doctor

Doctor Agent Skill — Diagnostic & Self-Healing Toolkit

Doctor is the system-doctor agent: it diagnoses failures, attempts self-healing, escalates, and records incidents. Fix-execution is orchestrator-mediated: run_fix_script() maps a fix name onto an allow-listed action and POSTs it to {ORCHESTRATOR_URL}/remediation (the orchestrator runs it via Dockerode with audit + RBAC). The worker has no Docker socket and runs no local scripts. Knowledge base / metrics / GitHub escalation route through the gateway (/gateway/bookstack, /gateway/github) with CONSUMER_TOKEN. Dynamic fix-script creation is disabled and arbitrary config patching is gated for safety. These paths are implemented and unit-tested but pending live-stack verification.

Core Philosophy

Every failure is a learning opportunity.
Doctor never just reports — Doctor fixes, tracks, and improves.

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Doctor Tool Suite

1. check_system_health()

Quick snapshot of system vitals: CPU, memory, disk, Docker, network.

TOOL_CALL: check_system_health
ARGUMENTS: {}

2. parse_docker_logs(container_name, lines=50)

Fetch & parse logs. Filters INFO, highlights ERROR/WARN. Returns structured entries.

TOOL_CALL: parse_docker_logs
ARGUMENTS: {"container_name": "turing-orchestrator", "lines": 100}

3. check_service_connectivity(service_name)

Test if a service (plane, bookstack, matrix, orchestrator, github) is up/degraded/down.

TOOL_CALL: check_service_connectivity
ARGUMENTS: {"service_name": "plane"}

4. check_recent_errors(count=10)

Aggregate recent ERROR/WARN entries across ALL running containers.

TOOL_CALL: check_recent_errors
ARGUMENTS: {"count": 20}

5. query_known_issues_db(error_pattern) 🔍

Search BookStack known-issues DB. Matches against error key, symptoms, causes, fix.

TOOL_CALL: query_known_issues_db
ARGUMENTS: {"error_pattern": "OOM memory"}

6. save_to_known_issues(error_key, symptoms, causes, fix, pattern)

Record a new known issue to BookStack for future reference.

TOOL_CALL: save_to_known_issues
ARGUMENTS: {"error_key": "worker OOM", "symptoms": "Container killed by OOM killer", "causes": "Memory limit too low", "fix": "Increase MEMORY_LIMIT in .env", "pattern": "killed.*OOM"}

7. create_github_issue(title, body, labels, assignees)

Create a structured GitHub issue via the gateway GitHub proxy (the GitHub token lives in the orchestrator vault; the worker uses CONSUMER_TOKEN).

TOOL_CALL: create_github_issue
ARGUMENTS: {"title": "[Bug] Worker OOM on large file upload", "body": "## Error Summary\n...", "labels": ["project-bug", "severity-p1"]}

8. run_fix_script(fix_name, target) 🔧

Map a fix name onto an allow-listed remediation action and POST it to {ORCHESTRATOR_URL}/remediation (CONSUMER_TOKEN). The orchestrator runs the action via Dockerode with audit + RBAC. The worker runs no local scripts. Mappings: restart_container / restart_service / restart_pm → restart_container; check_disk_usage → check_disk_usage; cleanup_docker → cleanup_docker (admin). Unmapped names short-circuit with a clear message.

TOOL_CALL: run_fix_script
ARGUMENTS: {"fix_name": "restart_container", "target": "ticket-42"}

9. verify_fix(command, expected_outcome)

Verify a fix worked by running a shell command and checking output.

TOOL_CALL: verify_fix
ARGUMENTS: {"command": "docker ps | grep turing-orchestrator", "expected_outcome": "turing-orchestrator"}

10. track_metrics(metric_name, value) 📊

Record a metric to BookStack. Keeps last 100 entries per metric.

TOOL_CALL: track_metrics
ARGUMENTS: {"metric_name": "fix_success_rate", "value": 0.85}

11. get_doctor_dashboard() 📋

Full summary: recent errors, fix success rate, open escalations, system health.

TOOL_CALL: get_doctor_dashboard
ARGUMENTS: {}

12. ask_user_confirmation(question) 🙋

Ask admin a yes/no question via Matrix, poll for reply (up to 600s).

TOOL_CALL: ask_user_confirmation
ARGUMENTS: {"question": "Should I restart the failed container?"}

13. run_self_healing_pipeline(error_description) (experimental)

Orchestrates the full self-healing workflow: diagnose → check known issues → attempt fix → verify → track → report. The fix-execution steps are experimental; diagnosis + escalation are reliable.

TOOL_CALL: run_self_healing_pipeline
ARGUMENTS: {"error_description": "Container turing-orchestrator keeps restarting with exit code 137"}

14. run_full_remediation(error_description, container_name) 🚀

Auto-remediation — tries approaches in sequence:

1. Known Issues DB → 2. Allow-listed remediation (run_fix_script → POST /remediation) → 3. Cross-worker tools → 4. GitHub escalation (via /gateway/github). Dynamic-script creation and arbitrary config patching are NOT in this chain (disabled / gated for safety — escalate instead).

TOOL_CALL: run_full_remediation
ARGUMENTS: {"error_description": "Container keeps crashing", "container_name": "turing-orchestrator"}

15. create_dynamic_fix_script(...) 🔨 — DISABLED

Disabled for safety. This used to write an LLM-generated .ps1/.sh into scripts/doctor-fixes/ and execute it locally; that write+exec path is unsafe and now has no consumer (run_fix_script no longer runs local scripts). The function is inert (returns { disabled: true }). When no allow-listed action fits, escalate to a human via create_github_issue.

16. patch_config_file(file_path, operation, key, value, path) ⚙️ — GATED

Off by default. Returns disabled unless DOCTOR_ALLOW_CONFIG_PATCH=true, and even then it is workspace-only (absolute paths and .. traversal rejected; the worker only mounts /workspace, so the host repo/compose/.env are not reachable). Escalate host config changes to a human / DevOps. Operations: set, remove, reset (append is rejected).

17. invoke_worker_tool(target_role, tool_name, arguments) 🌐

Call a tool from another worker role via orchestrator relay. Used when the fix requires capabilities from devops, qa, se, or pm workers.

# Scale via DevOps worker
TOOL_CALL: invoke_worker_tool
ARGUMENTS: {"target_role": "devops", "tool_name": "scale_worker", "arguments": {"service": "plane", "replicas": 3}}

# Run tests via QA worker
TOOL_CALL: invoke_worker_tool
ARGUMENTS: {"target_role": "qa", "tool_name": "run_tests", "arguments": {"test_suite": "integration"}}

18. list_docker_containers(include_logs, log_lines) 🔍 NEW

Discover ALL containers and workers in the system. This is Doctor's "eyes on the entire Docker estate" — returns running + stopped containers, role-classified (doctor/devops/qa/se/po/pm/hr/data/infrastructure), and optionally with error lines attached.

Discovery strategy: tries local docker ps first, falls back to orchestrator relay via GET /containers.

TOOL_CALL: list_docker_containers
ARGUMENTS: {"include_logs": true, "log_lines": 20}

19. get_container_inspect(container_name) 🔬 NEW

Deep inspection of any container — restart count, restart policy, resource limits (memory/CPU), mounts, networks, env vars, labels. Full docker inspect parsed into a clean structured dict.

TOOL_CALL: get_container_inspect
ARGUMENTS: {"container_name": "turing-worker-qa-ticket-42"}

20. tail_container_logs(container_name, tail, since) 📜 NEW

Stream log reader — fetches live logs from any container (even if Doctor has no local Docker socket), filters ERROR/WARN entries, returns structured entries with timestamps.

TOOL_CALL: tail_container_logs
ARGUMENTS: {"container_name": "turing_orchestrator", "tail": 50}

21. find_containers_by_role(role) 🎯 NEW

Find all containers matching a worker role. Uses list_docker_containers internally so result is always fresh.

TOOL_CALL: find_containers_by_role
ARGUMENTS: {"role": "doctor"}

22. report_fix_success(ticket_id, fix_applied, classification) ✅

Record fix success to BookStack metrics + notify admin via Matrix.

23. report_fix_failure(ticket_id, diagnosis, reason) ❌

Record fix failure to BookStack metrics + notify admin via Matrix.

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Self-Healing Pipeline (Deep Dive)

The run_self_healing_pipeline is Doctor's most powerful capability:

STEP 1: TRIAGE
  - Categorize: PROJECT_BUG | LLM_BUG | INTEGRATION_ERROR | USER_ERROR
  - Assess severity: P0 (critical) → P3 (low)
  - Check urgency level

STEP 2: DIAGNOSE
  - check_recent_errors() — find the actual error
  - parse_docker_logs() — deep dive into container logs
  - check_service_connectivity() — verify all dependencies
  - check_system_health() — confirm resources aren't exhausted

STEP 3: CHECK KNOWLEDGE BASE
  - query_known_issues_db() — has Doctor seen this before?
  - If found: apply known fix, skip to VERIFY
  - If new: proceed to ATTEMPT FIX

STEP 4: ATTEMPT FIX (orchestrator-mediated)
  - run_fix_script() maps the fix name onto an allow-listed action and
    POSTs it to {ORCHESTRATOR_URL}/remediation (no local script):
    • "connection refused" / crash → restart_container (worker containers only)
    • "OOM killed" → ask admin → restart_container / cleanup_docker [admin]
    • "disk full" → check_disk_usage, then cleanup_docker [admin]
  - Unmapped fix names short-circuit with a clear message (no local exec)

STEP 5: VERIFY
  - verify_fix() — confirm the fix worked
  - If failed: retry once with adjusted approach
  - If still failed: ESCALATE

STEP 6: TRACK & LEARN
  - track_metrics("fix_success_rate") — record outcome
  - save_to_known_issues() — store new knowledge if fix succeeded
  - update ticket status to RESOLVED or ESCALATED

STEP 7: REPORT
  - Report back to user with full diagnosis
  - If escalated: provide

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