CAMEL-AI Repo Skill

SkillDev tools

"Use CAMEL-AI to build, configure, tool, remember, evaluate, and

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the CAMEL-AI Repo Skill skill

What this skill tells your AI

The instructions your AI receives, as published by vectorspacelab/arex-skill in skills/repositories/repo-skills/camel-ai/SKILL.md and read by ahel’s review.

Use this repo skill when a task mentions CAMEL-AI, camel-ai, the camel Python package, ChatAgent, RolePlaying, Workforce, CAMEL toolkits, CAMEL model backends, CAMEL memory/RAG, or CAMEL benchmark/datagen/evaluation workflows.

First Checks

  1. Install the base package with pip install camel-ai for core agents, models, messages, tools, and package imports.
  2. Install only the optional extras needed for the chosen workflow, such as camel-ai[model_platforms], camel-ai[rag], camel-ai[storage], camel-ai[document_tools], camel-ai[web_tools], or camel-ai[dev_tools].
  3. Run scripts/inspect_camel_install.py for a no-network import, version, and route check.
  4. Read references/troubleshooting.md before installing broad extras, debugging provider credentials, or running network/Docker/browser/benchmark workflows.

Route By Task

Task or signalRead
Build a ChatAgent, system/user/assistant messages, task tree, role-playing society, or Workforcesub-skills/agents-and-societies/SKILL.md
Configure model providers, ModelFactory, ModelManager, provider enums, local/OpenAI-compatible endpoints, structured output, audio, or multimodal modelssub-skills/models-and-configuration/SKILL.md
Attach FunctionTool, built-in toolkits, MCP/OpenAPI tools, code execution, interpreters, runtimes, browser/Docker/terminal tools, or CAMEL servicessub-skills/tools-runtimes-and-services/SKILL.md
Add memory, retrieval/RAG, embeddings, vector/key-value/object/graph stores, loaders, datahubs, or datasetssub-skills/memory-rag-and-data/SKILL.md
Generate synthetic data, use data collectors, run verifiers/environments, or plan CAMEL benchmarkssub-skills/datagen-evaluation-and-benchmarks/SKILL.md

Cross-Cutting References

Safety And Scope

  • Start with credential-free inspection scripts and constructor/signature checks before calling models, services, datasets, browsers, Docker, or remote vector stores.
  • Do not install camel-ai[all] by default in automated environments; select extras by workflow to avoid heavyweight or unsupported optional dependencies.
  • Treat source examples and native tests as evidence; this skill is self-contained and does not require the original repository checkout at runtime.
  • Keep API keys, service URLs with secrets, OAuth tokens, model credentials, and local data paths outside generated prompts and skill files.

Signals

GitHub stars
266
Forks
21
Last commit
Sep 2026

ahel review

  • K1binfo
    installs-packages
  • K6low
    bundled executables the agent is told to run
  • K1binfo
    installs-packages (in sub-skills/agents-and-societies/scripts/inspect_agent_basics.py)
  • K1binfo
    installs-packages (in sub-skills/tools-runtimes-and-services/scripts/inspect_tool_schema.py)
  • K1binfo
    installs-packages (in references/troubleshooting.md)
  • K1binfo
    installs-packages (in sub-skills/memory-rag-and-data/references/troubleshooting.md)
  • K1binfo
    installs-packages (in sub-skills/tools-runtimes-and-services/references/toolkit-catalog.md)
  • K1binfo
    installs-packages (in sub-skills/tools-runtimes-and-services/references/troubleshooting.md)

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Catalog kind
skill
Gateway key
camel-ai
Source
github.com/vectorspacelab/arex-skill