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Found 6,494 Skills
Ingest OpenClaw agent history into the Obsidian wiki. Use this skill when the user wants to mine their past OpenClaw sessions for knowledge, import their ~/.openclaw folder, extract insights from previous OpenClaw conversations, or says things like "process my OpenClaw history", "add my OpenClaw sessions to the wiki", "ingest ~/.openclaw", or "what have I worked on in OpenClaw". Also triggers when the user mentions OpenClaw session logs, MEMORY.md, daily notes, or ~/.openclaw/workspace.
Creates project constitution files (CLAUDE.md/AGENTS.md) that serve as always-loaded context for coding agents. Use when setting up a new project for spec-driven development, configuring agent instructions, writing CLAUDE.md or AGENTS.md, or establishing project-wide coding standards and constraints.
Comprehensive security auditor for AI agent skills, prompts, and instructions. Checks for typosquatting, dangerous permissions, prompt injection, supply chain risks, and data exfiltration patterns — before you use any agent or skill.
Use this skill when you learn one or more design pattern(s) in the Langroid (multi) agent framework, and want to make a note for future reference for yourself. Use this either autonomously, or when asked by the user to record a new pattern.
Sets up or repairs the AGENTS.md source-of-truth pattern for any project. Creates a well-structured AGENTS.md with real stack info auto-detected from the project, then wires all AI config satellites (.claude/CLAUDE.md, .github/copilot-instructions.md, .agents/rules/, MEMORY.md) to point to it. Eliminates duplication. Always runs in plan mode — asks before acting. Use this skill whenever the user mentions AGENTS.md, agent config, source of truth for AI rules, setting up Claude/Copilot/Cursor for a project, fixing duplicate AI instructions, or wants to consolidate AI configuration files. Trigger even if the user just says "set up agents" or "fix my AI config".
Browser automation CLI using DOMShell MCP server. Maps Chrome's Accessibility Tree to a virtual filesystem for agent-native navigation.
Philip Tetlock's Superforecasting framework applied to a business decision, investment thesis, or strategic question. Spawns a team of specialist agents — Calibrator, Decomposer, Updater, Devil's Advocate, Scorekeeper — who each apply a different piece of the superforecasting methodology. The lead synthesizes into a calibrated probability estimate with Brier-scoreable predictions, explicit base rates, and an accountability structure for keeping score over time. Use when the user says "tetlock this", "what's the probability", "how confident should I be", "forecast this", "calibrate this", proposes a business thesis and wants probabilistic stress-testing, or wants to apply superforecasting to a decision. Works standalone or after /munger.
Nassim Taleb's Antifragility framework applied to a business idea, system, or portfolio position. Spawns a team of specialist agents — Fat-Tail Detector, Fragility Auditor, Optionality Scout, Iatrogenics Checker, Skin-in-the-Game Auditor — who each apply a distinct lens from Taleb's Incerto to evaluate whether the subject is fragile, robust, or antifragile. The lead synthesizes into a convexity assessment: what's the payoff structure under disorder, where are the hidden tail risks, and the honest Taleb verdict. Use when the user says "taleb this", "is this fragile", "antifragility analysis", "what would Taleb think", "tail risk check", or proposes a business/system and wants structural risk analysis. Works standalone or after /munger for complementary analysis.
Run comprehensive agent-native architecture review with scored principles
Expert skill for using Future AGI — the open-source end-to-end platform for evaluating, observing, and improving LLM and AI agent applications with tracing, evals, simulations, datasets, gateway, and guardrails.
Build command-line interfaces for AI agents. Covers arguments, flags, subcommands, help text, output formats, error messages, exit codes, config/env precedence, and safe/dry-run behavior. Use when building a new CLI or refactoring an existing one for agent use.
Scope coverage, build a testing strategy, test the feature with agent-browser, capture screenshots/video (always mandatory), upload to S3, and create a structured test report (never skip)