mcp-document-assistant
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: listing document IDs, reading a document's contents, and editing an existing document. There is no overlap or ambiguity between them.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern: list_documents, read_document, edit_document. The naming is predictable and easy to infer.
Tool Count5/5With only 3 tools, the server is tightly focused on core document operations. Each tool serves a distinct need, and the count is well within the ideal range.
Completeness2/5The tool surface covers listing, reading, and editing documents but lacks create and delete operations, which are fundamental to document lifecycle management. This is a significant gap that will likely force agents to rely on external processes for these actions.
Average 3.6/5 across 3 of 3 tools scored. Lowest: 2.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 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
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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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source for behavioral disclosure. It does not mention whether the edit overwrites the entire content, creates a new version, or handles missing documents, and it gives no indication of required permissions or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It is appropriately concise for a simple tool, though it lacks supporting detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has two required parameters and an output schema, but the description is minimal. It does not cover preconditions, side effects, or behavior on failure, leaving the agent underinformed for a tool that modifies state.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema lists 'doc_id' and 'content' with zero description coverage. The description adds no additional meaning beyond the word 'contents,' failing to clarify the expected format of 'content' or the role of 'doc_id.'
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 states 'Edit the contents of an existing document,' which clearly names the action (edit), the resource (document), and the scope (existing). This directly distinguishes it from sibling tools 'list_documents' and 'read_document'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any exclusion criteria. The description only states what it does, leaving usage implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It states the tool returns a list of all available document IDs, which implies a read-only action, but it does not explicitly mention side effects, safety, or any limitations. It is transparent about the primary behavior but lacks detail beyond that.
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 a single, concise sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and easy to parse, earning a perfect score for conciseness.
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?
Given the zero-parameter schema and existence of an output schema, the description adequately captures the tool's function. It does not explain nuances like 'available' or provide retrieval context, but for a simple list tool with no inputs, the description is sufficiently complete.
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?
The tool has zero parameters, and the schema confirms this with 100% coverage. Per the scoring rule, a baseline of 4 is appropriate because the description cannot add value for nonexistent parameters.
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 'Return a list' and identifies the resource 'document IDs', clearly distinguishing it from sibling tools read_document and edit_document. This is a precise and unambiguous statement of the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used to obtain document IDs for subsequent read/edit operations, but it does not explicitly state when to use it versus alternatives or provide exclusions. Contextual clues from sibling names suggest the use case, but guidance is not explicitly provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral disclosure burden. It states the core read operation but does not mention error behavior, return format, or any other side effects. The read-only nature is implied by the name, but no additional context is provided. It neither contradicts annotations nor adds significant depth beyond the obvious.
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 a single, front-loaded sentence with no filler. It states the action and the key input in minimal words, earning every word. It is concise and well-structured.
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?
This is a simple tool with one parameter and an output schema, so the description need not explain return values. It sufficiently covers the core function and identifies the required input. However, it could be more complete by explicitly guiding when to use this tool versus siblings, which would elevate the contextual guidance.
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 description coverage is 0%, so the description must compensate. It does so by explaining that doc_id is the 'document ID' that identifies the document to read. This gives the parameter meaning beyond the bare schema property name, though it does not specify how to obtain the ID (e.g., from list_documents) or the expected format.
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 action ('Return the contents'), the resource ('a document'), and the condition ('given its document ID'). It is immediately distinguishable from siblings list_documents (listing) and edit_document (modifying), so the purpose is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied: if you have a document ID and need its contents, use this tool. However, there is no explicit guidance on when not to use it or which alternative (e.g., list_documents for metadata) to choose. No alternatives are named, so it does not fully meet the 'explicit when/when-not' standard.
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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