Agent Building skills

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

lazyllm-skill

LazyLLM framework for building multi-agent AI applications. Use when task mentioned LazyLLM or AI program for: (1) Flow orchestration - linear, branching, parallel, loop workflows for complex data pipelines, (2) Model fine-tuning and acceleration - finetuning LLMs with LLaMA-Factory/Alpaca-LoRA/Collie and acceleration with vLLM/LMDeploy/LightLLM. Includes comprehensive code examples for all components, (3) RAG systems - knowledge-based QA with document retrieval, vectorization, and generation, (4) Agent development - single/multi-agent systems with tools, memory, planning, and web interfaces.

3.85k repo starsObserved in 1 repos

Agent Building

GitHub

llm-judge

AI quality judge that scores agent responses 0-10 across helpfulness, accuracy, completeness, and clarity. Use when evaluating multi-agent output or implementing LLM-as-judge quality gates.

3.78k repo starsObserved in 1 repos

Agent Building

GitHub

adding-skills

Guidelines for adding new agent skills: always register in AGENTS.md, and prefer deterministic scripts with unit tests over pure SKILL.md for repeatable workflows.

3.74k repo starsObserved in 1 repos

Agent Building

GitHub

tracecat-automation-best-practices

Use when building, editing, validating, or debugging generic Tracecat automations through Tracecat MCP, including workflow DSL/YAML authoring, table design, unique indexes, run-python Tracecat imports, agent presets, ai.agent or ai.preset_agent workflows, executions, validation, and workflow best practices.

3.73k repo starsObserved in 1 repos

Agent Building

GitHub

tracecat-slackbot-best-practices

Use when building, editing, validating, or debugging Tracecat Slack bots and Slack-facing automations through Tracecat MCP, including Slack app mentions, interactive messages, event subscriptions, webhooks, thread replies, Slack tools, ai.agent or ai.preset_agent bots, Slack tone, and Slack smoke tests.

3.73k repo starsObserved in 1 repos

Agent Building

GitHub

meta-skills

Patterns for structuring, composing, and improving agent skills, plus the Meta-Skilling Framework (MSF) for developing new skills from zero to competent. Covers skill routing, chunked processing, collaboration protocols, quality gates, MSF five phases (Discovery, Practice, Capture, Validation, Iteration), the SKILL.md template, and stackability patterns. Use when creating new skills, improving existing ones, designing multi-skill workflows, building a skill hierarchy, reviewing whether an existing skill needs iteration, or deciding how to decompose a domain into sub-skills.

3.71k repo starsObserved in 1 repos

Agent Building

GitHub

skill-distillation

Step 5 of the request loop (`ORIENT -> PLAN -> EXECUTE -> VALIDATE -> DISTILL -> DELIVER`). Before delivering any response, extract new skills, skill updates, or procedure refinements and write them to the library. Triggers: user correction, novel problem solved, undocumented workaround, >3-iteration debugging, draft skill created mid-task, heartbeat retrospective, every request closure.

3.71k repo starsObserved in 1 repos

Agent Building

GitHub

agent-engines

How to inspect and configure the AI engine (model provider) powering the agent. Use when the user asks to switch models, check which engine is active, test a new provider, or register a custom engine.

3.70k repo starsObserved in 4 repos

Agent Building

GitHub

harness-agents

Add or use full agent harness runtimes like Claude Code, Codex, Pi, Cursor, Mastra, or ACP agents inside Agent Native.

3.70k repo starsObserved in 3 repos

Agent Building

GitHub

progress

Report live progress from long-running agent tasks. Use when a task takes more than a few seconds, so the user can watch status in the runs tray instead of staring at a spinner.

3.70k repo starsObserved in 3 repos

Agent Building

GitHub