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MCP AI Agent Guidelines

Skills Overview

What Are Skills?

Section titled “What Are Skills?”

Skills are the internal workflow assets beneath the 20 public instruction tools. Consumers never call skills directly — they invoke an instruction tool which internally orchestrates the right skills.

102 skills · 18 domains · 0 orphans (verified by scripts/verify_matrix.py)

Skill Domains

Section titled “Skill Domains”
Requirements (4) req-* — Analysis, scope, ambiguity detection, acceptance criteria
Architecture (4) arch-* — System, reliability, scalability, security design
Quality (5) qual-* — Code analysis, review, performance, security, refactoring priority
Debugging (4) debug-* — Assistant, root cause, reproduction, postmortem
Documentation (4) doc-* — Generator, README, API reference, runbook
Evaluation (5) eval-* — Prompt, output grading, variance, design, benchmark
Benchmarking (3) bench-* — Analyzer, blind comparison, eval suite
Workflows (3) flow-* — Orchestrator, context handoff, mode switching
Governance (7) gov-* — Policy, compliance, guardrails, prompt-injection hardening
Orchestration (4) orch-* — Agent orchestrator, delegation, multi-agent, synthesis
Prompting (4) prompt-* — Engineering, chaining, refinement, hierarchy
Research (4) synth-* — Comparative, research, recommendation, engine
Strategy (4) strat-* — Advisor, roadmap, prioritization, tradeoff
Resilience (5) resil-* — Homeostatic, membrane, voter, replay, clone-mutate
Leadership (7) lead-* — Capability mapping, roadmap, exec briefing, mentoring

Instruction–Skill Coverage Graph

Section titled “Instruction–Skill Coverage Graph”

The graph below shows which instructions invoke which skill domains. Auto-generated from src/workflows/workflow-spec.ts.

flowchart LR

    subgraph INSTRUCTIONS["Instructions"]
        adapt["adapt"]
        bootstrap["bootstrap"]
        debug["debug"]
        design["design"]
        document["document"]
        enterprise["enterprise"]
        evaluate["evaluate"]
        govern["govern"]
        implement["implement"]
        meta_routing["meta-routing"]
        orchestrate["orchestrate"]
        physics_analysis["physics-analysis"]
        plan["plan"]
        prompt_engineering["prompt-engineering"]
        refactor["refactor"]
        research["research"]
        resilience["resilience"]
        review["review"]
        testing["testing"]
    end

    subgraph D_req["Requirements"]
        req_analysis["req-analysis"]
        req_scope["req-scope"]
        req_ambiguity["req-ambiguity-detection"]
        req_acceptance["req-acceptance-criteria"]
    end

    subgraph D_arch["Architecture"]
        arch_system["arch-system"]
        arch_reliability["arch-reliability"]
        arch_scalability["arch-scalability"]
        arch_security["arch-security"]
    end

    subgraph D_qual["Quality"]
        qual_review["qual-review"]
        qual_code["qual-code-analysis"]
        qual_perf["qual-performance"]
        qual_security["qual-security"]
        qual_refactor["qual-refactoring-priority"]
    end

    subgraph D_debug["Debug"]
        debug_assistant["debug-assistant"]
        debug_root["debug-root-cause"]
        debug_repro["debug-reproduction"]
        debug_post["debug-postmortem"]
    end

    subgraph D_gov["Governance"]
        gov_injection["gov-prompt-injection-hardening"]
        gov_policy["gov-policy-validation"]
        gov_data["gov-data-guardrails"]
        gov_model["gov-model-governance"]
        gov_compat["gov-model-compatibility"]
        gov_regulated["gov-regulated-workflow-design"]
        gov_compliance["gov-workflow-compliance"]
    end

    subgraph D_orch["Orchestration"]
        orch_agent["orch-agent-orchestrator"]
        orch_delegation["orch-delegation"]
        orch_multi["orch-multi-agent"]
        orch_synthesis["orch-result-synthesis"]
    end

    subgraph D_resil["Resilience"]
        resil_homeostatic["resil-homeostatic"]
        resil_membrane["resil-membrane"]
        resil_voter["resil-redundant-voter"]
        resil_replay["resil-replay"]
        resil_clone["resil-clone-mutate"]
    end

    subgraph D_adapt["Adaptive (gated)"]
        adapt_aco["adapt-aco-router"]
        adapt_anneal["adapt-annealing"]
        adapt_hebbian["adapt-hebbian-router"]
        adapt_physarum["adapt-physarum-router"]
        adapt_quorum["adapt-quorum"]
    end

    subgraph D_qm["Quantum Mechanics (gated)"]
        qm_super["qm-superposition-generator"]
        qm_entangle["qm-entanglement-mapper"]
        qm_collapse["qm-measurement-collapse"]
        qm_tunnel["qm-tunneling-breakthrough"]
        qm_wave["qm-wavefunction-coverage"]
        qm_more["... +10 more qm-* skills"]
    end

    subgraph D_gr["General Relativity (gated)"]
        gr_debt["gr-spacetime-debt-metric"]
        gr_horizon["gr-event-horizon-detector"]
        gr_geodesic["gr-geodesic-refactor"]
        gr_lens["gr-gravitational-lensing-tracer"]
        gr_more["... +11 more gr-* skills"]
    end

    design --> D_req
    design --> D_arch
    implement --> D_req
    implement --> D_arch
    research --> D_qual
    review --> D_qual
    review --> D_gov
    govern --> D_gov
    resilience --> D_resil
    orchestrate --> D_orch
    adapt --> D_adapt
    physics_analysis --> D_qm
    physics_analysis --> D_gr
    refactor --> D_qual
    debug --> D_debug
    bootstrap --> D_req
    plan --> D_arch
    evaluate --> D_qual
    enterprise --> D_gov
    testing --> D_qual
    prompt_engineering --> D_qual

How Skills Are Invoked

Section titled “How Skills Are Invoked”

Skills are dispatched by tier in src/tools/skill-handler.ts:

  • Physics tier (qm-*, gr-*): Requires ENABLE_PHYSICS_SKILLS=true
  • Governance tier (gov-*): Optional human-in-the-loop via ENABLE_GOVERNANCE_STRICT
  • Adaptive tier (adapt-*): Requires ENABLE_ADAPTIVE_ROUTING=true
  • Core tier: Everything else, always available

See The Skill System for the full architecture.