LLM-Agents-Ecosystem-Handbook
One-stop handbook for building, deploying, and understanding LLM agents with 60+ skeletons, tutorials, ecosystem guides, and evaluation tools.
- 555 stars
- 93 forks
- 4 open issues
- Language: Python
- License: MIT
- updated
Install
git clone https://github.com/oxbshw/LLM-Agents-Ecosystem-Handbook && cp LLM-Agents-Ecosystem-Handbook/*.md ~/.claude/agents/- Clone the repository and copy the agent .md definitions into ~/.claude/agents (or .claude/agents inside a project).
- Start a new Claude Code session to load the agents.
- Delegate work to them with the Task/Agent tool or by name.
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 after a session to promote useful episodic notes from logs/episodic/ into distilled, dated entries in MEMORY.md and memory/semantic/.
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 before connecting a new MCP server to your agent — produces a structured security review covering source, permissions, tools, network, and approvals.
Use when opening a PR — produces a clean PR description (what / why / how to verify / risks) from a branch diff against base.
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.
Use when planning the next sprint — turns ticket intake + team capacity into a planned sprint with explicit non-goals.
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 555 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 92/100 (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 4 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.