Dynamically select the best AI model for a task based on complexity, cost, and availability in GitHub Copilot. Use when deciding between free/paid models, or when you want automatic model routing based on query analysis.

This skill is plausible but has small inconsistencies you should resolve before trusting it. Steps to take before installing or running: - Open and read scripts/classify_task.py to confirm what it does: check for network calls, subprocess execution, or attempts to read files/credentials. If you are not comfortable inspecting it yourself, run it in an isolated sandbox. - Ensure you have the required runtime (likely Python). The SKILL.md should state how to run the script (python version, CLI args). Ask the author to add explicit run instructions. - Verify the models referenced in references/models.md actually map to models available in your environment (GitHub Copilot) — the examples include names from multiple providers, which may be inaccurate for Copilot-only routing. - Confirm there are no hidden data exfiltration behaviors (outbound network, telemetry) in the script before giving it access to real queries. - Because the source and homepage are unknown, treat this as untrusted code until you inspect it or obtain provenance from the publisher.

Type: OpenClaw Skill Name: dynamic-model-selector Version: 1.0.0 The skill bundle is benign. The `SKILL.md` file provides clear instructions for its intended purpose without any prompt injection attempts. The `classify_task.py` script performs only local text analysis using standard Python libraries (`sys`, `re`) and does not engage in any file I/O, network communication, environment variable access, or dynamic code execution. All content aligns with the stated goal of recommending an AI model based on query characteristics, lacking any indicators of malicious intent or high-risk behaviors.