Skill rating

Surface expert frameworks. Use when creating or evaluating skills, hooks, or agents.

Guides project ideation via Socratic questioning to produce a validated brief. Use before specification when requirements are unclear.

Detects time and space complexity hotspots via AST scan. Use when code feels slow, before performance-sensitive merges, or to find O(n²) regressions.

Test skills via TDD in fresh subagents. Use when validating behavior or preventing bias.

Creates behavioral rules in markdown to block dangerous commands or restrict AI behavior. Use when adding safety guardrails or preventing specific commands.

Evaluate hook security, performance, and SDK compliance. Use for audits.

Prepares pull requests by running quality gates, drafting descriptions, and validating tests. Use when completing a feature and ready for review.

Generate diverse solution candidates with category-spanning ideation methods and rotation. Use when stuck on a design or fighting repetitive LLM output.

Applies modular monolith with enforced internal boundaries. Use when teams want service-level autonomy without distributed system overhead.

Applies Functional Core, Imperative Shell to isolate logic from side effects. Use when business logic is entangled with I/O or unit tests are slow and brittle.

Applies client-server architecture for web/mobile apps. Use when designing systems with centralized backend services, trust boundaries, or offline-first sync.

Applies microservices for independent deployment and per-service scaling. Use when teams need autonomous release cycles with distinct capability scaling needs.

Applies coarse-grained service architecture for deployment independence. Use when independent deployment is needed but shared databases rule out microservices.

Applies event-driven async messaging to decouple producers and consumers. Use when designing real-time or multi-subscriber systems needing loose coupling.

Applies microkernel architecture with minimal core and plugin extensibility. Use when building platforms where third parties extend core functionality.

Applies data-grid architecture for high-traffic stateful workloads. Use when a single database cannot scale and in-memory partitioning is needed.

Applies serverless FaaS patterns for event-driven workloads. Use when designing bursty workloads with minimal infrastructure and pay-per-execution cost model.

Applies hexagonal architecture isolating domain from infrastructure. Use when designing systems where testability and port/adapter separation are priorities.

Applies pipes-and-filters for sequential data transformations. Use when data flows through discrete stages like ETL, streaming analytics, or CI/CD pipelines.

Applies layered n-tier architecture with enforced boundaries. Use when designing moderate systems needing clear presentation, domain, and persistence layers.

Generates markdown digests and CSV exports for GitHub initiative health. Use when reporting on issue/PR progress across a milestone or project.

Ramps implementation ambition a notch only after the prior increment is understood. Use when building a feature you must understand, not just ship.

Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.

Standardizes release approvals with GitHub-aware checklists and deployment gates. Use before releasing to production to verify all gates pass.

Orchestrates Spec Driven Development by coordinating spec, plan, and task skills. Use when running the full speckit workflow from spec to implementation.

Verifies workspace state and staged changes as a read-only preflight. Use before commits or PRs to confirm staged set is clean and correct.

Delegates tasks to a locally served Muse Glimmer via ollama. Use when delegation-core selects glimmer or the prompt must not leave the machine.

Tracks per-agent token usage and flags waste in parallel dispatch. Use when evaluating parallel agent efficiency or after a multi-agent run.

Installs egregore watchdog daemon via launchd or systemd for autonomous relaunching. Use when setting up egregore on a new machine. Do not use on CI/CD runners.

Decides hand-vs-compiler for loop transforms (unrolling, SIMD, fusion, branchless). Use when reviewing/authoring a hot loop or tempted to hand-optimize one.

Configures pre-commit hooks for linting, type checking, formatting, and testing. Use when setting up a new project or adding quality gates to an existing one.

Delegates tasks to Z.ai GLM-5.x via the stock claude binary and an endpoint swap. Use when delegation-core selects GLM or a 1M-token context is needed.

Makes agent reasoning visible, surfaces tradeoffs, and fades help so humans build judgment. Use when reviewing or learning from agent-written code.

Maps file structure and module organization of a codebase. Use before architecture reviews, refactoring planning, or migration scope estimation.

Creates clear, testable specifications from feature descriptions with user stories. Use when starting a new feature and needing a spec before planning.

Analyzes changesets with risk scoring, categorization by type and impact, and release note preparation. Use when extracting insights from raw change data.

Applies stewardship virtues (Care, Curiosity, Humility, Diligence) to plugin work. Use when authoring plugins or reviewing code quality.

Scores feature worthiness and enforces branch-size limits against overengineering. Use when evaluating whether a feature belongs in the current scope or branch.

Searches GitHub for existing implementations, libraries, or patterns. Use when finding code examples or prior art on a topic during a research session.

Scans HN, Lobsters, Reddit, and tech blogs for community experience reports. Use when gathering practitioner opinions on a technology or approach.

Searches academic literature via arXiv, Semantic Scholar, and open-access PDFs. Use when building literature reviews or finding formal research on a topic.

Applies TRIZ cross-domain analogical reasoning to find solutions from adjacent fields. Use when stuck on a problem and needing inventive perspectives.

Refines an active research session by drilling deeper into a subtopic. Use after tome:research to narrow results to a specific channel or angle.

Models a business in its own language. Use when the domain has real business rules to capture.

Delegates tasks to Meta's Muse Code CLI (muse) via delegation-core. Use when delegation-core selects Muse or repository-scale work needs a 1M-token context.

Processes external resources into stored knowledge with quality scoring and routing. Use when ingesting articles, papers, or docs into a memory palace.

Guide creating Claude Code skills with TDD and persuasion principles. Use for new skill development.

Reviews pull requests with scope validation, requirements compliance, and line comments. Use when reviewing GitHub or GitLab PRs.

Detects AI-generated writing patterns in prose. Use when reviewing docs for slop, vague language, or identity leaks before publishing.

Convenes a multi-LLM expert panel to pressure-test hard-to-reverse decisions. Use when reversibility score is low and adversarial review is warranted.