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taichi
by
Indivisible
· GitHub ↗
· v2.1.0
· MIT-0
80
Downloads
0
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0
Active Installs
1
Versions
Install in OpenClaw
/install taichi
Description
太极架构多 Agent 协作框架,支持集中式、分布式,元混合三种执行模式。基于 Redis 消息总线,实现 Planner/Drafter/Validator/Dispatcher 四个阶段的工作流。
Usage Guidance
This package appears to be what it says: a Redis-based multi-agent orchestration framework. Before installing: (1) review configs/configs/skills/manifest.yaml and configs/communication.yaml to ensure allowed_commands and permission rules are strict; (2) inspect install.sh and start.sh and run them in an isolated environment or container (do not run as root); (3) secure Redis (bind to localhost or require AUTH) to avoid exposing the message bus; (4) be aware that tasks can cause the framework to run shell commands — template substitution is simple string replacement and commands are executed via the shell, so untrusted task input or a lax skill manifest can lead to command injection or arbitrary command execution; (5) if you will accept tasks from external/untrusted sources, harden the allowed_commands whitelist and/or use non-shell executors. If you want a more thorough risk assessment, provide the contents of configs/skills/manifest.yaml and configs/communication.yaml and the orchestrator invocation options.
Capability Analysis
Type: OpenClaw Skill
Name: taichi
Version: 2.1.0
The 'Taichi Framework' bundle contains a critical Remote Code Execution (RCE) vulnerability due to unsafe command execution in 'taichi-framework/core/skills/skill_executor.py'. The 'bash_executor' skill defined in 'taichi-framework/configs/skills/manifest.yaml' uses a template that performs simple string substitution of user-controlled parameters into a shell command. The associated whitelist check is flawed as it only validates the first word of the resulting command string (using shlex.split), which can be easily bypassed using command chaining characters like ';' or '&&'. This vulnerability is reachable through the framework's standard multi-agent workflow, where input from the PlannerAgent is passed to the DrafterAgent and eventually executed by a worker.
Capability Assessment
Purpose & Capability
Name/description (multi-agent orchestration using Redis) match the shipped code and SKILL.md: orchestrator, CentralizedBus/DistributedBus, Agent classes, Worker implementations, configs and a skill manifest are present. There are no unrelated credentials, binaries, or external downloads requested. One minor inconsistency: registry metadata listed this as 'instruction-only' but the package includes full source and install scripts (not a security problem by itself, but worth noticing).
Instruction Scope
SKILL.md instructs running the framework in a venv and requires Redis — that's coherent. However the framework's SkillExecutor executes commands via asyncio.create_subprocess_shell with naive template substitution (string replace) and only a first-word whitelist check. Because commands are executed through the shell, poorly configured skill manifests or untrusted task parameters could enable shell injection or arbitrary command execution. The runtime also reads permission files and YAML manifests from the package; verify those before use.
Install Mechanism
No network download install spec in registry; code includes local install.sh and venv-based installation that will pip-install pinned requirements.txt. No remote archive downloads or obscure URLs present in the provided files.
Credentials
The package does not require external credentials or environment variables in registry metadata. It expects a reachable Redis instance and local venv — which is proportional to a Redis-based orchestration framework. Note: if your Redis requires authentication you will need to supply credentials in config; the skill does not itself request cloud/secret env vars.
Persistence & Privilege
always is false and the skill does not request elevated platform privileges or modify other skills. It persists runtime state to a local workspace and SQLite DB (expected for orchestration) and can run autonomously (default), which is the platform norm.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install taichi - After installation, invoke the skill by name or use
/taichi - Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.1.0
Taichi 2.1.0 introduces a flexible multi-agent workflow framework with multiple execution modes:
- Supports centralized, distributed, and hybrid (meta-mixed) execution modes for various task scenarios.
- Implements a four-stage workflow: Planner, Drafter, Validator, Dispatcher, using a Redis message bus.
- Provides easy command-line usage examples for each mode.
- Updated documentation with mode descriptions, commands, and prerequisites.
- Requires a running Redis server and Python virtual environment.
Metadata
Frequently Asked Questions
What is taichi?
太极架构多 Agent 协作框架,支持集中式、分布式,元混合三种执行模式。基于 Redis 消息总线,实现 Planner/Drafter/Validator/Dispatcher 四个阶段的工作流。 It is an AI Agent Skill for Claude Code / OpenClaw, with 80 downloads so far.
How do I install taichi?
Run "/install taichi" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is taichi free?
Yes, taichi is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does taichi support?
taichi is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created taichi?
It is built and maintained by Indivisible (@indivisible2025); the current version is v2.1.0.
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