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Found 2,167 Skills
Use when a developer wants to iterate on ONE specific Agent Observability / LLM Obs trace whose output they didn't like — re-running that trace against their LOCAL code, seeing a concise diff of the old vs new output, and looping (change code → replay → diff) until satisfied. Invoked as /agent-observability-replay-trace <trace-id> [changes to test]. Signals: "replay this trace"; "iterate on a trace"; "this trace's output is wrong, fix it and re-run"; "re-run trace <id> with <change>"; pasting a trace id from the Agent Observability UI with a description of what to fix. It fetches the trace via the datadog-llmo MCP or the pup CLI, edits code, re-runs the app to emit a NEW trace, and diffs the two — no local server, no browser. For agents traced with ddtrace / LLM Obs (Python first-class), with JSON-serializable entry input. Do NOT use for: scored Experiments or the browser "Replay" button (that's agent-observability-replay-experiment), building an experiment from a dataset/CSV, writing evaluators, root-causing failed traces, or RUM/HTTP session replay.
Generate hierarchical AGENTS.md knowledge base for a codebase. Creates root + complexity-scored subdirectory documentation.
Create agents for financial analysis, investment research, and portfolio management. Covers financial data processing, risk analysis, and recommendation generation. Use when building investment analysis tools, robo-advisors, portfolio trackers, or financial intelligence systems.
Analyze an existing codebase with parallel mapper agents, creating codebase documentation, understanding brownfield projects, or mapping code structure. Triggers include "map codebase", "analyze codebase", "create project context", "document codebase", "understand code", and "codebase map".
Compile an agent-optimized changelog by cross-referencing git history with plans and documentation. Use when asked to "update changelog", "compile history", "document project evolution", or proactively after major milestones, architectural changes, or when stale/deprecated information is detected that could confuse coding agents.
Build AI agents and apps with Composio - access 200+ external tools with Tool Router or direct execution
Advanced context engineering techniques for AI agents. Token-efficient plugins improving output quality through structured reasoning, reflection loops, and multi-agent patterns.
Complete ElevenLabs AI audio platform: text-to-speech (TTS), speech-to-text (STT/Scribe), voice cloning, voice design, sound effects, music generation, dubbing, voice changer, voice isolator, and conversational voice agents. Use when working with audio generation, voice synthesis, transcription, audio processing, or building voice-enabled applications. Triggers: generate speech, clone voice, transcribe audio, create sound effects, compose music, dub video, change voice, isolate vocals, build voice agent, ElevenLabs API/SDK/CLI/MCP.
Write or update documentation for the Inkeep docs site (agents-docs package). Use when: creating new docs, modifying existing docs, introducing features that need documentation, touching MDX files in agents-docs/content/. Triggers on: docs, documentation, MDX, agents-docs, write docs, update docs, add page, new tutorial, API reference, integration guide.
Create Trae IDE rules (.trae/rules/*.md) for AI behavior constraints. Use when user wants to: create a project rule, set up code style guidelines, enforce naming conventions, make AI always do X, customize AI behavior for specific files, configure AI coding standards, or establish project-specific AI guidelines. Triggers on: 'create rule', '创建 rule', 'project rule', '.trae/rules/', 'AGENTS.md', 'CLAUDE.md', 'set up coding rules', 'make AI always use PascalCase', 'enforce naming convention', 'configure AI behavior'. Do NOT use for skills (use trae-skill-writer) or agents (use trae-agent-writer).
Orchestrate parallel scientist agents for comprehensive analysis with AUTO mode
Use when orchestrating multi-agent teams for parallel work — feature dev, quality audits, research sprints, bug hunts, or any task needing 2+ agents working concurrently