mmccalla

Use when reviewing code before merge to assess correctness, tests, maintainability, security and user impact.

Use when reviewing plans, recommendations, prioritisation, risk registers, retrospectives or agent outputs for judgement distortion from cognitive bias — not for checking whether an argument's premises validly support its conclusion.

Use when evaluating whether premises in plans, ADRs, reviews, security justifications or agent recommendations validly support their conclusions — for logical fallacies, not judgement distortion from cognitive bias.

Use when a coding agent needs robust problem solving, explicit decomposition, alternative-path exploration, program-aided reasoning, ReAct loops, or self-correction.

Use when generated code, plans, tests, prompts or architecture need critique, repair and verification before completion; especially for coding tasks requiring self-review, test-driven repair or quality gates.

Identifies risks, scores likelihood and impact, selects treatment, assigns owners and review cadence. Use when building or updating a risk register, treating agent autonomy risks, or deciding mitigate, transfer, accept or avoid.

Identifies assets, trust boundaries, threats and mitigations for systems and agents. Use when designing security-sensitive features, reviewing attack surface, or planning abuse-case tests.

Applies WCAG 2.2 AA-aligned accessibility checks to interfaces, forms, dashboards and components. Use when building or reviewing any user-facing UI, content, or agent supervision screen.

Governs AI models through inventory, purpose, risk tier, approval, monitoring, drift, kill-switch and retirement. Use when introducing, changing or operating models in production or agent workflows.

Applies an Asimov-inspired hierarchy of AI safety laws when material AI or instruction risk is present. Use when harm, unlawful requests, authority conflicts, or safety trade-offs need an explicit law hierarchy. Also known as apply_laws_of_AI.

Use when implementing input validation, output filtering, tool restrictions, policy enforcement, secure coding controls, destructive-tool guardrails, approval gates, or safe agent behaviour.

Use when starting a session or deciding which local skill applies; acts as the meta-skill for discovering and loading the smallest relevant skill.

Use when measuring coding-agent quality, RAG evaluation, regression risk, latency, cost, reliability, safety, or production performance for agent systems.

Designs ontology-driven knowledge graphs for explainable KG-RAG. Use when modelling semantic graphs, ontologies, or graph schemas for retrieval.

Applies SRE practices for production reliability, service ownership, resilience, toil reduction and operability. Use when owning production services, defining SLOs, or improving operational maturity.

Applies WCAG 2.2 AA-aligned accessibility checks to interfaces, forms, dashboards and components. Use when building or reviewing any user-facing UI, content, or agent supervision screen.