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Found 8,781 Skills
Designs, builds, debugs, and documents OpenClaw workflows, skills, and AI assistant configurations. Use when the user mentions "OpenClaw," "personal AI assistant," "local AI," "ClawdHub," "openclaw skills," "chat platform AI," or wants to set up AI assistants across WhatsApp, Telegram, Discord, or Slack.
Self-improving agent toolkit — forge runtime tools, adapt personality traits, manage skills dynamically, compose multi-step workflows, and self-evaluate performance with bounded autonomy.
Use when the user asks to "improve a metric", "run labs", "leave feedback on a metric", "add to labs", "fix metric accuracy", "review metric results", "find misaligned metrics", or "iterate on metric quality". Covers the metric improvement cycle, the feedback workflow, and the labs pipeline used to refine metric accuracy over time.
Router skill for LLMQuant risk workflows. Use when the user needs fear scoring, VIX regime, hedge design, or research health checks.
Router skill for LLMQuant prediction-market workflows. Use when the user needs event odds, settlement criteria, probability gaps, cross-market pricing, or prediction-market arbitrage review.
Cross River integration. Manage data, records, and automate workflows. Use when the user wants to interact with Cross River data.
Audit GitHub Actions workflow efficiency and recommend fixes to reduce CI minutes and costs.
Review one pull request through a standalone, progressively disclosed workflow. Use when the user asks to review a PR, audit a pull request, prepare GitHub review comments, draft request-changes feedback, write a PR review file, or optionally post approved review comments. This skill handles exactly one PR; ask the user to choose one PR when multiple PR URLs are supplied.
Router and overview for the Cargo CLI agent skills. Explains the eleven skills (one outcome skill cargo-gtm + ten capability skills), the UUID flow between them, async polling, end-to-end use cases (enrich one record, enrich and sync to CRM, AI lead scoring, custom workflow, error monitoring, fresh-workspace bootstrap, segment export, GTM context authoring), and common gotchas (`conjonction` spelling, run vs batch, model-uuid vs segment-uuid). Load first whenever working with the Cargo CLI, when unsure which sub-skill applies, when stitching multiple sub-skills together, when bootstrapping a workspace, or when the user asks about Cargo skills in general.
Capture a hard-won "golden path" from the current session as a reusable Agent Skill, so future sessions start already knowing it. Use it (1) right after non-trivial debugging, after working out a multi-step operational workflow, or after rediscovering project facts you didn't know up front — e.g. how to reach the dev/prod database, where credentials and env vars live, how to deploy, run migrations, or verify a change live; and (2) whenever the user says "remember this", "save this as a skill", "make a skill for this", "don't make me re-explain this next time", or otherwise wants a workflow preserved across sessions. Proactively recognize the moment even when unprompted: if a task took several attempts before it worked, used non-obvious tooling, or is likely to recur, harvest it without asking first. Delegates to a subagent when your tool supports one, or works inline, to extract the proven procedure into a new project-local or global skill.
This skill should be used when the user asks to "update documentation for my changes", "check docs for this PR", "what docs need updating", "sync docs with code", "scaffold docs for this feature", "document this feature", "review docs completeness", "add docs for this change", "what documentation is affected", "docs impact", or mentions "docs/", "docs/01-app", "docs/02-pages", "MDX", "documentation update", "API reference", ".mdx files". Provides guided workflow for updating Next.js documentation based on code changes.
Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.