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zhiyan-detective

zhiyan-detective

by harveyzhang
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

verify_digest

一次查证最多 5 条 AI 消息，返回每条结论和一篇统一编号出处的快讯合集（Markdown），可直接改写成公众号文章。

Instructions

一次查证最多 5 条 AI 消息，返回每条结论和一篇统一编号出处的快讯合集（Markdown），可直接改写成公众号文章。

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": {
      "claims": "<claims>"
    },
    "name": "verify_digest"
  }
}

Input Schema

NameRequiredDescriptionDefault
claimsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It does disclose useful behavior — the hard limit of 5 claims per call, the per-claim conclusion, and the numbered-source Markdown digest — but says nothing about what happens with more than 5 claims, failure modes, or cost/latency implications.

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?

A single sentence that front-loads the batch limit, then the return shape, then the downstream use. No filler and no repetition of the tool name.

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?

For a one-parameter tool with no output schema and no annotations, the description covers input constraint and output format well. It stops short of clarifying edge cases (over-limit input, non-factual claims) or whether sources are externally fetched.

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

Parameters4/5

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

Schema coverage is 0% and the schema only says 'array of strings' with no constraints. The description compensates by establishing that each element is an AI claim and that at most 5 are allowed per call, which is the key semantic the schema omits.

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

Purpose4/5

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

States a specific verb (查证/verify) and resource (AI 消息/claims), plus the batch cap of 5 and the Markdown digest output. The batch scope implicitly separates it from the singular sibling verify_claim, but it never names that sibling, so differentiation relies on inference.

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

Usage Guidelines3/5

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

Usage is implied by '一次查证最多 5 条' — batch verification producing a publishable digest — but there is no explicit statement of when to prefer this over verify_claim for a single claim, nor any exclusion or prerequisite.

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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