Arya Model Router
v0.1.0Efficiently routes tasks between cheap, default, and pro models using optional sub-agents and briefing to minimize token use and cost.
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The files and runtime instructions match the stated purpose: router.py implements local routing/thresholds/overrides and brief.py creates a compact brief. The rule set lists models and thresholds consistent with a model router. Minor inconsistency: SKILL.md metadata lists required bins (bash, python3) while the registry 'Requirements' section reported none — this is a small metadata mismatch (python3 is logically required to run the scripts).
Instruction Scope
SKILL.md and README instruct running local scripts (router.py, brief.py) and interpreting JSON output. The scripts only read/edit local files (rules.json, state.json) and do no network or model calls themselves. Important operational note: brief.py extracts lines that look like URLs, job IDs, stack traces, etc.; if the downstream integration sends the brief to a remote model (e.g., an OpenAI model recommended by the router), that brief could contain sensitive tokens/IDs/URLs you supplied in the context. The router itself does not exfiltrate data, but the decisions it emits may cause other components to send data to external models.
Install Mechanism
No install spec (instruction-only skill with bundled scripts). No downloads or external installers are used; files are local and static, which is lower risk.
Credentials
The skill requests no environment variables or credentials and does not access system-wide config. The SKILL.md metadata's 'bins' requirement (bash, python3) is reasonable for running the included scripts. There are no unrelated secrets requested.
Persistence & Privilege
The skill writes and updates a local state file (state.json) in its own directory to store mode/feedback/lastDecision — this is scoped to the skill and expected. always is false and the skill does not modify other skills or system-wide agent settings.
Assessment
This skill appears to be what it says: a local router that decides when to escalate to stronger models. Before installing, consider: 1) It writes rules.json and state.json in the skill folder — review and back up those files if you edit them. 2) brief.py will surface URLs, job IDs, errors and similar 'interesting' lines; do not pass sensitive tokens/credentials in context you expect to be briefed and potentially forwarded to an external model. 3) The router only emits decisions (model names like openai/gpt-4.1); actual calls to remote LLMs happen elsewhere — ensure any downstream integration that executes 'use_subagent' is authorized and has appropriate API keys and data-handling policies. 4) Ensure python3 is available (SKILL.md lists bash and python3). 5) Optionally review and customize rules.json thresholds/keywords to match your workload and to avoid unnecessary escalation. If you want a second check, provide how your agent invokes sub-agents (what component accepts 'use_subagent' and whether it will send briefs to remote models).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.