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Inspect tool

inspect_tool
Read-onlyIdempotent

Read one third-party tool before running it: input_schema (body / queryParams / pathParams), price model (per_call, per_result, per_unit, tiered, free) with amounts as {usd, idr}, notes and health. Free. Always call this before run_tool so the input matches the schema and you know the cost.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "tool": "<tool>"
    },
    "name": "inspect_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
toolYesTool id from discover_tools, e.g. "dataforseo/serp/google-organic"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's added value is in payload and cost disclosure: it enumerates the returned sections (input_schema split into body/queryParams/pathParams, notes, health) and the price models with {usd, idr} amounts. It also flags "Free," which is a real cost signal. It stops short of return sizing or rate-limit details, but with no output schema this is still substantial.

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

Conciseness5/5

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

Two sentences, front-loaded with the action and followed by the mandatory ordering constraint. Every clause carries new information — no restatement of the title or annotations.

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

Completeness5/5

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

For a one-parameter, annotation-covered read tool with no output schema, the description supplies exactly what's missing: what the response contains and what the cost model looks like. Nothing an agent needs in order to call it correctly is absent.

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 description coverage is 100% and the single parameter already documents itself with a concrete example id from discover_tools. The description adds no format, syntax, or validation detail beyond that, so the schema carries the burden and baseline 3 applies.

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 specific verb and resource ("Read one third-party tool") and immediately scopes it as a pre-execution step, which separates it cleanly from discover_tools (find tools) and run_tool (execute). An agent can place this tool in the workflow without opening any schema.

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

Usage Guidelines5/5

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

Explicitly prescribes the ordering: "Always call this before run_tool," and gives the two reasons (matching input to schema, knowing the cost). The alternative sibling is named along with the condition that selects it, leaving nothing to inference.

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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