Token Budget Advisor
v1.0.1Offer users informed choice about response depth before answering. Control token usage, response length, and answer depth. Trigger phrases: token budget, tok...
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byDeonte Cooper@djc00p
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 name and description (controlling token usage/response depth) match the SKILL.md instructions. It doesn't request unrelated binaries, environment variables, or config paths.
Instruction Scope
The instructions are focused on prompting the user for a depth option, estimating token usage heuristically, and then producing answers at that level. They require access to session context (to know if depth was already set) and give the agent some discretion about when to trigger, which is expected but somewhat subjective. No file I/O, external network endpoints, or secret exfiltration are requested.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only, so nothing is written to disk and no external packages are pulled.
Credentials
The skill declares no required environment variables or credentials. The runtime instructions do not reference any secrets or config beyond session state, so requested access is proportionate to the stated function.
Persistence & Privilege
The skill asks the agent to 'maintain user's chosen level for rest of session.' This implies session-state persistence but does not request permanent or cross-skill configuration or always-on privileges. Users should verify how the host agent stores session preferences (in-memory vs persistent storage) if that matters to them.
Assessment
This skill looks coherent and low-risk: it will ask users to pick a response depth and remember that choice during the session, estimate token usage heuristically, and then answer accordingly. It does not request credentials or install code. Things to consider before enabling: test how often it triggers (its trigger rules are somewhat subjective), confirm how your agent persists session preferences (if persistent storage is a concern), and be aware token estimates are approximate since it uses a heuristic rather than a tokenizer.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
💰 Clawdis
OSLinux · macOS · Windows