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Found 523 Skills
L3 Worker. Analyzes single pattern implementation, calculates 4 scores (compliance, completeness, quality, implementation), identifies gaps and issues. Usually invoked by ln-640, can also analyze a specific pattern on user request.
Build with OpenAI's stateless APIs - Chat Completions (GPT-5, GPT-4o), Embeddings, Images (DALL-E 3), Audio (Whisper + TTS), and Moderation. Includes Node.js SDK and fetch-based approaches for Cloudflare Workers. Use when: implementing chat completions with GPT-5/GPT-4o, streaming responses with SSE, using function calling/tools, creating structured outputs with JSON schemas, generating embeddings for RAG (text-embedding-3-small/large), generating images with DALL-E 3, editing images with GPT-Image-1, transcribing audio with Whisper, synthesizing speech with TTS (11 voices), moderating content (11 safety categories), or troubleshooting rate limits (429), invalid API keys (401), function calling failures, streaming parse errors, embeddings dimension mismatches, or token limit exceeded.
Coordinates project documentation creation. Gathers context once, detects project type, delegates to 5 L3 workers (ln-111-115). L2 Coordinator invoked by ln-100.
Worker that runs existing tests to catch regressions. Auto-detects framework, reports pass/fail. No status changes or task creation.
Applies DRY, YAGNI, PORO, Convention over Configuration, and KISS to Rails code; defers style to the project's linter(s). Covers structured logging, comment discipline, and path-specific rules (models, workers, services, controllers, repositories, serializers, RSpec, raw SQL). Use when designing or reviewing Rails structure, avoiding over-engineering, or aligning code with team boundaries by directory.
Define an entire Cargo workspace in code — connectors, models, plays, tools, agents, MCP servers, context, capacities, territories, segments, folders, files, workers, apps — and deploy it declaratively with `cargo-ai cdk` (init → types → plan → deploy), the way you'd manage cloud infra with Pulumi or the AWS CDK. Use when the user wants to manage Cargo resources as code: reproducibly, version-controlled, in git, from a template, or across environments. Routes to authoring/deploy/typing guides (Level 2), recipes (Level 2.5), and references. For one-off imperative operations (create one connector, read a model, run a workflow), use the matching capability skill instead.
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.
Python background job patterns including task queues, workers, and event-driven architecture. Use when implementing async task processing, job queues, long-running operations, or decoupling work from request/response cycles.
Orchestrate multiple worker agents to implement groomed tasks. Use when multiple ready tasks need implementation, when you want autonomous multi-task execution, or when coordinating batch development work. Keywords: coordinator, orchestrator, multi-task, parallel, workers, batch, autonomous.
Top orchestrator for complete doc system. Delegates to ln-110 coordinator (project docs via 5 L3 workers) + ln-120-150 workers. Phase 4: global cleanup. Idempotent.
Dependencies audit worker (L3). Checks outdated packages, unused deps, reinvented wheels, vulnerability scan (CVE/CVSS). Supports mode: full | vulnerabilities_only.
Frontend structure worker: SCAFFOLD new React project or RESTRUCTURE existing monolith to component-based architecture