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ChromaDB Agent Router
v1.0.0Local semantic message routing for multi-agent systems. Routes messages to the correct agent based on embeddings + keyword + context scoring. No external API...
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by@mars375
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
Name/description align with required runtime (python3 + chromadb + numpy). The code implements a local ChromaDB-based router and exposes a localhost REST API, which is coherent with the stated purpose. However, the SKILL.md's metadata lists only chromadb and numpy as Python deps while the API wrapper requires additional packages (starlette, uvicorn) that are not declared—this is an inconsistency.
Instruction Scope
Runtime instructions (start API, POST /route) and the included code stay within routing functionality. The skill does create a local REST endpoint and writes a ChromaDB persistent cache under /tmp/semantic_router_cache/, both of which are documented in SKILL.md. The code does not read environment variables or unrelated system files.
Install Mechanism
SKILL.md contains a pip install step for chromadb and numpy (reasonable). But router-api.py and runtime require starlette and uvicorn (and possibly other transitives) which are not declared in the install metadata—this mismatch can cause broken installs or surprise network installs at runtime. Installing PyPI packages is moderate risk but acceptable if the exact packages/versions are declared; here they are not.
Credentials
The skill requests no environment variables, no credentials, and does not access system configs beyond writing a cache directory under /tmp. That level of access is proportionate to a local embedding indexer.
Persistence & Privilege
The skill persistently stores embeddings to /tmp/semantic_router_cache/chromadb (documented). It runs a local HTTP server bound to 127.0.0.1 (not public). 'always' is false. Storing cache on disk and running a localhost API are reasonable for this purpose but users should be aware of on-disk persistence of embeddings and route data.
What to consider before installing
This skill appears to implement a local ChromaDB-based router and mostly matches its description, but proceed with caution. Before installing: 1) Note the SKILL.md only declares chromadb and numpy, yet the API needs starlette and uvicorn — verify and install the full dependency list in a virtualenv (or container) rather than system-wide. 2) The skill writes embeddings to /tmp/semantic_router_cache; decide whether persisting embeddings on-disk is acceptable for your environment. 3) The router runs a localhost HTTP server (bound to 127.0.0.1) — that's safer than binding publicly, but confirm you don't expose the port via proxy or firewall. 4) The README claims '100% accuracy' on a small benchmark — treat that as an unverified marketing claim and validate with your own test dataset. 5) If you plan to use this in production or with sensitive data, run it in an isolated environment (container/VM) and pin package versions from trusted sources. Install only the packages you audit, and review or test the EXAMPLE_ROUTES to ensure no unintended routing of sensitive queries.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
Runtime requirements
Binspython3