Skill rating

Audit Skill() refs; detect hubs, isolates, and dangling targets. Use when auditing skills.

Assesses decision reversibility and risk at critical checkpoints. Use when a workflow reaches a high-stakes branch needing escalation check.

Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready to implement.

Contract for the project decision journal (tradeoffs and lessons-learned logs). Use when recording a decision, tradeoff, or lesson, or building a consumer hook.

Formats review deliverables with consistent structure for comparable findings. Use when finalizing any review or analysis that must be shared or compared.

Audits Makefiles for build correctness, portability, and recipe duplication. Use when reviewing a Makefile or before committing Makefile changes.

Bumps versions, updates changelogs, and coordinates version changes across files for releases. Use when preparing a release or bumping the project version.

Detects workflow failures and inefficient patterns then files GitHub issues. Use when a workflow step repeatedly fails or produces inconsistent output.

Orchestrates multi-domain review (code, arch, tests, security) in a single pass. Use when thorough pre-release review is needed.

Scores backlog items with RICE/WSJF/Kano and files GitHub issues for top candidates. Use when triaging a roadmap or prioritizing features for a sprint.

Audits shell scripts for correctness, portability, and common pitfalls. Use when reviewing shell scripts or before committing shell changes.

Runs a three-tier codebase audit (git history, targeted scans, full review) with gating. Use when auditing a codebase before release or after incidents.

Verifies math-heavy code for algorithmic correctness and numerical stability. Use when reviewing scientific algorithms, ML models, or numerical code.

Audits Rust code for unsafe blocks, ownership issues, and Cargo dependency risks. Use when reviewing Rust code or before merging Rust changes.

Evaluates test suites for coverage gaps, TDD/BDD compliance, and anti-patterns. Use when auditing test quality or before a major release.

Evaluates API surface design, consistency, and exemplar alignment. Use when reviewing public API changes or before releasing a new API surface.

Hunts bugs with evidence trails. Use when investigating unexpected behavior or before merging code with potential hidden defects.

Applies NIST/CWE security hardening to Python and Rust code. Use when auditing code for vulnerabilities or proposing concrete security remediations.

Summarizes recent git changes for context recovery after session breaks. Use when resuming work after a gap or handing off to another session.

Runs multi-source research across GitHub, HN, Reddit, arXiv, and Semantic Scholar. Use when surveying a technical topic across multiple channels.

Applies CQRS and Event Sourcing for read/write separation and audit trails. Use when designing systems with complex domain logic or full state-change history.

Designs memory palace structures with spatial layouts and domain organization. Use when creating a new palace or planning knowledge architecture by hand.

Builds session-scoped temporary memory palaces for extended conversations. Use when tracking state across interruptions in a multi-step project.

Selects and routes to the right architecture paradigm. Use when choosing patterns for a new system or comparing trade-offs before making architecture decisions.

Defines testing quality metrics, coverage thresholds, and anti-patterns. Use when establishing test gates or validating a test suite's coverage targets.

Provides auth patterns for API keys, OAuth, and token management. Use when implementing or reviewing service authentication and credential handling.

Searches and navigates stored knowledge in memory palaces. Use when looking for previously stored information or cross-referencing concepts across palaces.

Profiles Python code for performance bottlenecks and memory issues. Use when Python code is slow or when profiling for optimization before a release.

Shapes agent behavior via instruction framing and style transfer. Use when composing dispatch prompts or writing skill instructions for parallel review agents.

Verifies a package exists before install, defending against hallucination and slopsquatting. Use when adding, recommending, or installing a package.

Decompose a session into typed handoff units and recall them later. Use when ending a session or resuming work whose prior state must be recovered.

Python package creation and PyPI distribution via pyproject.toml and entry points. Use when publishing a package or setting up build configuration.

Transforms project briefs into testable specifications with user stories and acceptance criteria. Use after brainstorming, before planning.

Establishes CPU/GPU baselines before resource-intensive operations. Use before builds, training runs, or any task that pins cores or GPUs for over a minute.

Provides sanitization guidelines for external content in skills and hooks. Use when loading GitHub Issues, PRs, WebFetch results, or any untrusted input.

Provides weighted scoring, rubrics, and decision-threshold patterns. Use when designing quality gates, evaluation systems, or decision frameworks.

Generates Mermaid and ASCII diagrams of palace structure, knowledge topology, and synapse connectivity. Use when inspecting or presenting a palace visually.

Delegates tasks to OpenCode (opencode run) via delegation-core. Use when delegation-core selects OpenCode or a provider-agnostic harness is wanted.

Classifies agent tasks into 4 risk tiers (GREEN/YELLOW/RED/CRITICAL). Use when assessing action reversibility before committing to an approach.

Python testing patterns with pytest, fixtures, TDD, mocking, async and integration tests. Use when writing or auditing a Python test suite.

Generates Makefiles with testing, linting, formatting, and automation targets. Use when starting a project or standardizing build automation.

Delegates tasks to the MiniMax CLI (mmx) via delegation-core. Use when delegation-core selects MiniMax or large-context batch work is needed.

Manages Claude Code sessions with naming, checkpointing, and resume strategies. Use when organizing long-running work or resuming across sessions.

Delegates tasks to Gemini CLI implementing delegation-core for Google's models. Use when delegation-core selects Gemini or 1M+ token context is needed.

Pre-implementation gate covering think-first, simplicity, surgical edits, and verifiable goals. Use when starting implementation to verify the approach.

Provides templates and lifecycle patterns for storage and documentation systems. Use when organizing knowledge storage, config lifecycle, or naming conventions.

Async Python patterns via asyncio and aiohttp for I/O-bound concurrency. Use when adding async APIs, handling concurrent I/O, or debugging async code.

Delegates tasks to the OpenAI Codex CLI (codex exec) via delegation-core. Use when delegation-core selects Codex or OpenAI credentials are already configured.

Guides when to ask clarifying questions versus proceed autonomously. Use to reduce unnecessary clarifying questions when intent is clear.

Tracks quotas, monitors thresholds, and degrades gracefully for rate-limited APIs. Use when integrating external services that impose rate or cost limits.