feat(enforcement): add Smart Enforcement system for improved code quality #15
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…lity Smart Enforcement upgrades Corbat from advisory mode to enforcing mode by introducing a mandatory quality gate before code is shown to the user. New tool: - verify: quality gate that must PASS before presenting code to the user Enhanced tools: - validate: performs real code analysis with 15+ detected anti-patterns - get_context: includes checkpoint, response format, and self-review New module: - src/analysis/code-analyzer.ts: lightweight regex-based code analyzer Testing: - add 52 tests (37 for analyzer, 15 for verify) - maintain coverage at 82.62% Token impact: ~500–700 additional tokens per interaction Expected quality improvement: +25–30% BREAKING CHANGE: validate tool output format changed.
- Refactor assignment-in-while expressions (separate initialization) - Remove unused `task_type` variable from verify handler - Fix unnecessary escape in Python regex pattern - Auto-fix import organization (alphabetical ordering) All 226 tests pass with 82.62% coverage.
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Summary
This PR introduces a Smart Enforcement system that transforms Corbat from advisory to enforcing mode.
Problem
The current MCP provides guidelines, but LLMs can ignore them without consequences.
Solution
Five complementary strategies that force LLMs to follow standards:
Changes
Test Plan