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Found 1,127 Skills
Chat with your agent about projects, recommendations, and canonical papers in Paperzilla. Use when users ask for recent project recommendations, canonical paper details, markdown-based summaries, recommendation feedback, feed export, or Atom feed URLs.
Ejecutar la batería de verificaciones automatizadas de un proyecto TypeScript/Node antes de aceptar una implementación como apta para merge - `tsc --noEmit` (crítico, fail-fast), `eslint` (calidad), suite de tests (comportamiento), `build` (integración) y `sonar-scanner` (análisis estático). Usar siempre que el usuario pida "revisión de código", "code review", "valida el código", "ejecuta los checks", "revisa antes de PR/merge", o tras terminar una historia o TK que toque código TS. Devolver un informe Markdown con estado por check, errores agrupados, veredicto (apto / no apto / incompleto) y próximas acciones priorizadas. No corrige código ni modifica configuración.
Bun JavaScript/TypeScript runtime and all-in-one toolkit. Covers runtime, package manager, bundler, test runner, HTTP server, WebSockets, SQLite, S3, Redis, file I/O, shell scripting, FFI, Markdown parser. Keywords: bun, bunx, bun install, bun run, bun test, bun build, Bun.serve, Bun.file, bun:sqlite, Bun.markdown.
Generates comprehensive API documentation in Markdown, HTML, or Docusaurus format from Express, Next.js, Fastify, or other API routes. Creates endpoint references, request/response examples, authentication guides, and error documentation. Use when users request "generate api docs", "api documentation", "endpoint documentation", or "api reference".
Domain-agnostic strategic decision analysis and wargaming. Auto-classifies scenario complexity: simple decisions get structured analysis (pre-mortem, ACH, decision trees); complex or adversarial scenarios get full multi-turn interactive wargames with AI-controlled actors, Monte Carlo outcome exploration, and structured adjudication. Generates visual dashboards and saves markdown decision journals. Use for business strategy, crisis management, competitive analysis, geopolitical scenarios, personal decisions, or any consequential choice under uncertainty. NOT for simple pros/cons lists, non-strategic decisions, or academic debate.
Datadog docs lookup using docs.datadoghq.com/llms.txt and linked Markdown pages.
Comprehensive Obsidian vault management. USE WHEN obsidian, vault, note, daily note, PARA, inbox, knowledge capture, dataview, DQL, search vault, .base, bases, wikilink, frontmatter, second brain, markdown syntax, obsidian.nvim, OR obsidian API. Python-powered tools for search, creation, and vault health.
MindOS Knowledge Base Operation Guide (Chinese) for Agent tasks on local markdown/csv knowledge bases. It should be automatically triggered whenever tasks involve note files, SOP/workflow documents, profile/context documents, CSV tables, knowledge base organization, cross-Agent handover or decision synchronization, and are executed via the MindOS MCP tool. Typical requests include "update notes", "search knowledge base", "organize files", "execute SOP", "review according to team standards", "hand over tasks to another Agent", "synchronize decisions", "append to CSV", "retrospect this conversation", "extract key experiences", "adaptively update retrospective results to corresponding documents", "route this information to corresponding files", "synchronously update all related documents", etc.; it should be triggered even if the user does not explicitly mention MindOS.
Convert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.
Create a complete, actionable design system for any project (website, app, product) grounded in physical/sensory anchoring rather than design trends. Delivers CSS tokens, typography scale, component patterns, accessibility checklist, and absolute rules as a single developer-ready markdown document. Use this skill whenever the user asks to create a design system, theme, color palette, visual identity, CSS tokens, theme variables, or propose an art direction. Also triggers on "style guide", "site colors", "choose fonts", "look and feel", "visual branding", "charte graphique", "identite visuelle", "direction artistique", "refonte visuelle", or any new project where design isn't yet defined — propose this skill proactively.
Execute deep research on every item in a research outline, producing structured JSON per item and a final markdown report. Use after running /research to generate an outline. Reads outline.yaml and fields.yaml, launches parallel research agents in batches, validates output, generates a consolidated report, and supports resume on interruption. Trigger when the user says "start deep research", "research these items", "run the deep phase", "fill in the fields for each item", or "generate the research report".
A step-by-step practice tool for LeetCode medium-difficulty interview questions. It is triggered when users want to practice algorithm problems, brush up on LeetCode, prepare for technical interviews, or say "Give me a problem", "Next problem", "Generate scaffold", "Start practicing". It supports categorized practice by problem type (DP, Linked List, Tree, Graph, Sliding Window, Two Pointers, Hash Table, Binary Search, Stack, Heap, Backtracking, Interval, String, Union Find), generates Python scaffolds with test cases for each problem, tracks learning progress via Markdown tables, and guides users to think independently before providing solutions. It supports the goal of 3 problems per day, counts progress via `git diff README.md` and submits to Git.