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Found 10,079 Skills
Use when a Head of Ops, Knowledge Manager, or TPM-Internal needs to author, validate, or clean up company SOPs and internal runbooks (procurement intake, vendor offboarding, incident-comms cascade, employee onboarding, expense reimbursement, system-access provisioning, customer-escalation playbook) — including 5W2H completeness checks (Who-What-When-Where-Why-How-HowMuch), cross-link and orphan-page validation across a sprawling Notion/Confluence/Obsidian wiki, KB ingestion + hygiene reporting, ops onboarding doc generation, and runbook step verification (named owner, expected duration, observable success signal, rollback path, escalation contact). Pairs Kaoru Ishikawa's 5W2H method, Atul Gawande's *The Checklist Manifesto*, ISO 9001, ITIL v4 Service Operation, FDA 21 CFR Part 211, and Google SRE Workbook runbook discipline with deterministic stdlib-only Python tools that score completeness, detect anti-patterns, and emit prioritized cleanup lists. Distinct from `engineering/llm-wiki` (Karpathy-style personal PKM second brain), `engineering-team/runbook-generator` (system-ops production debugging runbook), `project-management/*` (Jira/Confluence delivery + ticket tracking), and sibling `business-operations/process-mapper` (BPMN process *design*, while knowledge-ops is process *documentation*).
Use when building PHP applications with modern PHP 8.3+ features, Laravel, or Symfony frameworks. Invoke for strict typing, PHPStan level 9, async patterns with Swoole, PSR standards.
Build backend AI with Vercel AI SDK v6 stable. Covers Output API (replaces generateObject/streamObject), speech synthesis, transcription, embeddings, MCP tools with security guidance. Includes v4→v5 migration and 15 error solutions with workarounds. Use when: implementing AI SDK v5/v6, migrating versions, troubleshooting AI_APICallError, Workers startup issues, Output API errors, Gemini caching issues, Anthropic tool errors, MCP tools, or stream resumption failures.
Generate complete, accessible color palettes from a single brand hex. Creates 11-shade scale (50-950), semantic tokens (background, foreground, card, muted), and dark mode variants. Includes WCAG contrast checking for text accessibility. Use when: setting up design system, creating Tailwind theme, building brand colors from single hex, converting designs to code, checking color accessibility.
Build conversational AI voice agents with ElevenLabs Platform. Configure agents, tools, RAG knowledge bases, agent versioning with A/B testing, and MCP security. React, React Native, or Swift SDKs. Prevents 34 documented errors. Use when: building voice agents, AI phone systems, agent versioning/branching, MCP security, or troubleshooting @11labs deprecated, webhook errors, CSP violations, localhost allowlist, tool parsing errors.
Build semantic search with Cloudflare Vectorize V2. Covers async mutations, 5M vectors/index, 31ms latency, returnMetadata enum changes, and V1 deprecation. Prevents 14 errors including dimension mismatches, TypeScript types, testing setup. Use when: building RAG or semantic search, troubleshooting returnMetadata, V2 timing, metadata index, dimension errors, vitest setup, or wrangler --json output.
Cross-platform desktop application framework combining Rust backend with web frontend, emphasizing security and performance
Build with Firebase Authentication - email/password, OAuth providers, phone auth, and custom tokens. Use when: setting up auth flows, implementing sign-in/sign-up, managing user sessions, protecting routes, or troubleshooting auth/invalid-credential, auth/popup-closed, auth/user-not-found, or token refresh errors. Prevents 12 documented errors.
Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation, missing value handling, groupby operations, or performance optimization.
Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.
Use when building NestJS applications requiring modular architecture, dependency injection, or TypeScript backend development. Invoke for modules, controllers, services, DTOs, guards, interceptors, TypeORM/Prisma.