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by wuzenghai616-lang
OverviewSchemaSourceRelated ServersDiscussions(4)Admin
JavaScript
Remote

baidu_text_corrector

Detects and fixes spelling, grammar, and punctuation mistakes in text. Applies natural language processing for corrections.

Instructions

[NLP] 文本纠错 — $0.01/call (free: 5/5 today)

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": {
      "text": "<text>"
    },
    "name": "baidu_text_corrector"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes待纠错文本

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It only mentions cost and a daily free limit, but does not clarify whether it modifies input, returns corrections, or any side effects. The correctness behavior is implied but not explicit.

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

Conciseness4/5

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

The description is very short and front-loaded with a tag. It efficiently conveys the core purpose and pricing, though it sacrifices some clarity. It could be slightly more informative without adding length.

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

Completeness2/5

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

Given the simple input schema and no output schema or annotations, the description should provide more context about the output format or usage. It lacks completeness, leaving the agent uncertain about what the tool returns.

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% for the single parameter 'text', which already has a description ('待纠错文本'). The tool description adds no additional meaning, such as constraints on text length or encoding, so it meets the baseline 3.

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

Purpose3/5

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

The description states the tool does text correction ('文本纠错'), which provides a verb and resource. However, it lacks specifics such as language support or scope, and does not differentiate it from siblings like baidu_nlp. The pricing info is ancillary.

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

Usage Guidelines2/5

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

No guidance is given on when to use this tool versus alternatives such as baidu_nlp or baidu_sentiment. There is no mention of prerequisites, context, or when not to use it.

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

Deploy Server

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