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web-DnA

Navable MCP

by web-DnA
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Server Quality Checklist

67%
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  • Latest release: v0.3.0

  • Disambiguation5/5

    Each tool serves a distinct function: scanning, generating a fix plan, and updating status. No overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case (run_accessibility_scan, generate_fix_plan, update_fix_status) and clear verbs.

    Tool Count5/5

    Three tools is well-scoped for a specialized accessibility scanning and fix-planning domain, covering the essential actions without bloat.

    Completeness4/5

    Covers the core workflow: scan, generate plan, update status. Minor gaps like viewing the plan metadata or listing scans, but the set is complete for the primary use case.

  • 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
    • 3 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.

  • 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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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 indicate write (readOnlyHint=false) and non-destructive (destructiveHint=false). Description adds process details: reads, updates, writes, returns summary. No contradiction.

    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?

    Three concise sentences: purpose, usage, process. Front-loaded with action and resource. No fluff.

    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?

    Describes purpose, when to use, process (read, update, write), and return (summary). No output schema, but summary is implied. Covers all relevant aspects for a simple tool.

    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 has 100% description coverage for all 3 parameters. Description adds context about planPath resolving from project root, but does not add new parameter meaning beyond the schema. Baseline 3.

    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 ('Update'), specific resource ('items in .navable-plan.json'), and scope ('one or more'). Distinguishes from siblings 'generate_fix_plan' and 'run_accessibility_scan' which are different actions.

    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?

    Explicitly states when to use: 'Use after applying a fix to mark it as done, or to skip an item.' Implies not for generating plans or scanning. Mentions reading/writing file, but no explicit alternatives or exclusions.

    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?

    Beyond the readOnlyHint and destructiveHint annotations, the description adds that the URL must be reachable, explains engine behavior with deduping, and notes performance cost (~2-4s with HTMLCS). 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 well-structured with sections for engines and next step, concise yet informative, and front-loaded with the main purpose. No filler.

    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 complexity (6 params, no output schema), the description covers key aspects: engines behavior, performance, and next step. It could detail output structure more, but the mention of grouped violations and scanId is sufficient.

    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?

    With 100% schema coverage, baseline is 3. The description adds meaning for engines (deduping, default), tags, and compact format details, exceeding the schema's basic descriptions.

    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 scans a URL for WCAG 2.1 Level A+AA violations using Playwright and axe-core with optional Pa11y. It distinguishes from siblings by mentioning the next step of using generate_fix_plan with the scanId.

    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?

    It provides context for when to use the tool (scanning a URL) and directs the next step to generate_fix_plan. It does not explicitly state when not to use it or compare with alternatives, but the sibling distinction is clear.

    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 (readOnlyHint=false, destructiveHint=false) are minimal. The description compensates by disclosing write-to-disk behavior, fallback mechanism, and potential write failure. It does not explicitly state whether the file is overwritten, but the response always includes planPath.

    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?

    Description is well-structured with clear sections (preferred workflow, fallback, write location, response). While slightly verbose, each sentence serves a purpose. Front-loaded with core function.

    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 no output schema, the description explains the response includes planPath. It covers all usage scenarios, write location pitfalls, and parameter behaviors. Complete for a tool with 4 parameters and nested objects.

    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%, but the description adds significant context: scanId vs scan as preferred/fallback, default values for compact and writeToDisk, and limitations (server keeps last 10 scans). This aids the agent in parameter selection beyond schema.

    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 converts a scan result into a structured AccessibilityFixPlan and writes to a file. It distinguishes from siblings by referencing run_accessibility_scan as a prerequisite and update_fix_status as a separate tool.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly provides preferred workflow (step 1: run_accessibility_scan, step 2: generate_fix_plan with scanId) and fallback workflow (pass full scan JSON). Also details write location and environment variable configuration, guiding the agent on when to use which approach.

    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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