Total 56,939 skills, AI & Machine Learning has 9468 skills
Showing 12 of 9468 skills
KOMODO v1.0 — Momentum Event Consensus. Uses leaderboard_get_momentum_events (real-time threshold crossings) to detect when 2+ quality SM traders cross momentum thresholds on the same asset/direction within 60 minutes. Confirmed by market concentration + volume. Enters with the momentum. Replaces MANTIS v1.0 and SCORPION v1.1 (both used stale position data).
Debugs errors and traces failures in AI agents and their tools. Use this skill when the user says: "the agent is failing", "tool call not working", "error in the pipeline", "debug this", "why is the agent doing X instead of Y", "trace the execution", "agent is stuck", "infinite loop", "model response won't parse", "context overflow". Identifies context errors, infinite loops, malformed tool calls, response parsing issues and subagent conflicts.
Decomposes complex, multi-day tasks into optimized milestones using parallel reviewer agents (ultraplan). Spawns 5 independent reviewers that analyze the problem from different angles, then synthesizes their findings into a milestone dependency DAG. Triggers when the user says "plan milestones", "break this into milestones", "ultraplan", or when long-run harness needs milestone generation.
Text analytics using LLM APIs — sentiment analysis, customer feedback classification, document entity extraction, multi-language support (English/Luganda/Swahili), feedback aggregation, and NLP feature implementation for PHP/Android/iOS. Sources...
Enforces a 'Document-then-Execute' workflow. Use when an agent needs to run shell commands, execute tests, build projects, or perform any task that should favor established task runners (Makefile, npm run) and be logged to .cmds-by-agents/ for auditability.
Claude Code + Codex parallel pipeline for bootstrapping Trellis coding specs. CC analyzes the repo with GitNexus (knowledge graph) + ABCoder (AST), creates Trellis task PRDs with full architectural context and MCP tool instructions, then Codex agents run those tasks in parallel to fill spec files. Use when: bootstrapping coding guidelines, setting up Trellis specs, 'bootstrap specs for codex', 'create spec tasks', 'CC + Codex spec pipeline', 'initialize coding guidelines with code intelligence'. Also triggers when user wants to set up GitNexus or ABCoder MCP for multi-agent spec generation.
Expert in the Vercel AI SDK. Covers Core API (generateText, streamText), UI hooks (useChat, useCompletion), tool calling, and streaming UI components with React and Next.js.
How to use the repo-scoped sk CLI to manage Claude Skills in this codebase.
Use when the user says "/plan-execute", "plan execute", "implement plan", or "execute plan" and provides a finalized plan file path to carry out. Claude orchestrates, Codex writes code, Claude reviews, and Codex fixes issues until the quality bar is met.
Interactive model selection workflow with paginated navigation. Use when users want to select a model interactively - guides them through provider selection then model selection using the question tool with pagination support for large lists.
This skill should be used when the user asks to "implement a plan", "execute implementation", "build from plan", "implement feature", or needs to orchestrate execution of an implementation plan with specialized engineering agents.
Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experiment logging/record-keeping that supports debugging and iteration. Do not use it for designing a brand-new experiment pipeline or full experiment program (use experiment-pipeline), generating research ideas, fixing isolated coding/syntax errors, or writing retrospective summaries into research memory/notes/knowledge bases.