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Found 875 Skills
Build MCP servers in Python with FastMCP. Workflow: define tools and resources, build server, test locally, deploy to FastMCP Cloud or Docker. Use when creating MCP servers, exposing tools/resources/prompts to LLMs, building Claude integrations, or troubleshooting FastMCP module-level server, storage, lifespan, middleware, OAuth, or deployment errors.
Psychological profiling through natural conversation using narrative identity research (McAdams), self-defining memory elicitation (Singer), and Motivational Interviewing (OARS framework). Use when you need to: (1) understand someone's core values and motivations, (2) discover formative memories and life-defining experiences, (3) detect emotional schemas and belief patterns, (4) build psychological profiles through gradual disclosure, (5) conduct user interviews that reveal deep insights, (6) design conversational flows for personal discovery, (7) identify identity themes like redemption and contamination narratives, (8) elicit authentic self-disclosure without interrogation.
Guide for implementing parsers with error recovery for new languages in Biome. Use when creating parsers for JavaScript, CSS, JSON, HTML, GraphQL, or adding new language support. Examples:<example>User needs to add parsing support for a new language</example><example>User wants to implement error recovery in parser</example><example>User is writing grammar definitions in .ungram format</example>
Define, validate, and run lane-style multi-step automation sequences using `asc workflow` and a repo-local `.asc/workflow.json`. Use when migrating from lane-based automation, building enterprise CI flows, or orchestrating multi-command `asc` runs.
Build a structured taxonomy of failure modes from open-coded trace annotations. Use this skill whenever the user has freeform annotations from reviewing LLM traces and wants to cluster them into a coherent, non-overlapping set of binary failure categories (axial coding). Also use when the user mentions "failure modes", "error taxonomy", "axial coding", "cluster annotations", "categorize errors", "failure analysis", or wants to go from raw observation notes to structured evaluation criteria. This skill covers the full pipeline: grouping open codes, defining failure modes, re-labeling traces, and quantifying error rates.
Create Galaxy REST API endpoints with FastAPI routers, Pydantic schemas, and manager pattern. Use for: new API routes, FastAPI endpoints, REST resources, Pydantic request/response models, lib/galaxy/webapps/galaxy/api routers, lib/galaxy/schema definitions, API controller creation.
Convert single-file task backlogs (TASKS.md format) to AutoClaude multi-file spec structure. Use when the user wants to (1) convert existing TASKS.md or similar task backlog files to AutoClaude specs, (2) initialize a new project with AutoClaude-compatible task structure, (3) migrate task definitions from simple markdown to the multi-file spec format with requirements.json, context.json, implementation_plan.json. Triggers on phrases like "convert tasks to AutoClaude", "set up AutoClaude specs", "migrate backlog", "create spec from task".
Create and validate solution design documents (SDD). Use when designing architecture, defining interfaces, documenting technical decisions, analyzing system components, or working on solution-design.md files in docs/specs/. Includes validation checklist, consistency verification, and overlap detection.
Generate structured product and technical documents through guided discovery. 8 document types: PRD, Brief, Issue, Task, User Story, RFC, ADR, TDD. Use when: defining products, reporting bugs, planning sprints, writing stories, proposing changes, recording decisions, designing systems. Triggers on "create PRD", "create issue", "report bug", "feature request", "create task", "create user story", "create RFC", "create ADR", "create TDD", "create document", "write doc".
Generate measurable learning outcomes aligned with Bloom's taxonomy and CEFR proficiency levels for educational content. Use when educators need to define what students will achieve, create learning objectives for curriculum planning, or ensure objectives are specific and testable rather than vague.
Connect the complete AI development workflow through documents. It covers domain modeling and code organization (DDD), behavior verification and automated testing (BDD), as well as AI development specification setting (Agent specifications). Use when (1) the project has .feature files, (2) the user asks to organize code by business features or define naming conventions, (3) creating or updating AGENTS.md / project rule files, (4) writing or implementing Gherkin scenarios, (5) starting a new project from scratch, or (6) the agent needs the full development lifecycle.
ArkType runtime validation with TypeScript-native syntax. Type-safe schemas using string expressions, morphs, scopes, and generics. Use when defining schemas, validating data, transforming input, or building type-safe APIs with ArkType.