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Found 1,270 Skills
OpenClaw-RL framework for training personalized AI agents via reinforcement learning from natural conversation feedback
#1 on DeepResearch Bench (Feb 2026). Any-to-Any AI for agents. Combines deep reasoning with all modalities through sophisticated multi-agent orchestration. Research, videos, images, audio, dashboards, presentations, spreadsheets, and more.
2-stage pipeline: trace (causal investigation) -> deep-interview (requirements crystallization) with 3-point injection
Comprehensive memory quality review across 6 dimensions: purity, freshness, coverage, clarity, relevance, and structure. Generates prioritized findings with specific memory references and actionable recommendations.
Autonomous bounty hunting — scan open bounties, match to your skills, claim and track work
Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.
Use this skill when you receive a 402 Payment Required response that contains an `agentkit` extension. Covers checking 402 responses for the AgentKit extension before paying, constructing and signing a CAIP-122 challenge (SIWE for EVM, SIWS for Solana), sending the signed `agentkit` HTTP header, and interpreting access modes (free, free-trial, discount). Supports both EOA wallets (EIP-191) and Smart Contract Wallets (ERC-1271, e.g. Coinbase Smart Wallet, Safe).
Orchestrate subagent workflows for complex tasks that benefit from decomposition, role-based delegation, and parallel execution. Use when Codex should assemble a temporary team of subagents, choose roles from a reusable role library, create a controlled fallback role when no preset role fits, coordinate read-heavy work in parallel, or handle write-heavy work with ownership boundaries, staged execution, and an integrator-led merge path.
Execute deep research on every item in a research outline, producing structured JSON per item and a final markdown report. Use after running /research to generate an outline. Reads outline.yaml and fields.yaml, launches parallel research agents in batches, validates output, generates a consolidated report, and supports resume on interruption. Trigger when the user says "start deep research", "research these items", "run the deep phase", "fill in the fields for each item", or "generate the research report".
Turn a rough idea into a structured prompt or skill scaffold with explicit objective, inputs, workflow, outputs, and a concrete file plan. Use this whenever the user wants to design a new prompt or skill, scaffold a skill-like workflow, mentions "scaffold," "blueprint," "structure," or "plan" for a prompt, or arrives with a vague request that needs to be shaped before implementation — even if they don't explicitly ask to scaffold.
Creates new skills, either generic for the global catalog or specific to the current project. Trigger: /skill-create <name>, create skill, new skill, generate skill, add skill to project.
Command-line interface for Gimp - A stateful command-line interface for image editing, built on Pillow. Designed for AI agents and pow...