Agent Building skills

Browse reusable Agent Skills, each with a clear purpose and practical guidance.

memory-lancedb-pro

This skill should be used when working with memory-lancedb-pro, a production-grade long-term memory MCP plugin for OpenClaw AI agents. Use when installing, configuring, or using any feature of memory-lancedb-pro including Smart Extraction, hybrid retrieval, memory lifecycle management, multi-scope isolation, self-improvement governance, or any MCP memory tools (memory_recall, memory_store, memory_forget, memory_update, memory_stats, memory_list, self_improvement_log, self_improvement_extract_skill, self_improvement_review).

235 repo starsObserved in 1 repos
Agent Building

orchestrating-swarms

Master multi-agent orchestration using Claude Code's TeammateTool and Task system. Use when coordinating multiple agents, running parallel code reviews, creating pipeline workflows with dependencies, building self-organizing task queues, or any task benefiting from divide-and-conquer patterns.

234 repo starsObserved in 3 repos
Agent Building

agentsmd-scaffold

Generate or update repository-specific AGENTS.md instruction files from real repo evidence. Use when asked to create, design, scaffold, split, or improve root or scoped AGENTS.md files for Codex/Claude/agent workflows, especially when a repo needs directory-specific rules, validation commands, generated-file boundaries, or a short agent onboarding router.

234 repo starsObserved in 2 repos
Agent Building

capability-distill

能力蒸馏工作流——从用户批准的强模型访谈或真实任务轨迹中提取非显然的判断规则,形成可审计的 judgment packet,再交给 skill-audit 和 skill-creator 决定是否落成可加载 skill。当用户说“蒸馏这个模型的判断力”“把这次任务的关键决策固化下来”“模型窗口要关了,保留它在某类场景的判断”时使用。普通流程文档、直接写 SKILL.md、泛化最佳实践或未授权的会话日志扫描不使用本 skill。

234 repo starsObserved in 2 repos
Agent Building

skill-lifeguard

Use when a skill is brittle, drifting, repeatedly failing, or needs a Reliable Skill Contract. Trigger for phrases like skill lifeguard, reliable skill, self-maintaining skill, negative examples, verification checkpoints, drift signals, replay hooks, or failure log to skill patch. Audits or patches skills so high-value workflows include explicit forbidden behaviors, checkpoints, machine-checkable done conditions, replay or smoke hooks, and drift detection.

234 repo starsObserved in 2 repos
Agent Building

agentsmd-optimize

Audit AND optimize a CLAUDE.md / AGENTS.md instruction file — score it against the five high-leverage patterns, flag anti-patterns, then apply approved fixes in place. Use when the user says 优化 CLAUDE.md / 优化 AGENTS.md / optimize my agent doc / 帮我改 claudemd, or after an audit when they want the fixes applied (not just reported).

234 repo starsObserved in 1 repos
Agent Building

codex-retrospective

Use when you want Codex to review its own recent history (last N days or specific period) and improve its behavior. Produces minimal, high-signal updates to AGENTS.md and tiny reusable skills. The goal is long-term fluency — Codex gradually becomes better at your specific style, constraints, and workflows.

234 repo starsObserved in 1 repos
Agent Building

conversation-to-skill

Turn the current conversation's workflow into a reusable agent skill. Use this whenever the user wants to make a workflow reusable, standardize a successful thread, package an agent capability, or convert an ad hoc process into a repeatable skill. Read the thread first, extract the stable pattern, decide whether the skill should live in `~/.agents/skills/<name>` or `<project-path>/.agents/skills/<name>`, write the skill, and when quality matters add lightweight evals and iteration instead of just transcribing the chat.

234 repo starsObserved in 1 repos
Agent Building

flowguard

Guard long, ambiguous, or stateful AI-agent work from drift. Use when the user asks to run or continue a multi-step task, autonomous loop, bug fix, repo change, PR readiness check, compaction handoff, resume from previous context, cost-control checkpoint, or any task likely to span many tool calls, files, sessions, agents, or verification gates.

234 repo starsObserved in 1 repos
Agent Building

multi-model-orchestrator

Use when coordinating complex tasks across multiple AI agents with a centralized handoff document for planning, execution tracking, and feedback fusion.

234 repo starsObserved in 1 repos
Agent Building