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DeepSeek-MCP

DeepSeek-MCP

by Abbas-F-R
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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review_project

Perform a comprehensive project review with DeepSeek Reasoner. Submit a project summary and receive high-level analysis, insights, and recommendations.

Instructions

Perform a comprehensive high-level project review utilizing DeepSeek Reasoner model

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": {
      "project_summary": "<project_summary>"
    },
    "name": "review_project"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNoModel to use (default: deepseek-reasoner)
providerNoAI Provider (default: deepseek)
project_summaryYesOverview and code structure of the project

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only notes that the DeepSeek Reasoner model is used, which hints at a backend dependency, but gives no details on input expectations (that it needs a project_summary rather than repository access), output format, or potential side effects. This is insufficient for a tool with zero annotation support.

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 sentence, making it concise and front-loaded with the main purpose. The phrase 'utilizing DeepSeek Reasoner model' is slightly awkward and arguably redundant given the 'model' parameter's default, but it does not waste many words. It is appropriately short for a simple purpose.

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 lack of an output schema and annotations, the description is too minimal. It does not explain what the tool returns (e.g., a textual review report), how it consumes the project_summary, or how it differs from similar comprehensive tools like 'summarize'. The one-liner leaves significant gaps in the agent's understanding, making selection and invocation riskier.

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?

The input schema already provides full descriptions for all three parameters: model, provider, and project_summary. The description adds no extra meaning beyond what the schema already documents, and does not clarify how the parameters interrelate or influence the review output. With 100% schema coverage, a baseline of 3 is appropriate.

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 clearly states the tool performs a 'comprehensive high-level project review', providing a specific verb and resource. It also mentions using the DeepSeek Reasoner model, which adds specificity. However, it does not explicitly distinguish itself from sibling tools like review_architecture or review_code, so it misses the full sibling differentiation needed for a 5.

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?

The description offers no explicit guidance on when to use this tool versus its many siblings. It doesn't mention suitable use cases, exclusions, or alternatives. The phrase 'high-level' implies it's for broad overviews, but this is not clearly stated as a directive.

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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