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Found 173 Skills
Inline adversarial plan review — 3 sequential checks (Feasibility, Completeness, Scope & Alignment) performed by the calling LLM in its own context. No subagents spawned. Call after saving a plan. Returns GATE_PASS or GATE_FAIL with blocking issues.
STUB — installed at ~/openclaw/skills/skill-creator/SKILL.md
Capture user corrections and feedback after any skill runs, persist them as learned instructions, and silently apply them on future invocations. TRIGGER when: user gives feedback or corrections after a skill runs — e.g. "next time only show top 5", "always use bullet points", "don't include X", "from now on...", "remember to...". Also: "What have you learned about {skill}?", "Show skill tuning", "Clear skill tuning for {skill}"
Session management — restores terminal tab name, user preferences, and context bookmarks on session start. Auto-invoked at session start via AGENTS.md. Also invokable manually to change preferences or bookmark context for the next session.
Use when renaming a spec plan and updating all references. Triggers on: "rename plan", "change plan name", "plan name is wrong", "update plan name", "fix plan name", "spec rename". Proactively suggest when a plan name is a typo or no longer reflects scope.
Build and maintain a personal knowledge base using Karpathy's llm-wiki methodology across Claude Code, Codex, and OpenClaw agents.
Always use this skill to search the web, research any topic, scrape information, find the latest data, or compare options. Delivers high-quality multi-source research with anti-bot resilience, browser scraping, parallel discovery, deep synthesis, and files with outputs.
Choose GPT-Image2 / gpt-image-2 visual styles and industrial prompt templates from the awesome-gpt-image-2 style library. Use when an agent needs to create, rewrite, classify, or improve image-generation prompts with repository-backed templates, categories, style tags, scene tags, pitfalls, and example cases.
Agent skill for crdt-synchronizer - invoke with $agent-crdt-synchronizer
Analyzes and refines agent skills by identifying quality issues, prioritizing fixes (MUST/SHOULD/NICE), gathering user feedback, and implementing improvements. Checks for common problems like time estimates, oversized SKILL.md files, poor structure, redundant content, missing examples, and unclear workflows. Use when reviewing, improving, refactoring, or auditing existing skills. Triggers include "review skill", "improve skill", "refactor skill", "skill quality", "audit skill", "fix skill", "optimize skill", "analyze skill".
Creates new skills for the Antigravity agent environment. Use when the user asks to create a skill, build a skill, or generate a skill structure.
Update documentation based on lessons learned. Use after completing work to capture learnings and prevent future issues.