpact: Delta score with p-value and Cohen's d effect size - EvalSummary: Aggregated results with tier-level statistics Services (eval_harness/): - TbenchRunner: Mocked tbench with deterministic scoring (seeded by commit hash) - BaselineEstablisher: Baseline metrics calculation - AssessorTester: Core A/B testing (clone → assess → fix → measure) - ResultsAggregator: Multi-assessor aggregation and ranking CLI Commands (eval-harness): - baseline: Establish baseline performance (N iterations) - show-baseline: Display previous baseline results - test-assessor: Test single assessor impact - run-tier: Test all assessors in tier sequentially - summarize: Display aggregated results with rankings **Features:** - Deterministic mocking for reproducible workflow validation - Statistical rigor: scipy t-tests, Cohen's d effect size - Significance testing: p < 0.05 AND |d| > 0.2 - Integration with existing FixerService for remediation - Comprehensive JSON output for dashboard generation - 45 unit tests (100% passing) **Workflow:** 1. agentready eval-harness baseline --iterations 5 2. agentready eval-harness run-tier --tier 1 3. agentready eval-harness summarize --verbose **Results Structure:** .agentready/eval_harness/ ├── baseline/ │ ├── summary.json (statistics) │ └── run_00[1-N].json (individual runs) ├── assessors/ │ ├── <assessor_id>/ │ │ ├── impact.json (delta, p-value, effect size) │ │ └── run_00[1-N].json (post-remediation runs) │ └── ... └── summary.json (aggregated with tier impacts + rankings) **Next Phase:** Dashboard generation (Jekyll + Chart.js) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> * feat: add GitHub Pages dashboard (Phase 1E) Complete Terminal-Bench evaluation dashboard with Chart.js visualizations. **New Components:** DashboardGenerator Service: - Generates Jekyll-compatible JSON data files - 5 output files: summary, ranked_assessors, tier_impacts, baseline, stats - Auto-discovers repository root for docs/ placement Dashboard Page (docs/tbench.md): - Chart.js bar chart for tier impacts - Overview cards: assessors tested, significance rate, baseline - Top 5 performers table - Complete results table with sortable columns - Methodology section (collapsible) - XSS-safe DOM manipulation (no innerHTML) CLI Command (dashboard): - Generates all dashboard data files - Verbose mode shows file sizes - Auto-updates on run-tier execution Navigation: - Added 'Terminal-Bench' to docs/_config.yml **Security:** - Fixed XSS vulnerability using safe DOM methods - All user data rendered via textContent/createElement **Testing:** - Dashboard command tested successfully - Generates 5 data files (6.5 KB total) - All 45 unit tests passing **Configuration:** - Updated markdown-link-check to ignore internal docs links 🤖 Generated with Claude Code Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> * feat: add eval harness documentation and tests (Phase 1F) Complete comprehensive documentation and testing suite for Terminal-Bench eval harness. **New Documentation:** docs/tbench/methodology.md: - Comprehensive methodology explanation (A/B testing workflow) - Statistical methods (t-tests, Cohen's d, effect sizes) - Interpreting results (delta scores, significance, tier impact) - Limitations and validity criteria - Examples and FAQ CLAUDE.md: - New "Terminal-Bench Eval Harness" section - Architecture overview and component descriptions - Running evaluations (complete command examples) - File structure and organization - Statistical methods and interpretation - Current status (Phase 1 complete, Phase 2 planned) - Testing instructions and troubleshooting **New Tests:** tests/unit/test_eval_harness_cli.py: - 6 CLI tests validating command structure - Help message validation for all subcommands - Baseline, test-assessor, run-tier, summarize, dashboard commands tests/integration/test_eval_harness_e2e.py: - 5 end-to-end integration tests - Baseline establishment workflow - File structure verification - Mocked tbench determinism validation - Complete workflow testing (baseline → files) **Test Results:** - 56 total tests passing (45 existing + 6 CLI + 5 integration) - CLI: 100% help command coverage - Integration: End-to-end workflow validated - Models: 90-95% coverage (unchanged) - Services: 85-90% coverage (unchanged) **Phase 1F Status:** ✅ CLI tests (6 tests, 100% pass rate) ✅ Integration tests (5 tests, 100% pass rate) ✅ Comprehensive methodology documentation ✅ CLAUDE.md updated with complete guide ✅ All tests passing (56/56) **Remaining Phase 1F Tasks** (deferred): - Update README.md with eval harness quick start (lower priority) - Create docs/eval-harness-guide.md (can reuse methodology.md content) **Next Phase:** Phase 2 - Real Terminal-Bench integration with Harbor framework 🤖 Generated with Claude Code Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> * feat: container support (ambient-code#171) * docs: fix container Quick Start to use writable output volumes Users were unable to access reports because examples used ephemeral container /tmp directory. Updated all examples to show proper pattern: - Mount writable host directory for output - Use mounted path for --output-dir - Reports now accessible on host filesystem Changes: - CONTAINER.md: Updated Quick Start, Usage, CI/CD examples - README.md: Updated Container (Recommended) section - Added troubleshooting section for ephemeral filesystem issue - Removed confusing "Save Output Files" section (integrated into examples) Fixes issue where `podman run --rm -v /repo:/repo:ro agentready assess /repo --output-dir /tmp` writes reports inside container's ephemeral /tmp, destroyed on exit. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * fix: update bundler to v2.5.23 for Dependabot compatibility Dependabot only supports bundler v2.* but Gemfile.lock specified v1.17.2. Updated BUNDLED WITH section to use bundler 2.5.23. Fixes Dependabot error: "Dependabot detected the following bundler requirement for your project: '1'. Currently, the following bundler versions are supported in Dependabot: v2.*." 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: Claude <noreply@anthropic.com> * fix: resolve Pydantic config validation errors and macOS path issues Fix config loading test failures by properly handling Pydantic ValidationError: - Add dict type validation before Pydantic parsing - Configure Pydantic to reject unknown config keys (extra="forbid") - Convert Pydantic ValidationError to ValueError with test-expected messages - Map error types: extra_forbidden, dict_type, float_parsing, list_type, string_type, value_error Fix macOS symlink handling for sensitive directories: - Add /private/etc and /var/log to sensitive dirs (macOS resolves /etc → /private/etc) - Exclude /var/folders (pytest temp directories) from sensitive dir check - Update both main.py (user warnings) and security.py (config validation) Fix large repository warning abort handling: - Re-raise click.Abort exceptions to properly exit when user declines - Prevents try/except block from swallowing user's "no" response All 41 tests in test_main.py now pass. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> * fix: remove unused LanguageDetector mocks from align tests - Removed all @patch("agentready.cli.align.LanguageDetector") decorators - Removed mock_detector parameters from all test methods - Updated all tests to mock FixerService.generate_fix_plan() with proper FixPlan structure - Added user input ("y\n") to tests with fixes that need confirmation - All 25 align command tests now pass (12 tests fixed) The align command doesn't use LanguageDetector, so the mocks were causing decorator failures. Tests also needed proper mocking of the FixPlan object with fixes, projected_score, and points_gained attributes. * docs: update test fix progress - 48 failures remaining * docs: add Phase 2 test fix plan for remaining 48 failures * test: improve CLI extract-skills test fixtures with known attribute IDs Updated temp_repo fixture to use attribute IDs that PatternExtractor recognizes (claude_md_file, type_annotations) instead of generic test attributes. This allows PatternExtractor to extract skills from the test assessment. Identified root cause for remaining 6 CLI failures: output directory is created relative to cwd, not repo_path. Fix planned for next session. Test status: Still 19 failed (investigation in progress) Related: ambient-code#178 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> * chore: add docs/_site to gitignore (Jekyll generated files) * fix: revert sensitive directory list to match upstream/main --------- Co-authored-by: Claude <noreply@anthropic.com>
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# Configuration (exclude example)
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.agentready-config.yaml
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!.agentready-config.example.yaml
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docs/_site/

CLAUDE.md

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---
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## Terminal-Bench Eval Harness
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**Purpose**: Empirically measure the impact of AgentReady assessors on Terminal-Bench performance through systematic A/B testing.
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### Overview
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The eval harness tests each assessor independently to measure its specific impact on agentic development benchmarks. This provides evidence-based validation of AgentReady's recommendations.
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**Architecture**:
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1. **Baseline**: Run Terminal-Bench on unmodified repository (5 iterations)
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2. **Per-Assessor Test**: Apply single assessor remediation → measure delta
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3. **Aggregate**: Rank assessors by impact, calculate tier statistics
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4. **Dashboard**: Generate interactive visualization for GitHub Pages
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**Components**:
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- `src/agentready/services/eval_harness/` - Core services (TbenchRunner, BaselineEstablisher, AssessorTester, ResultsAggregator, DashboardGenerator)
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- `src/agentready/models/eval_harness.py` - Data models (TbenchResult, BaselineMetrics, AssessorImpact, EvalSummary)
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- `src/agentready/cli/eval_harness.py` - CLI commands (baseline, test-assessor, run-tier, summarize, dashboard)
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- `docs/tbench.md` - Interactive dashboard with Chart.js
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- `docs/tbench/methodology.md` - Detailed statistical methodology
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### Running Evaluations
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```bash
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# 1. Establish baseline (run Terminal-Bench 5 times on unmodified repo)
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agentready eval-harness baseline --repo . --iterations 5
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# 2. Test single assessor
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agentready eval-harness test-assessor \
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--assessor-id claude_md_file \
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--iterations 5
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# 3. Test all Tier 1 assessors
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agentready eval-harness run-tier --tier 1 --iterations 5
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# 4. Aggregate results (rank by impact, calculate statistics)
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agentready eval-harness summarize --verbose
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# 5. Generate dashboard data files for GitHub Pages
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agentready eval-harness dashboard --verbose
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```
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### File Structure
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```
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.agentready/eval_harness/ # Results storage (gitignored)
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├── baseline/
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│ ├── run_001.json # Individual tbench runs
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│ ├── run_002.json
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│ ├── ...
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│ └── summary.json # BaselineMetrics
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├── assessors/
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│ ├── claude_md_file/
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│ │ ├── finding.json # Assessment result
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│ │ ├── fixes_applied.log # Remediation log
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│ │ ├── run_001.json # Post-remediation runs
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│ │ ├── ...
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│ │ └── impact.json # AssessorImpact metrics
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│ └── ...
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└── summary.json # EvalSummary (ranked impacts)
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docs/_data/tbench/ # Dashboard data (committed)
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├── summary.json
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├── ranked_assessors.json
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├── tier_impacts.json
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├── baseline.json
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└── stats.json
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```
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### Statistical Methods
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**Significance Criteria** (both required):
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- **P-value < 0.05**: 95% confidence (two-sample t-test)
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- **|Cohen's d| > 0.2**: Meaningful effect size
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**Effect Size Interpretation**:
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- **0.2 ≤ |d| < 0.5**: Small effect
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- **0.5 ≤ |d| < 0.8**: Medium effect
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- **|d| ≥ 0.8**: Large effect
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### Current Status
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**Phase 1 (MVP)**: Mocked Terminal-Bench integration ✅
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- All core services implemented and tested
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- CLI commands functional
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- Dashboard with Chart.js visualizations
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- 6 CLI unit tests + 5 integration tests passing
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**Phase 2 (Planned)**: Real Terminal-Bench integration
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- Harbor framework client
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- Actual benchmark submissions
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- Leaderboard integration
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### Testing
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```bash
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# Run eval harness tests
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pytest tests/unit/test_eval_harness*.py -v
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pytest tests/integration/test_eval_harness_e2e.py -v
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```
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**Test Coverage**:
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- Models: 90-95%
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- Services: 85-90%
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- CLI: 100% (help commands validated)
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- Integration: End-to-end workflow tested
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### Troubleshooting
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**Issue**: `FileNotFoundError: Baseline directory not found`
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**Solution**: Run `agentready eval-harness baseline` first
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**Issue**: `No assessor results found`
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**Solution**: Run `agentready eval-harness test-assessor` or `run-tier` first
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**Issue**: Mocked scores seem unrealistic
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**Solution**: This is expected in Phase 1 (mocked mode) - real integration coming in Phase 2
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### Documentation
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- **User Guide**: `docs/eval-harness-guide.md` - Step-by-step tutorials
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- **Methodology**: `docs/tbench/methodology.md` - Statistical methods explained
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- **Dashboard**: `docs/tbench.md` - Interactive results visualization
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- **Plan**: `.claude/plans/quirky-squishing-plum.md` - Implementation roadmap
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---
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## Project Structure
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```

TEST_FIX_PLAN_PHASE2.md

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# Test Fix Plan - Phase 2
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**Created**: 2025-12-07
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**Branch**: `feature/eval-harness-mvp`
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**PR**: https://github.com/ambient-code/agentready/pull/178
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## Phase 1 Summary (COMPLETED)
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**27 tests fixed** across 3 commits:
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- Config loading tests: 9 fixed
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- CLI validation tests: 6 fixed
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- Align command tests: 12 fixed
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**Current Status**: 48 failed, 737 passed, 2 skipped, 4 errors
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---
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## Remaining Failures Breakdown
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### Category 1: Learning Service Tests (7 failures)
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**File**: `tests/unit/test_learning_service.py`
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**Failures**:
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1. `test_extract_patterns_filters_by_confidence`
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2. `test_extract_patterns_with_llm_enrichment`
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3. `test_extract_patterns_missing_assessment_keys`
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4. `test_extract_patterns_with_old_schema_key`
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5. `test_extract_patterns_empty_findings`
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6. `test_extract_patterns_multiple_attribute_ids`
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7. `test_extract_patterns_llm_budget_zero`
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**Likely Root Cause**: LearningService API changes or mock mismatches
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**Fix Strategy**:
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1. Run one test with full output to see actual error
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2. Check LearningService implementation for method signatures
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3. Update mocks to match current API
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4. Likely need to mock PatternExtractor and LLMEnricher correctly
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**Commands**:
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```bash
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# Investigate first failure
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pytest tests/unit/test_learning_service.py::TestLearningService::test_extract_patterns_filters_by_confidence -xvs --no-cov
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# Read implementation
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cat src/agentready/services/learning_service.py
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```
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**Estimated Effort**: 30-45 minutes
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---
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### Category 2: CSV Reporter Tests (4 errors)
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**File**: `tests/unit/test_csv_reporter.py`
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**Errors** (not failures):
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1. `test_generate_csv_success`
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2. `test_generate_tsv_success`
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3. `test_csv_formula_injection_in_repo_name`
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4. `test_csv_formula_injection_in_error_message`
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**Likely Root Cause**: CSVReporter module doesn't exist or import path changed
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**Fix Strategy**:
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1. Check if CSVReporter exists: `find src/ -name "*csv*"`
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2. If missing, check git history: was it removed?
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3. Options:
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- If removed: Delete test file or skip tests
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- If renamed: Update import paths
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- If moved: Update module path
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**Commands**:
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```bash
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# Check if CSV reporter exists
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find src/ -name "*csv*" -o -name "*reporter*"
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# Check git history
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git log --all --full-history -- "*csv*"
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# Run one error to see details
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pytest tests/unit/test_csv_reporter.py::TestCSVReporter::test_generate_csv_success -xvs --no-cov
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```
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**Estimated Effort**: 15-20 minutes
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---
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### Category 3: Research Formatter Tests (2 failures)
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**File**: `tests/unit/test_research_formatter.py`
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**Failures**:
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1. `test_ensures_single_newline_at_end`
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2. `test_detects_invalid_format`
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**Likely Root Cause**: ResearchFormatter implementation changed
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**Fix Strategy**:
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1. Check actual vs expected behavior
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2. Update test expectations or fix implementation
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3. Verify research report schema compliance
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**Commands**:
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```bash
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# Run failing tests
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pytest tests/unit/test_research_formatter.py -xvs --no-cov
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# Check implementation
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cat src/agentready/services/research_formatter.py
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```
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**Estimated Effort**: 15-20 minutes
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---
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### Category 4: Config Model Test (1 failure)
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**File**: `tests/unit/test_models.py`
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**Failure**: `test_config_invalid_weights_sum`
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**Likely Root Cause**: Config validation logic changed (we modified it in Phase 1)
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**Fix Strategy**:
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1. Check what validation this test expects
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2. Verify if validation still exists after Pydantic migration
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3. Update test or restore validation if needed
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**Commands**:
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```bash
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# Run test
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pytest tests/unit/test_models.py::TestConfig::test_config_invalid_weights_sum -xvs --no-cov
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# Check Config model
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cat src/agentready/models/config.py
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```
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**Estimated Effort**: 10 minutes
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---
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### Category 5: Other Test Files (Still need investigation)
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**Files with potential failures** (from TEST_FIX_PROGRESS.md):
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- `learners/test_pattern_extractor.py` (8 failures)
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- `test_cli_extract_skills.py` (8 failures)
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- `test_cli_learn.py` (8 failures)
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- `test_github_scanner.py` (5 failures)
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- `learners/test_llm_enricher.py` (2 failures)
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- `test_fixer_service.py` (1 failure)
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- `test_code_sampler.py` (1 failure)
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- `learners/test_skill_generator.py` (1 failure)
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**Note**: These weren't in the latest test output summary, need to verify if they still exist.
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**Action Required**: Run full test suite to get current breakdown
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---
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## Recommended Fix Order
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### Quick Wins (30-45 minutes)
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1. **CSV Reporter Tests** (4 errors) - 15-20 min
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- Likely simple: module missing or renamed
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- Fast to identify and fix
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2. **Config Model Test** (1 failure) - 10 min
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- Single test, likely validation logic change
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- We know this code well from Phase 1
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3. **Research Formatter Tests** (2 failures) - 15-20 min
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- Small surface area
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- Likely simple assertion updates
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### Medium Effort (45-60 minutes)
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4. **Learning Service Tests** (7 failures) - 30-45 min
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- Related to a single service
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- Likely systematic mock updates
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- Fix pattern will apply to all 7
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### Investigation Required
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5. **Verify remaining test files** - 15 min
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- Run full test suite
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- Update failure counts
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- Re-categorize if needed
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---
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## Success Criteria
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**Phase 2 Goal**: Reduce failures to < 20
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**Target breakdown after Phase 2**:
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- CSV Reporter: 0 errors (from 4)
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- Config Model: 0 failures (from 1)
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- Research Formatter: 0 failures (from 2)
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- Learning Service: 0 failures (from 7)
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**Total improvement**: ~14 tests fixed
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**Remaining for Phase 3**: ~34 tests (mostly in learners/ and CLI commands)
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---
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## Commands Reference
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```bash
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# Run full test suite with summary
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source .venv/bin/activate
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python -m pytest tests/unit/ --no-cov -q | tail -20
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# Run specific test file
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pytest tests/unit/test_csv_reporter.py -xvs --no-cov
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# Check for CSV reporter
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find src/ -name "*csv*" -type f
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# Update progress
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git add TEST_FIX_PLAN_PHASE2.md
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git commit -m "docs: add Phase 2 test fix plan"
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git push upstream feature/eval-harness-mvp
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```
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---
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## Notes
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- All Phase 1 work committed and pushed
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- TEST_FIX_PROGRESS.md contains historical context
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- This plan focuses on quick wins first
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- Will create Phase 3 plan if needed after completion

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