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camel-ai

Use CAMEL-AI to build, configure, tool, remember, evaluate, and troubleshoot multi-agent Python systems with self-contained routing across agents, models…

Skill by VectorSpaceLab

IndexedApache-2.0★ 341
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/vectorspacelab-camel-ai

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About

Use CAMEL-AI to build, configure, tool, remember, evaluate, and troubleshoot multi-agent Python systems with self-contained routing across agents, models, tools, RAG, and evaluation workflows.

Use cases: ml, agent-building

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/camel-ai

What's inside

Skill name
camel-ai
Description
Use CAMEL-AI to build, configure, tool, remember, evaluate, and troubleshoot multi-agent Python systems with self-contained routing across agents, models, tools, RAG, and evaluation workflows.
License
Apache-2.0
Metadata
disco-role: operating
Instructions
36 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (36)

  • SKILL.md
  • package-overview.md · references/
  • repo-provenance.md · references/
  • repo-routing-metadata.json · references/
  • troubleshooting.md · references/
  • inspect_camel_install.py · scripts/
  • SKILL.md · sub-skills/agents-and-societies/
  • api-reference.md · sub-skills/agents-and-societies/references/
  • troubleshooting.md · sub-skills/agents-and-societies/references/
  • workflows.md · sub-skills/agents-and-societies/references/
  • inspect_agent_basics.py · sub-skills/agents-and-societies/scripts/
  • SKILL.md · sub-skills/datagen-evaluation-and-benchmarks/
  • api-reference.md · sub-skills/datagen-evaluation-and-benchmarks/references/
  • benchmarks.md · sub-skills/datagen-evaluation-and-benchmarks/references/
  • troubleshooting.md · sub-skills/datagen-evaluation-and-benchmarks/references/
  • workflows.md · sub-skills/datagen-evaluation-and-benchmarks/references/
  • inspect_eval_components.py · sub-skills/datagen-evaluation-and-benchmarks/scripts/
  • SKILL.md · sub-skills/memory-rag-and-data/
  • api-reference.md · sub-skills/memory-rag-and-data/references/
  • data-workflows.md · sub-skills/memory-rag-and-data/references/
  • storage-selection.md · sub-skills/memory-rag-and-data/references/
  • troubleshooting.md · sub-skills/memory-rag-and-data/references/
  • workflows.md · sub-skills/memory-rag-and-data/references/
  • inspect_rag_components.py · sub-skills/memory-rag-and-data/scripts/
  • SKILL.md · sub-skills/models-and-configuration/
  • api-reference.md · sub-skills/models-and-configuration/references/
  • configuration.md · sub-skills/models-and-configuration/references/
  • provider-patterns.md · sub-skills/models-and-configuration/references/
  • troubleshooting.md · sub-skills/models-and-configuration/references/
  • inspect_model_registry.py · sub-skills/models-and-configuration/scripts/
  • SKILL.md · sub-skills/tools-runtimes-and-services/
  • api-reference.md · sub-skills/tools-runtimes-and-services/references/
  • runtime-service-patterns.md · sub-skills/tools-runtimes-and-services/references/
  • toolkit-catalog.md · sub-skills/tools-runtimes-and-services/references/
  • troubleshooting.md · sub-skills/tools-runtimes-and-services/references/
  • inspect_tool_schema.py · sub-skills/tools-runtimes-and-services/scripts/

SKILL.md (first lines)

# CAMEL-AI Repo Skill

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](scripts/inspect_camel_install.py) for a no-network import, version, and route check.
4. Read [references/troubleshooting.md](references/troubleshooting.md) before installing broad extras, debugging provider credentials, or running network/Docker/browser/benchmark workflows.

## Route By Task

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

## Cross-Cutting References

- [references/package-overview.md](references/package-overview.md) summarizes package surfaces, optional extras, and support modules such as prompts, personas, schemas, responses, caches, parsers, configs, and utilities.
- [references/troubleshooting.md](references/troubleshooting.md) covers install/import failures, optional dependencies, credentials, data/config validation, and workflow-specific escalation.
- [references/repo-provenance.md](references/repo-provenance.md) records the source commit, package version, evidence paths, and dirty-state baseline used to create this skill.
- [references/repo-routing-metadata.json](references/repo-routing-metadata.json) is structured metadata for the managed `repo-skills-router` import process.

## 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.

From VectorSpaceLab/AREX-Skill, Apache-2.0.

More from VectorSpaceLab/AREX-Skill

Signals

Stars
341
Forks
26
Open issues
0
Last commit (this folder)
Aug 26, 2026 (2 months ago)
Last release
Sep 2, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from VectorSpaceLab

Cite this page

camel-ai skill. Agent Mart. https://agentmart.dev/skills/vectorspacelab-camel-ai (last updated 2026-10-24)