Skill rating

Building engineer self-branding by turning technical contributions into a professional brand. Use for GitHub/LinkedIn/blog/conference positioning or content strategy.

Gatekeeping Git/PR by classifying change essence and recommending granularity, naming, and strategy. Use when PR preparation or commit strategy is needed.

Quantifying priority by scoring competing items with ICE/RICE/WSJF/MoSCoW/Cost of Delay/Kano. No code. Use to prioritize features/bugs/initiatives or arbitrate Must vs Should at MVP scoping.

Orchestrating ecosystem self-evolution: lifecycle-phase detection, agent relevance, cross-agent knowledge synthesis, evolution proposals. Use when auditing skill-ecosystem health or fitness.

Designing multi-tenant architectures with tenant isolation strategies, RLS, routing, and scale design for SaaS. Use when designing multi-tenant SaaS systems or tenant isolation.

Generating slides via Marp, reveal.js, or Slidev, designing narrative arcs, and optimizing conference talks with WPM-calibrated timing. Use when creating or pacing presentations.

Generating SVG icons/illustrations, designing icon systems, and constructing sprite symbols. Use when vector assets are needed.

Designing LLM-optimized folder structures: audits and restructures directories for context efficiency, progressive disclosure, and prompt cache performance. Not for general repo structure (Grove).

Navigating the skill ecosystem and guiding onboarding. Lists agents, recommends best fit for tasks. Don't use for task execution (Nexus), agent design (Architect).

Generating and auditing personal dev environment configs (zsh/tmux/neovim/ghostty) and automating the macOS desktop via AppleScript/JXA (Finder, Mail, Safari). Use for dotfiles or Apple Events.

Generating AI image-generation code using the Gemini API. Handles text-to-image generation, image editing, and prompt optimization. Use when image generation code is needed.

Channeling the documented thinking of named notable figures (an 'itako' medium) — their mental models, heuristics, and decision-style as advisory lenses. Not for decisions (Magi) or personas (Cast).

Delivering working code fastest via build-first product delivery through minimum agent chains; S/M scopes skip planning and build immediately. Use when compressing time-to-first-PR.

Generating test data and fixtures. Use when factory pattern design, boundary value data generation, synthetic data generation, or seed data management is needed.

Advising founders YC-style — socratic probing to surface the #1 bottleneck, anti-pattern detection, and 1-2 week action items. Not for brainstorming (Riff) or long-term scenarios (Helm).

Provisioning infrastructure via cloud IaC (Terraform/OpenTofu/CloudFormation/Pulumi) and local dev environments (Docker Compose, env vars). Use for IaC design or multi-cloud provisioning.

Implementing robust business logic, API integrations, data models, and reproducible AI image-generation code with type safety. Use for production implementation, Gemini image API pipelines, or interac

Authoring Storybook stories, component catalogs, and Visual Regression integration (CSF 3.0/Factories, Storybook 10 ESM-only, React Cosmos). Use when building a component catalog.

Verifying spec compliance: extracts ACs from specs, adversarially checks conformance, generates BDD scenarios and traceability matrices. Use when impl must be proven to match a PRD/SRS/AC.

Constructing landing pages from a focused section to a premium multi-stage studio pipeline: structure, copy, conversion, responsive build, craft gates, and launch handoffs. Use when building or optimi

Optimizing FinOps and cloud cost: IaC-based estimation, right-sizing, RI/SP recommendations, anomaly detection, budget alerts, AI/GPU workload economics. Use to forecast or cut cloud spend.

Controlling combinatorial explosion across multi-dimensional axes: minimum coverage sets, execution plans, test/deploy/UX/risk prioritization. Use when scoping multi-axis combinations.

Designing and evaluating AI/ML systems: prompt engineering, RAG design, LLM application patterns, AI safety, evaluation frameworks, MLOps, cost optimization. Use for AI pipelines or eval harnesses.

Analyzing pre-change impact across vertical (dependency chains, files) and horizontal (pattern consistency, naming) dimensions. Use to estimate blast radius before a refactor. No code.

Authoring standalone and cross-team specifications: PRD/SRS/HLD/LLD, staged L0-L4 unified packages, BDD acceptance criteria, and traceability. Use for technical or multi-audience documentation; not im

Guiding workflows by decomposing complex tasks (Epics) into Atomic Steps under 15 minutes each, with progress tracking and drift prevention. Use when complex decomposition is needed.

Responding to incidents: identifies impact scope, formulates recovery procedures, creates postmortems. Use when incident response or disaster recovery is needed. Delegates fixes to Builder.

Directing UI/UX creative work — redesigns, new designs, trend application, Design System construction, Muse/Palette/Flow/Forge orchestration. Use for design direction. Offers a co-design pair mode.

Generating pixel-accurate HTML/CSS code from image mockups (PNG/JPG/screenshots) and performing visual verification for faithful reproduction. Use when mockup-to-code generation is needed.

Cleaning up the skill ecosystem: auditing the agent roster for overlap and inactivity, proposing merges and sunset plans. Propose-only. Not for ecosystem strategy (Darwin) or code YAGNI (Void).

Orchestrating multi-session parallel execution via Claude Code Agent Teams API and Codex CLI Subagents — launch, manage, coordinate concurrent tasks. Use when parallel work is needed.

Verifying system resilience via load testing, contract testing, chaos engineering, and mutation testing. Use for limit verification, non-functional testing, or reliability validation.

Defining and managing design tokens, applying token systems to existing codebases, building design system foundations. Use for spacing, color, typography, dark mode, cross-platform output.

Designing search engines and vector DBs for full-text, vector, and hybrid retrieval, including permission-aware retrieval for multi-tenant or per-role corpora. Use for search design, index optimizatio

Converting technical knowledge into durable learning documents and publishable articles. Use for diff-based teaching, decision records, onboarding, note/Zenn/Qiita/dev.to posts, article series, retros

Curating cross-agent knowledge and institutional memory: extracts patterns from agent journals into METAPATTERNS.md, detects knowledge decay, propagates best practices. Use for memory curation.

Collecting GitHub PR data and generating work reports. Retrieves PR info via gh commands to auto-generate weekly/monthly reports and release notes. Use when work reporting or PR analysis is needed.

Integrating messaging platforms and bots: channel adapters, webhook handlers, WebSocket servers, event-driven architecture, bot command frameworks. Use for Slack/Discord/Teams integration.

Designing A/B tests: hypothesis docs, sample size, feature flags, significance analysis, CUPED, SRM detection, switchback experiments. Use when hypothesis validation is needed.

Engineering observability and reliability: SLO/SLI design, distributed tracing, alerting, dashboards, capacity planning, toil automation, reliability review. Use for instrumentation or SLO definition.

Visualizing code, specs, or context as Mermaid, ASCII, or draw.io diagrams: flowcharts, sequence/state/class/ER, Journey Maps, personas, coverage heatmaps. Use to reverse-document systems visually.

Optimizing SEO (meta/OGP/JSON-LD/headings), SMO (social sharing), CRO (CTA/form/exit-intent), and GEO (AI citation optimization). Use for search ranking, conversion, or AI visibility.

Planning releases and reporting delivery work from GitHub PR history. Use when versioning, CHANGELOGs, rollout or rollback plans, engineering metrics, retrospectives, or stakeholder reports are needed

Designing ETL/ELT pipelines, visualizing data flows, selecting batch/streaming approaches, and architecting Kafka/Airflow/dbt systems. Use when building data pipelines or managing data quality.

Analyzing dependencies, circular references, and God Classes; authoring ADRs/RFCs. Use for architecture improvement, module decomposition, and technical debt assessment.

Designing cryptographic architecture: algorithm selection, key management, E2EE, KMS integration, signature verification, TLS. Use when designing crypto protocols or key rotation flows.

Conducting user research: interview guides, usability test plans, qualitative analysis, persona creation, journey mapping. Use when research design or analysis is needed; complements Echo.

Building rapid prototypes for frontend (UI components/pages) and backend (API mocks, simple servers). Use to validate new features or turn ideas into working demos. Working software over perfection.

Extracting and structuring design context from Figma via MCP Server for downstream implementation agents. Use for Figma-to-code bridging or Code Connect management.

Auditing SKILL.md normalization and compliance: scans the 21-item checklist, classifies violations, produces fix snippets. Use when auditing SKILL.md compliance or ecosystem health.