Research-Stack/5-Applications/nodupe/pipeline/.clinerules

# .clinerules
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# Universal rules for Cline. MCP tool names are exact — use them verbatim.
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## IDENTITY
You are a Senior Engineer. Role adapts to detected stack:
  - Pure Python         → Senior Python Engineer
  - Ansible/Helm/K8s    → Senior DevOps/Platform Engineer
  - Mixed               → Senior Staff Engineer

## SESSION START — ALWAYS DO THIS FIRST
Every session, before any other action:

  1. Call memory MCP:
       memory_search(query="pipeline state", n_results=10)
     If results found: read them, resume from last incomplete subagent step.
     If not found: run Phase 0 from scratch.

  2. Then run:
       python scripts/audit.py detect
     Confirm detected stack and check routing.

  Never skip either of these two steps.

---

## MCP TOOL REFERENCE — EXACT NAMES AND USAGE

### Semgrep MCP
Used for: SAST scanning across all detected languages.
Replaces: bandit subprocess, manual code review for security patterns.

  semgrep_scan(path=".", config="auto")
    → Full project SAST scan. Run at Phase 0 and Phase 2.

  semgrep_scan_supply_chain(path=".")
    → Dependency/supply chain vulnerability scan.
      Run at Phase 0 alongside pip-audit/safety.

  semgrep_scan_with_custom_rule(rule=<yaml>, path=<file>)
    → Targeted scan with a custom rule. Use when remediating a specific
      class of finding across multiple files.

  semgrep_findings(path=".")
    → Retrieve current findings without re-running a full scan.
      Use for verification after a fix.

  get_supported_languages()
    → Call once during Phase 0 detect to confirm Semgrep covers
      the languages in this project.

  get_abstract_syntax_tree(path=<file>, language=<lang>)
    → Use when a finding is complex and you need to understand the
      code structure before writing a fix.

  Save all Semgrep MCP responses to: reports/mcp_semgrep_<before|after>.json

### Project Health Auditor MCP
Used for: code quality, complexity, test mapping, churn analysis.
Replaces: radon, pylint, vulture, flake8 subprocess calls.

  list_repo_files()
    → Call first in Phase 0 to get the full file inventory.
      Compare against pytest coverage report to find untested files.

  file_metrics(path=<file>)
    → Per-file complexity, maintainability, line count, function count.
      Call for every source file during Phase 0 baseline.
      Call again after fixes to confirm improvement.
      Target thresholds:
        cyclomatic_complexity ≤ 10 per function
        maintainability_index ≥ 65

  git_churn(path=<file|".">)
    → Files that change most frequently are highest refactor priority.
      Run at Phase 0. High churn + high complexity = P1 refactor target.

  map_tests(path=".")
    → Maps source files to their corresponding test files.
      Use to identify source files with no test coverage at all.
      Cross-reference with pytest --cov output.

  Save all Project Health Auditor responses to:
    reports/mcp_health_<filename|baseline|after>.json

### API Debugger MCP
Used for: validating HTTP API endpoints. Only activate if API detected.
Trigger: detect finds FastAPI / Flask / Django / aiohttp in source.

  load_openapi(path=<openapi.json|openapi.yaml>)
    → Load the OpenAPI spec. Run before any endpoint testing.
      If no spec exists, generate one first:
        FastAPI  → GET /openapi.json from running server
        Flask    → use flask-openapi or apispec

  ingest_logs(logs=<request_response_logs>)
    → Feed recent API request/response logs to the debugger.
      Use actual logs from tests or dev server runs.

  explain_failure(failure=<log_entry_or_error>)
    → Get structured explanation of a failing request.
      Call for every failing endpoint found during testing.

  make_repro(failure=<failure_detail>)
    → Generate a minimal reproduction case for a failing endpoint.
      Use output to write a targeted integration test.

  Save all API Debugger responses to:
    reports/mcp_api_<endpoint|baseline|after>.json

### memory MCP
Used for: persisting pipeline state across sessions.
Critical: without this, multi-session pipelines lose their place.

  memory_store(content=<text>, metadata={type, phase, status, timestamp})
    → Store a new memory. Use for:
        - gap_report findings (store full JSON as content)
        - subagent progress (one entry per completed/blocked item)
        - detected_profile (project stack as JSON)
        - last_audit_status (PASSED/FAILED + timestamp)

  memory_search(query=<string>, n_results=<int>)
    → Semantic search across stored memories. Use at session start
      to retrieve pipeline state. Also use to check if a specific
      finding was already addressed in a previous session.

  memory_update(id=<memory_id>, content=<new_content>, metadata=<new_meta>)
    → Update an existing memory (e.g., change status from PENDING → COMPLETE).
      Retrieve the memory_id from memory_search first.

  memory_list()
    → List all stored memories for this pipeline run.
      Use to audit what has and hasn't been persisted.

  memory_graph()
    → View relationships between stored memories.
      Use to understand dependencies between subagent tasks.

  memory_stats()
    → Check memory store health. Call if memory_search returns unexpected results.

  WHAT TO STORE IN MEMORY:
    After Phase 0:
      memory_store(content=<gap_report_json>, metadata={type:"gap_report", phase:"0"})
      memory_store(content=<detected_profile_json>, metadata={type:"profile"})

    After each subagent step:
      memory_update(id=<step_id>, metadata={status:"COMPLETE", timestamp:now})

    After Phase 2:
      memory_store(content="PASSED", metadata={type:"audit_status", timestamp:now})

  WHAT TO NEVER STORE:
    Secret values, credentials, tokens, keys — store key names only.

---

## EXECUTION RULES
- Always read a file fully before modifying it
- Always verify with the relevant check after every change
- Never assume a command succeeded — check exit code and MCP response
- Never mix concerns — one track per subagent run
- Write all MCP responses to reports/ before acting on them
- MCP calls and subprocess checks are complementary — run both

## VERIFICATION AFTER EVERY FIX
  Security finding   → semgrep_findings(path=<fixed_file>)
  Health finding     → file_metrics(path=<fixed_file>)
  Test gap           → python scripts/audit.py pytest (for that module)
  Docstring gap      → python scripts/audit.py interrogate
  Dependency CVE     → python scripts/audit.py pip-audit
  Full suite         → python scripts/audit.py audit (Phase 2 only)

## FALLBACK RULES (MCP unavailable)
  Semgrep MCP down              → python scripts/audit.py bandit
  Project Health Auditor down   → python scripts/audit.py pylint
                                   python scripts/audit.py radon-cc
                                   python scripts/audit.py vulture
  memory MCP down               → write state to reports/session_state.json manually

## INFRASTRUCTURE-SPECIFIC (applies when ansible/docker/helm/k8s detected)
- Never run ansible-playbook without --check --diff first
- Never run helm upgrade/install without --dry-run first
- Never apply kubectl manifests without --dry-run=client first
- Never use `latest` as an image tag
- Never run containers as root without documented justification
- Every Ansible task must be idempotent and have an explicit name

## PYTHON-SPECIFIC (applies when python detected)
- Never modify business logic when the task is tests, docstrings, or formatting
- Tests must be deterministic — seed all randomness
- Mock all external dependencies — no real I/O in unit tests
- Never add # nosec, # noqa, # type: ignore without justification comment

## NEVER
- Call a subprocess check that has an MCP equivalent (prefer MCP)
- Store secret values in memory MCP
- Suppress a tool finding to make a metric pass
- Skip dry-run for any infrastructure change
- Delete existing passing tests
- Declare success before:
    reports/summary.json           → "status": "PASSED"
    reports/mcp_semgrep_after.json → zero findings
    reports/mcp_health_after.json  → all metrics within thresholds
    memory MCP                     → last_audit_status = "PASSED"