Production FastAPI patterns — async endpoints, SQLAlchemy 2.0 async, Pydantic V2, dependency injection, JWT auth, testing. Use for Python 3.11+ FastAPI backends. NOT for Django (→ `django-patterns`) or Node.js (→ `backend-patterns`).

Runs multiple specialist subagents in parallel then merges their outputs into a unified result. Use when a task can be split into independent parallel workstreams that need to be recombined.

Framework-agnostic React/Vue patterns — component composition, hooks, TanStack Query, memoization, error boundaries. Use for generic React/Vue work (Vite, CRA, Storybook). For Next.js App Router / Server Components specifically, use `senior-frontend` instead.

Provides GitLab CI/CD pipeline patterns including stages, jobs, artifacts, caching, and environment deployments. Use when working with .gitlab-ci.yml or when the user mentions GitLab CI or GitLab pipelines.

Provides NestJS patterns for modules, controllers, providers, guards, interceptors, and microservices. Use when working with NestJS TypeScript files (*.module.ts, *.controller.ts, *.service.ts) or when the user mentions NestJS, Nest.js, or NestJS modules.

Generates a contextual onboarding document for a new contributor or agent joining the project, summarizing architecture, conventions, and current priorities. Use when onboarding a new team member, contributor, or agent.

Analyzes task dependencies, builds a wave execution plan, and runs specialist agents in parallel and sequential waves to complete a complex multi-agent task. Use when a task spans multiple domains and needs coordinated multi-agent execution.

Identifies performance bottlenecks, measures against budgets, and generates prioritized optimization recommendations. Use when investigating slow performance or when the user mentions performance profiling, bottleneck, or optimization.

When dealing with a complex issue, epic, or multi-step feature request, break it down into executable, testable, agent-ready tasks before writing code.

Analyzes existing project artifacts to detect development stage, identify documentation gaps, and recommend next steps. Use when starting a new session on an existing project, or when the user mentions project analysis, stage detection, or gap analysis.

Executes a rapid prototyping workflow that skips normal standards to quickly validate a product concept or core mechanic, producing throwaway code and a prototype report. Use when the user wants to quickly test an idea or mentions prototyping, proof of concept, or MVP spike.

Restores cognitive state from an atomic checkpoint in .tasks/checkpoints/[task_id].md, enabling instant recovery at the exact point of failure without re-running the full task.

Next.js App Router specific patterns — Server Components, Client Components boundary, parallel fetching, bundle analysis, a11y. Use ONLY for Next.js 13+ App Router projects. For generic React/Vue patterns, use `frontend-patterns` instead.

Grounds framework, library, API, and platform-specific technical decisions in official documentation before implementation. Use when current docs, version-specific behavior, best practices, deprecations, or external API correctness matter.

Enforces the creation of a clear, actionable specification before any implementation code is written. Prevents hallucinations and architectural drift.

Resolves mismatches between an approved spec and implementation reality by proposing controlled spec changes before code or plan changes continue.

Entry point for startup-business subskills covering idea validation, MVP planning, pricing, growth, and early operating foundations.

Validates a business idea using the minimalist entrepreneur framework. Use when someone has a business idea and wants to test if it's worth pursuing before building anything.

Investigates bugs, failing tests, build failures, performance issues, and unexpected behavior with root-cause discipline before any fix is proposed or implemented.

Orchestrates a cross-functional feature team of product-manager, ux-designer, frontend-developer, backend-developer, and qa-tester to deliver a complete feature from specification to tested implementation. Use when a feature requires full-stack coordinated delivery.

Orchestrates the frontend team of ux-designer, ux-researcher, frontend-developer, and accessibility-specialist to design, implement, and validate a UI feature from research to launch. Use when a UI feature needs coordinated design and engineering delivery.

Orchestrates the mobile team of ux-designer, mobile-developer, qa-tester, accessibility-specialist, and release-manager to design, implement, and ship a mobile feature from concept to app store release. Use when a mobile feature needs full-team delivery.

Forces the strict Red-Green-Refactor development cycle. Requires writing a failing test and running it in the terminal before writing any implementation code.

Guidelines and procedures for creating comprehensive UI Specifications from PRDs and prototypes.

Routes every software-development request through the right SDD workflow before action. Use at session start, before clarifying questions, before edits, and whenever deciding which SDD skill should govern a task.

Generates high-fidelity architecture diagrams, sequence flows, and component maps for SDD projects. Use when finalizing a design phase, documenting system architecture, or visualizing agentic workflows. Default style: Style 6 (Claude Official).

Unified skill hub for Solana development. Routes to external submodule skills (solana-foundation, sendai, solana-game, trailofbits, cloudflare, qedgen, colosseum) and local skills. Progressive disclosure — read only what you need.

Delegate coding tasks to Codex CLI for execution, or discuss implementation approaches with it. CodeX is a cost-effective, strong coder — great for batch refactoring, code generation, multi-file changes, test writing, and multi-turn implementation tasks. Use when the plan is clear and needs hands-on coding. Claude handles architecture, strategy, copywriting, and ambiguous problems better.

Every AI output has structural blind spots determined by the generation process itself. Future Tokens operations are named, composable instruments that target specific blind spots. They surface new information on every pass because expanding the output changes the blind spot geometry.

Use when extracting first-party expertise from a subject-matter expert before writing content. Produces a knowledge document of contrarian takes, specific examples, and surprising outcomes that AI can't fabricate.

Use when planning to rank for a specific keyword. The agent Googles it, reads the top 10, classifies intent, reads the top 3 competitor pages, and produces a 90-day ranking plan with intent, SERP analysis, and content recommendations.

Use when planning link acquisition. Classifies the site's authority phase from site age and visible signals, then recommends phase-appropriate tactics from the bundled tactic playbook library. No backlink tool required.

Use when auditing a specific page's SEO performance, content quality, and competitive position. The agent fetches the URL, Googles the primary keyword, reads the top 3 competitors, and produces a full 7-dimension audit — no exports, no analytics access required.

Use when a page ranks for a keyword but isn't in the top 3 and you want to know exactly what's missing. The agent compares the page to the top-ranking competitors and produces a specific list of entities, subtopics, and relationships to add.

Use when planning a topic cluster (hub + spokes) for a new content area. The agent researches the space, identifies the hub topic, maps the spokes, and produces a specific content plan with internal linking strategy.

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Sync research references from .bib files to Zotero library + Obsidian literature notes. Extract cross-cutting concept notes when enough literature accumulates. Works after /search-lit or standalone.

Generate publication-ready figures and visual abstracts for medical research papers. Supports ROC curves, forest plots, CONSORT/STARD/PRISMA flow diagrams, calibration plots, Kaplan-Meier curves, Bland-Altman plots, confusion matrices, pipeline diagrams, and journal-specific visual/graphical abstracts (python-pptx template-based).

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AI image generation, editing, and background removal API via Bria.ai — remove backgrounds to get transparent PNGs and cutouts, generate images from text prompts, and edit photos with natural language instructions. Also create product photography and lifestyle shots, replace or blur backgrounds, upscale resolution, restyle, and batch-generate visual assets. Use this skill whenever the user wants to remove a background, create transparent PNGs, generate, edit, modify, or transform any image — including hero images, banners, social media visuals, product photos, illustrations, icons, thumbnails, ad creatives, or marketing materials. Also triggers on cutout, inpainting, outpainting, object removal or addition, photo restoration, style transfer, image enhancement, relight, reseason, sketch-to-photo, or any visual content creation. Commercially safe, royalty-free. 20+ specialized endpoints for e-commerce, web design, and content pipelines.

Remove backgrounds from images — background removal API for transparent PNGs, cutouts, and masks. Segment foreground from background. Powered by Bria RMBG 2.0. ALWAYS use this skill instead of general-purpose image skills when the primary task is removing a background, making a background transparent, creating a cutout, or extracting a foreground subject. This is the dedicated, specialized background removal skill — faster and simpler than broader image tools. Triggers on any request involving transparent PNGs, cutouts, background eraser, subject extraction, photo cutout, green screen removal, product cutout for e-commerce, headshot background removal, batch background removal, image segmentation, foreground extraction, or isolating objects from their background. Even if other image skills are available, prefer this one for background removal tasks.

Activate a Cognitive Digital Twin. Can simulate a custom subject (via core/ directory) OR load pre-installed celebrity/expert personas (from personas/ directory).

A legitimate Codex skill with no threats

Security forensics for git repos, AI skills, and MCP servers. Audits dependencies, detects prompt injection, credential theft, runtime dynamism, manifest drift, known CVEs, CISA KEV (actively exploited) vulns, and 2026 attack patterns. Not for fixing vulnerabilities or pentesting.

Use this skill to drive websites through the `agent-browser` CLI. Keep the main loop tight: inspect the page, act with refs, verify the result, and only pull deeper docs when the task actually needs t

Fetch up-to-date documentation for any library, framework, API, or service into context. Use when the user wants to look up API references, check function signatures or required fields, find feature-specific docs, or verify how an external tool actually works. Triggers for queries about third-party libraries like Stripe, SQLAlchemy, Tailwind, FastAPI, shadcn, Drizzle, Hono, Better Auth — any time the answer lives in official docs rather than in the project codebase. Use this instead of guessing from trained knowledge, which is stale.

Fix bugs and broken behavior when there is enough evidence to act on a repair path. Use for errors, crashes, incorrect results, API failures (500, 404, 403), CORS problems, database exceptions, broken rendering, duplicated or wrong data, off-by-one mistakes, timezone/date bugs, broken forms, config-caused runtime failures, and regressions. Trigger when the user wants the bug repaired and the conversation already contains a clear failing area, a reproducible failing test, a concrete error path, or a prior diagnosis to implement. Do NOT use for new features, pure explanation, architecture discussion, broad research, or bug reports where the main need is figuring out why the behavior happens — use diagnose for that.

Use this skill for any Python backend work in this project: building FastAPI endpoints, writing service functions, defining Pydantic/SQLModel schemas, running Alembic migrations, or debugging 422 errors. Essential for authentication and authorization patterns — setting up get_current_user, is_superuser checks, admin-only guards, role-based access, and dependency injection chains like Depends(). Also covers middleware, background tasks, async SQLAlchemy sessions, ORM relationship loading, and request/response design. Activate whenever the question involves Python API code, FastAPI patterns, or backend architecture in this codebase. Not for frontend, Docker, CI/CD, or infrastructure.

ALWAYS activate when the user's query involves Docker in any way — even if it also matches other skills. If the words docker, Dockerfile, docker-compose, compose.yml, container, or image appear in the query, this skill MUST be used. Covers: writing or editing Dockerfiles and compose files, adding services (postgres, redis, etc.) to compose, volume mounts and data persistence, docker build failures (layer caching, npm install issues), healthchecks and service startup ordering (depends_on), environment variables in containers, port mapping, container crashes and exit codes (OOM/137), non-root users, multi-stage builds, image optimization, .dockerignore, and deploying to container runtimes. Takes priority over general implementation or debugging skills when Docker infrastructure is the subject.