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ToolFit + MCPCheck

Audit a tool list (ToolFit)

audit_tools
Read-onlyIdempotent

Check the tool definitions an agent loads, before they cost tokens or fail: estimated tokens per tool, schema errors per provider (OpenAI, Anthropic, Gemini, Bedrock, MCP; add openai_strict for strict mode) with JSON paths and fixed definitions, tool pairs models will confuse with fix hints, basic poisoning patterns, a grade and a pin (set_id) for diff_tools. Pass "tools" (array in any common format) or "url" (public remote MCP server; tools are listed, never called). level "lite" returns the summary only. Free: 20 calls/day per IP (shared with diff_tools), then $0.003 lite / $0.01 full via x402 or credits.

Input Schema

NameRequiredDescriptionDefault
urlNoPublic remote MCP server URL (Streamable HTTP, https), e.g. https://api.youraitools.co/mcp/hub. ToolFit only lists its tools.
levelNolite = summary only; full (default) = every issue, fixed definitions, pair hints
toolsNoTool definitions: MCP tools/list entries, OpenAI {type:"function",function:{...}}, Anthropic {name,description,input_schema}, Gemini functionDeclarations or Bedrock toolSpec. Max 500.
providersNoProviders to check (default openai, anthropic, gemini, bedrock, mcp; add openai_strict for Structured Outputs strict mode). GET: comma list.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark it read-only, idempotent, and open-world; the description adds genuinely new behavior: remote MCP servers are only listed, never called, the 500-tool cap, the 20 calls/day free limit shared with diff_tools, and pricing after that. It stops short of describing error behavior or partial-failure handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

All the content is relevant and the purpose is front-loaded, but it is delivered as one sprawling 100+ word sentence with stacked clauses and a pricing tail, which makes it harder to scan than a short bulleted structure would be.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description still enumerates what comes back (token counts, schema errors with JSON paths and fixed definitions, pair hints, grade, set_id), so an agent knows what to expect. A note on partial failures or when no issues are found would complete it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all four parameters, their enums, and accepted formats. The description only adds marginal meaning, such as reminding that openai_strict is for strict mode and that lite yields summary only, both of which are effectively restated in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb and resource: audit a list of tool definitions, returning token estimates, per-provider schema errors, confusion pairs, poisoning signals, a grade, and a set_id. It names the sibling it feeds (diff_tools) and is clearly distinguishable from check_mcp_server and the watch_* tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explains the trigger clearly ('before they cost tokens or fail') and gives the two mutually exclusive input paths (tools array vs. url). It explains lite vs. full and that set_id feeds diff_tools, but never states when NOT to use it or how it differs from check_mcp_server.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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