deepseek-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: review_changes focuses on git diffs, review_files on complete files, and consult on general engineering questions. There is no overlap or ambiguity in what each tool does.
Naming Consistency4/5Two tools follow a consistent verb_noun pattern (review_changes, review_files), while consult is a single verb but still clear and in line with the action-oriented naming. Minor deviation from the review_ prefix but not chaotic.
Tool Count5/5Three tools is a well-scoped set for the server's purpose of providing DeepSeek-powered code assistance. Each tool covers a distinct need without unnecessary redundancy.
Completeness5/5The tool surface covers the full range of use cases for the domain: reviewing changes, reviewing existing files, and asking general engineering questions. No obvious gaps exist for an AI consultation server.
Average 4.4/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 7 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description adds the useful detail that the server reads the files, so the agent does not need to read them itself. This clarifies the execution model and aligns with openWorldHint, though it does not discuss limits or response structure. No contradictions found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose in the first sentence and usage context in the second. Every sentence earns its place with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two parameters, good annotations, and no output schema. The description covers purpose, usage, and calling convention. It does not explicitly describe the return format, but for a review tool the output is implied as the review itself, so completeness is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers both parameters with descriptions (repo-relative paths, focus). The description adds 'Pass paths only; the server reads them', which reinforces the paths parameter but does not introduce new semantic meaning. With high schema coverage, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides a DeepSeek review of complete files (resource) rather than a diff. It explicitly contrasts with diff-based review and gives example use cases (architecture, suspected bug, unfamiliar module), making the purpose unmistakable. The verb 'Get' is specific to the action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage context: use when the question is about existing code rather than a change, and lists concrete scenarios. It says 'rather than a diff' which implies the sibling tool review_changes, but it does not explicitly name the alternative tool, so it stops short of full explicitness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so safety is covered. The description adds valuable behavioral context: files are attached by path (not pasted), and prior turns are passed via 'history' to build on them. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, followed by two essential usage tips. Every sentence earns its place with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description fully covers the tool's purpose, main use cases, and important parameters. With 100% schema coverage and readOnly annotation, it provides enough context for an agent to select and invoke the tool correctly. No output schema needed for this Q&A tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, giving baseline 3. The description adds practical guidance beyond schema: 'Attach files by path rather than pasting them' clarifies 'paths', and 'pass the prior turns in history' clarifies 'history'. This adds meaning for parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Ask') with resource 'DeepSeek' and scope 'a specific engineering question as a second opinion', listing concrete use cases. This clearly distinguishes it from sibling review tools which focus on reviewing changes or files.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on when to use this tool (design trade-offs, uncertain decisions, hard-to-place bugs) and practical guidance on file attachment and multi-turn history. It does not explicitly name alternatives or state when-not-to-use, but the use cases make the intended usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds critical behavioral context beyond the readOnlyHint and openWorldHint annotations: the server runs the diff itself and the user must NOT paste code. It also discloses the return format ('findings grouped by severity with file:line anchors'), giving the agent a clear expectation of output. This is genuinely helpful and non-redundant.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, front-loaded with the core purpose, then usage guidance, a critical behavioral warning, and output format. Every sentence earns its place with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description explains exactly what the tool does, when to use it, a key usage caveat, and the return structure. Annotations cover safety and open-world assumptions. The description is fully self-sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% description coverage for all three optional parameters (base, focus, paths). The description's mention of 'which changes to look at' is consistent with the path/focus parameters but adds little semantic detail beyond the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get an independent code review from DeepSeek on the current git changes.' The verb 'get' plus the resource 'current git changes' is specific and distinguishes it from siblings like review_files (file-level) and consult (general consultation).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance ('Worth using for substantial changes... anything before a PR') and when-not-to-use ('not worth the round trip for one-line edits'). It does not explicitly name alternatives, but the context is clear enough for an agent to decide between this and related tools.
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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- Evaluate tool definition quality.
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