feat: Benchmark Quality Gate (M117)

[hlin99]

Summary

Composite pass/fail quality gate for benchmark data, designed for CI/CD pipeline integration.

Changes

• QualityGate class in quality_gate.py with YAML-configurable GateConfig
• GateCheck, GateConfig, GateResult, GateVerdict Pydantic models
• 5 built-in checks: min_requests, quality_score, outlier_ratio, convergence, load_profile
• Non-zero exit code on FAIL (CI/CD pipeline friendly)
• CLI quality-gate subcommand with --config YAML support, table + JSON output
• Programmatic evaluate_quality_gate() and load_gate_config() APIs
• 23 new tests
• Updated ROADMAP.md (M116 ✅, M117 🔄)

Closes #257

[hlin99-Review-Bot]

✅ Approved by hlin99-Review-Bot

Idea Value: High — composite quality gate is essential for CI/CD pipeline integration. Combining validation, convergence, outlier, and load profile checks into a single pass/fail verdict is the right approach.

Code Quality:

• Clean Pydantic models (GateConfig, GateCheck, GateResult, GateVerdict)
• YAML-configurable thresholds with sensible defaults
• Good separation: core logic in quality_gate.py, CLI in _quality_gate.py
• 23 tests covering models, config loading, evaluator, programmatic API, CLI, and imports
• Non-zero exit on FAIL is CI-friendly
• docs/iterations/current.md updated

All 5 CI checks pass. LGTM.

[hlin99-Review-BotX]

✅ Approved by hlin99-Review-BotX

Idea Value: High — composite quality gate is a natural CI/CD integration point. Combining validation, convergence, outlier, and load profile checks into a single pass/fail verdict with YAML-configurable thresholds is well-designed.

Code Quality:

• Clean Pydantic models (GateConfig, GateCheck, GateResult, GateVerdict)
• Good separation: core quality_gate.py + CLI _quality_gate.py
• YAML config with sensible defaults, graceful warn/fail thresholds
• 23 tests covering models, config, evaluator, programmatic API, CLI, and imports
• Non-zero exit on FAIL is CI-friendly
• docs/iterations/current.md updated

All 5 CI checks pass. Second +1 — ready for merge.

[hlin99-Review-BotX]

✅ Approved by hlin99-Review-BotX

Idea Value: Strong — composite quality gate for CI/CD is a natural fit after the benchmark pipeline milestones. YAML-configurable thresholds and non-zero exit on FAIL make it immediately usable in pipelines.

Code Quality:

• Clean Pydantic models (GateConfig/GateCheck/GateResult/GateVerdict)
• Good separation: core logic in quality_gate.py, CLI in _quality_gate.py
• 5 built-in checks with graduated PASS/WARN/FAIL verdicts
• YAML config loader with sensible defaults
• CLI properly registered with table + JSON output
• docs/iterations/current.md updated
• ROADMAP.md updated (M116 ✅, M117 🔄)
• CI all green (lint + tests 3.10/3.11/3.12)

No issues found. LGTM.

[hlin99-Review-BotX]

✅ Approved (hlin99-Review-BotX)

Idea Value: Strong — composite quality gate for CI/CD pipeline integration is a natural next step after convergence/outlier/load-profile analyzers. Clean design combining existing analyzers into a unified pass/fail verdict.

Code Quality:

• Well-structured Pydantic models (GateConfig, GateCheck, GateResult, GateVerdict)
• 5 checks with sensible PASS/WARN/FAIL thresholds and configurable via YAML
• Clean CLI with table + JSON output, non-zero exit on FAIL (CI-friendly)
• Programmatic evaluate_quality_gate() API with both config-file and kwargs paths
• 23 tests covering models, config loading, evaluator, API, CLI, and public imports
• docs/iterations/current.md and ROADMAP.md properly updated

Minor nit: ROADMAP says '~22 new tests' but actual count is 23. Not blocking.

LGTM 🚀