One-stop handbook for building, deploying, and understanding LLM agents with 60+ skeletons, tutorials, ecosystem guides, and evaluation tools.
- ✓Open-source license (MIT)
- ✓Recently active
- ✓Healthy fork ratio
- ✓Clear description
- ✓Topics declared
- ✓Mature repo (>1y old)
git clone https://github.com/oxbshw/LLM-Agents-Ecosystem-Handbook && cp LLM-Agents-Ecosystem-Handbook/*.md ~/.claude/agents/11 items in this repository
Use when capturing an architecture decision so it survives turnover — produces an ADR-NNNN.md from context, options considered, and the chosen path.
Use when reviewing a proposed REST or GraphQL API change before merge — checks contract clarity, backwards compatibility, errors, pagination, auth, and naming.
Use when first encountering a new dataset — produces a structured profile (schema, missingness, distributions, outliers, gotchas) before any analysis.
Use after an incident is resolved — drafts a blameless postmortem from timeline notes, alerts, and chat threads.
Use when opening a PR — produces a clean PR description (what / why / how to verify / risks) from a branch diff against base.
Use when planning the next sprint — turns ticket intake + team capacity into a planned sprint with explicit non-goals.
Use after a session to promote useful episodic notes from logs/episodic/ into distilled, dated entries in MEMORY.md and memory/semantic/.
Use before connecting a new MCP server to your agent — produces a structured security review covering source, permissions, tools, network, and approvals.
Use before opening a PR to audit the changes for stale comments, unused imports, missing tests, and inconsistencies with neighboring code.
Use when the user asks for a sourced briefing on a topic that spans multiple web sources and requires citations.
Subagents overview
What people ask about LLM-Agents-Ecosystem-Handbook
What is oxbshw/LLM-Agents-Ecosystem-Handbook?
+
oxbshw/LLM-Agents-Ecosystem-Handbook is subagents for the Claude AI ecosystem. One-stop handbook for building, deploying, and understanding LLM agents with 60+ skeletons, tutorials, ecosystem guides, and evaluation tools. It has 546 GitHub stars and its last recorded update is dated 2026-06-30.
How do I install LLM-Agents-Ecosystem-Handbook?
+
You can install LLM-Agents-Ecosystem-Handbook by cloning the repository (https://github.com/oxbshw/LLM-Agents-Ecosystem-Handbook) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is oxbshw/LLM-Agents-Ecosystem-Handbook safe to use?
+
Our security agent has analyzed oxbshw/LLM-Agents-Ecosystem-Handbook and assigned a Trust Score of 97/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.
Who maintains oxbshw/LLM-Agents-Ecosystem-Handbook?
+
oxbshw/LLM-Agents-Ecosystem-Handbook is maintained by oxbshw. The last recorded GitHub activity is dated 2026-06-30, with 2 open issues.
Are there alternatives to LLM-Agents-Ecosystem-Handbook?
+
Yes. On ClaudeWave you can browse similar subagents at /categories/agents, sorted by popularity or recent activity.
Deploy LLM-Agents-Ecosystem-Handbook to your cloud
Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.
Maintain this repo? Add a badge to your README
Drop the badge into your GitHub README to show it's tracked on ClaudeWave. Each badge links back to this page and reflects the live Trust Score.
[](https://claudewave.com/repo/oxbshw-llm-agents-ecosystem-handbook)<a href="https://claudewave.com/repo/oxbshw-llm-agents-ecosystem-handbook"><img src="https://claudewave.com/api/badge/oxbshw-llm-agents-ecosystem-handbook" alt="Featured on ClaudeWave: oxbshw/LLM-Agents-Ecosystem-Handbook" width="320" height="64" /></a>More Subagents
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
The agent that grows with you
Java 面试 & 后端通用面试指南,覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
The agent engineering platform.
Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.