Total 56,986 skills, AI & Machine Learning has 9476 skills
Showing 12 of 9476 skills
Hermes Agent framework by Nous Research - self-improving AI agent with built-in learning loop, three-layer memory, and automatic skill evolution
Boost.ai integration. Manage data, records, and automate workflows. Use when the user wants to interact with Boost.ai data.
Expert guidance for contributing to and using the Awesome Claude Code repository, a curated collection of Claude Code skills, agents, hooks, and resources.
Collection of 130+ specialized Claude Code subagents for development tasks across languages, frameworks, infrastructure, and security
Academic literature orientation skill that searches papers via Consensus, builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a professionally formatted Word document (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — not a finished review, but an orientation guide that lets a researcher dive in confidently. Triggers: 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'. Do NOT trigger for single one-off paper searches where the user just wants a quick list — that's a plain Consensus search.
AI Agent Orchestration Dashboard for managing AI agents, tasks, and multi-agent collaboration via OpenClaw Gateway
Expert guide for designing and building high-quality skills from scratch through structured conversation. Use when someone wants to create a new skill, build a skill, design a skill, or asks for help making Agents do something consistently. Also use when someone says "turn this into a skill", "I want to automate this workflow", "how do I teach my Agent to do X", or mentions creating SKILL.md files. Covers standalone skills and MCP-enhanced workflows. Do NOT use for creating subagents (use subagent-creator) or technical design documents (use create-technical-design-doc).
Deploy and configure OpenClaw AI assistant with multi-model support and messaging channel integrations
Company discovery and deep research skill. Researches a company's product and ICP, discovers target companies to sell to using Browserbase Search API, deeply researches each using a Plan→Research→Synthesize pattern, and scores ICP fit — compiled into a scored research report and CSV. Supports depth modes (quick/deep/deeper) for balancing scale vs intelligence. Use when the user wants to: (1) find companies to sell to, (2) research potential customers, (3) discover companies matching an ICP, (4) build a target company list, (5) do market research on prospects. Triggers: "find companies to sell to", "company research", "find prospects", "ICP research", "target companies", "who should we sell to", "market research", "lead research", "prospect list".
Guides edge and tactical autonomous systems—perception-planning-control under latency and safety constraints; behavior trees/state machines vs learned policies; human-on-the-loop; geofencing, no-strike rules, mission abort; sim and field testing; ROS2/middleware patterns; sensor fusion; degraded modes; autonomy audit logging. Use for UAS/autonomous stacks, safety rules, HITL, sim-to-field validation, fail-safe—not LLM products (ai-engineer), LLM red team (ai-redteam), safeguard serving (ml-infrastructure-engineer-safeguards), governance only (ai-risk-governance), MCU firmware without autonomy (embedded-real-time-software-engineer), plant PLC/DCS (control-software-developer), HIL security bench (hardware-in-the-loop-security-tester).
Guides AI ops leadership—LLM SRE, model/prompt releases, eval/incidents, cost/capacity, vendors, and cross-functional cadence. Use for AI platform ops, LLM SLAs, incidents, rollout governance, unit economics, red-team/eval gates, and team rituals—not memory (ai-memory-developer), context code (ai-context-engineer), security programs (cybersecurity), token roadmaps (ai-token-improvement-plan-engineer), solution architecture (applied-ai-architect-commercial-enterprise), skills portfolio (ai-skill-manager), or vertical AI product eng management (engineering-manager-vertical-ai-products). Prompt/eval team management and golden-set release policy: engineering-manager-agent-prompts-evals. Safeguard inference platform: ml-infrastructure-engineer-safeguards. Safeguard model research: ml-research-engineer-safeguards.
Design, test, and optimize prompts for LLM interactions. Cover prompt patterns (few-shot, chain-of-thought, ReAct), system prompt design, output formatting, prompt evaluation, and prompt optimization techniques. Triggers on "write prompt", "optimize prompt", "design system prompt", "few-shot examples", "chain of thought", "prompt evaluation", "LLM output formatting", "prompt testing", or "prompt patterns".