GoldBean

baidu_deepthink

Solve complex reasoning problems by triggering DeepSeek-R1 chain-of-thought. Each call costs $0.005, with 5 free calls daily.

Instructions

[LLM] 深度思考（DeepSeek-R1 链式推理） — $0.005/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": {
      "message": "<message>",
      "model": "<model>"
    },
    "name": "baidu_deepthink"
  }
}

Input Schema

Name	Required	Description	Default
`model`	Yes	模型名(可选)
`message`	Yes	推理问题

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.0.0Jul 13, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided. The description only mentions pricing and a free limit, but does not disclose response format, token limits, or any side effects. The behavioral burden is not met.

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 a single line with an [LLM] prefix, making it front-loaded and concise. However, the Chinese characters may affect readability.

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?

For a complex LLM tool with no output schema, the description is too sparse. It lacks information on return values, model options, and usage constraints.

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% with descriptions for both parameters. The description does not add any additional meaning beyond the schema, so it meets the baseline.

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?

The description uses '深度思考（DeepSeek-R1 链式推理）' to indicate a deep reasoning LLM tool, distinguishing it from other Baidu tools. The [LLM] tag and pricing add context, but the use of Chinese may reduce clarity for some users.

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 on when to use this tool versus other LLM tools like baidu_llm_chat. The description does not specify context or alternatives.

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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