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lint-and-validate

Automatic quality control, linting, and static analysis procedures. Use after every code modification to ensure syntax correctness and project standards. Triggers onKeywords: lint, format, check, validate, types, static analysis.

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SKILL.md

Full skill instructions

Lint and Validate Skill

MANDATORY: Run appropriate validation tools after EVERY code change. Do not finish a task until the code is error-free.

Procedures by Ecosystem

Node.js / TypeScript
  1. Lint/​Fix: npm run lint or npx eslint "path" --fix
  2. Types: npx tsc --noEmit
  3. Security: npm audit --audit-level=high
Python
  1. Linter (Ruff): ruff check "path" --fix (Fast & Modern)
  2. Security (Bandit): bandit -r "path" -ll
  3. Types (MyPy): mypy "path"

The Quality Loop

  1. Write/​Edit Code
  2. Run Audit: npm run lint && npx tsc --noEmit
  3. Analyze Report: Check the "FINAL AUDIT REPORT" section.
  4. Fix & Repeat: Submitting code with "FINAL AUDIT" failures is NOT allowed.

Error Handling

  • If lint fails: Fix the style or syntax issues immediately.
  • If tsc fails: Correct type mismatches before proceeding.
  • If no tool is configured: Check the project root for .eslintrc, tsconfig.json, pyproject.toml and suggest creating one.

Strict Rule: No code should be committed or reported as "done" without passing these checks.

Scripts

ScriptPurposeCommand
scripts/​lint_runner.pyUnified lint checkpython scripts/​lint_runner.py <project_path>
scripts/​type_coverage.pyType coverage analysispython scripts/​type_coverage.py <project_path>

AGI Framework Integration

Qdrant Memory Integration

Before executing complex tasks with this skill:

python3 execution/​memory_manager.py auto --query "<task summary>"

Decision Tree:

  • Cache hit? Use cached response directly — no need to re-process.
  • Memory match? Inject context_chunks into your reasoning.
  • No match? Proceed normally, then store results:
python3 execution/​memory_manager.py store \
  --content "Description of what was decided/​solved" \
  --type decision \
  --tags lint-and-validate <relevant-tags>

Note: Storing automatically updates both Vector (Qdrant) and Keyword (BM25) indices.

Agent Team Collaboration

  • Strategy: This skill communicates via the shared memory system.
  • Orchestration: Invoked by orchestrator via intelligent routing.
  • Context Sharing: Always read previous agent outputs from memory before starting.

Local LLM Support

When available, use local Ollama models for embedding and lightweight inference:

  • Embeddings: nomic-embed-text via Qdrant memory system
  • Lightweight analysis: Local models reduce API costs for repetitive patterns