DocGuard

by raccioly

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Server Quality Checklist

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Latest release: v0.33.1
Disambiguation5/5
Each tool has a distinct, non-overlapping purpose: diagnose finds issues, explain clarifies finding codes, guard runs validation, report generates compliance evidence, score computes maturity, and verify_claims extracts semantic claims. No ambiguity.
Naming Consistency5/5
All tools follow a consistent verb-based pattern (docguard_verb) with clear, descriptive verbs (diagnose, explain, guard, report, score, verify_claims). No mixing of conventions.
Tool Count5/5
With 6 tools, the server covers the core workflow of documentation validation and compliance without being too sparse or overwhelming. Each tool earns its place.
Completeness4/5
The tool set covers diagnosis, explanation, full validation, compliance evidence, maturity scoring, and claim extraction. A minor gap is the lack of a tool to directly apply fixes or manage suppressions, but diagnose provides actionable suggestions.
Average 4.2/5 across 6 of 6 tools scored. Lowest: 3.6/5.
See the Tool Scores section below for per-tool breakdowns.
- 12 of 15 community issues answered or closed in the last 6 months
- 96 commits in the last 12 weeks
- Last stable release on August 13, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds minimal behavioral context beyond stating the output format (letter grade and breakdown). It does not contradict annotations but also does not disclose additional traits like performance characteristics or required environment setup.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that immediately conveys the tool's purpose and output format. Every word adds value, and there is no redundancy or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single optional parameter, rich annotations, and clear output description (score range, letter grade, breakdown), the description is sufficiently complete for the tool's complexity. It lacks only a mention of whether the score is computed immediately or cached, but this is minor.
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 provides full coverage for the single parameter (projectDir), including its type, description, and default behavior. The tool description adds no further parameter-specific semantics, so it meets the baseline for complete schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes a CDD maturity score with a specific range (0-100), letter grade, and per-category breakdown. It uses a specific verb ('Compute') and identifies the resource ('project's CDD maturity score'), distinguishing it from sibling tools like docguard_diagnose or docguard_explain.
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 provided on when to use this tool versus its siblings. The description only states what the tool does without mentioning prerequisites, preferred scenarios, or trade-offs relative to other tools like docguard_verify_claims.
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 indicate read-only, idempotent, non-destructive. Description adds value by specifying the output format (structured findings, suggested actions) and the focus on actionable items, but does not detail all behavioral aspects like response structure or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is front-loaded with the core action and outcome, no wasted words. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (1 optional param, read-only, no output schema), the description adequately covers the tool's purpose and output. Lack of explicit return format is a minor gap, but the description's mention of 'structured findings' provides enough context for an agent.
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 description coverage is 100% for the single parameter, so baseline 3 is appropriate. Description does not add extra meaning beyond the parameter's existing description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'run guard' and specific resource 'only what needs fixing', listing concrete outputs: failing/warning validators, messages, structured findings, suggested next actions. Distinguishes from sibling tools like docguard_guard (full run) and docguard_explain (explanation).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for actionable diagnostics, but no explicit 'when to use' vs. alternatives like docguard_guard or docguard_score. Does not provide exclusions or prerequisites.
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, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context beyond annotations by detailing the return contract structure (status, findings, suggestions, nextStep, etc.), which helps the agent understand what to expect. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: the first states the action, the second lists the output. Every sentence adds value, and it is front-loaded with the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description thoroughly explains the return value (full guard JSON contract with fields like status, findings, suggestions, etc.). The tool is simple (one optional param), and the description covers everything needed for correct invocation.
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 (projectDir), and the description does not add any additional meaning beyond the schema. The baseline of 3 is appropriate as the schema already documents the parameter fully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Run every enabled DocGuard validator'), the resource ('project's canonical docs'), and the output ('full guard JSON contract'). It distinguishes this tool from siblings like docguard_diagnose or docguard_score by indicating it runs all validators comprehensively.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a full validation run but lacks explicit guidance on when to choose this tool over siblings (e.g., diagnose for specific issues, score for scoring). No 'when to use' or 'when not to use' is provided.
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 mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context: it reports state without failing, includes a tamper-evident sha256 hash, and outlines bundle contents. No contradictions 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two well-structured sentences. The first sentence lists the bundle contents, and the second clarifies the purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one optional parameter and no output schema, the description provides sufficient context about what the bundle includes and that it reports state without failing. Complete for its complexity.
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 single parameter 'projectDir' has a clear schema description. The tool description does not add additional semantic detail beyond the schema, but schema coverage is 100% and the parameter is straightforward, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a 'commit-stamped compliance-evidence bundle' and lists its contents (verdict, findings, CDD score, etc.). It distinguishes from siblings by noting it reports state without failing, making it unique among the sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clarifies that this tool produces evidence, not a gate, implying it should be used when reporting state rather than enforcing compliance. It implicitly distinguishes from other tools like docguard_guard, but does not explicitly state when to use alternatives.
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 indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds 'Deterministic discovery, LLM judgment' and clarifies the caller's role, providing useful behavioral context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main action ('Extract...'), and every part adds value. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and full schema coverage, the description explains the output (task list of claims) and the process (deterministic discovery, LLM judgment, caller verification). It is complete without needing output schema.
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 schema covers 100% of the single parameter (projectDir) with a clear description. The tool description does not repeat param info, which is acceptable given full schema coverage. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Extract the semantic claims in the project's canonical docs' with a specific verb and resource. It distinguishes from sibling tools like docguard_diagnose, docguard_explain, etc., by focusing on extraction for verification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for extracting claims to verify against code, with 'the caller verifies each claim against the code.' It provides context but does not explicitly state when not to use or alternatives, though sibling names suggest differentiation.
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?
Annotations indicate readOnly, idempotent, non-destructive. The description adds value by detailing what the tool returns (meaning, validator, suppression), and specifies it works on 'stable' codes, providing clarity beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with verb and examples, no wasted words. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity (one parameter, no output schema), the description fully explains the tool's purpose, behavior, and return value. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the 'code' parameter described. The description adds context about stability and case-insensitivity, and provides examples, reinforcing schema details with minimal redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Explain a stable DocGuard finding code', specifying verb (explain), resource (finding code), and outputs (meaning, validator, suppression). It distinguishes from siblings like docguard_diagnose by focusing on explanation rather than diagnosis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context on when to use it (for stable codes, e.g., STR001), and hints at usage for false positives. However, it lacks explicit when-not or alternatives, though the context is sufficient for an agent to decide.
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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