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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct role: detect_version identifies project context, search_docs finds relevant documentation pages, and get_doc retrieves page content. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    All tool names follow the same snake_case verb_noun pattern: detect_version, search_docs, get_doc. The naming is predictable and consistent.

    Tool Count5/5

    Three tools is a well-scoped size for a documentation server. Each tool covers a necessary step in the workflow: version detection, searching, and fetching content.

    Completeness5/5

    The tool set forms a complete workflow: detect version, search relevant docs, and retrieve specific pages or sections. There are no obvious dead ends or missing core operations for documentation access.

  • Average 4.1/5 across 3 of 3 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 8 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?

    With no annotations provided, the description carries the full burden of disclosing behavior. It clearly states that the tool reads the project's package.json, which implies a read-only, non-mutating operation. It also describes the kind of information it reports. It doesn't detail error handling or missing-package.json scenarios, but the key behavioral trait is disclosed.

    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 front-loads the action and resource, then lists the outputs. Every clause adds value and there is no redundant or filler text.

    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?

    The tool has one parameter, no output schema, and no annotations. The description explains the expected input and the high-level output: major version, related packages, and matching docs source. It could be more specific about the structure of the output or edge cases, but for a simple detection tool it is reasonably complete.

    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%, and the parameter description in the schema already explains what projectPath means. The tool description itself adds no additional parameter semantics beyond what the schema provides, so the baseline score 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 uses a specific verb ('Reads ... and reports') and clearly identifies the resource (project's package.json) and the outputs (AdonisJS major version, related packages, matching docs source). It is easily distinguished from the sibling tools search_docs and get_doc, which focus on documentation lookup rather than project inspection.

    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 a usage context: determining the AdonisJS version and correct docs source before using docs tools. However, it does not explicitly state when to use this tool versus the sibling tools, nor does it name alternatives or exclusions. The guidance is inferred rather than stated.

    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?

    With no annotations provided, the description carries the behavioral disclosure burden. It explains that the tool returns a 'compact ranked list of doc ids,' which tells the agent results are not full page content and that a follow-up call to get_doc is needed. It does not mention rate limits, auth, or failure behavior, but those are minor for a read-only docs search tool.

    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 compact: two sentences deliver the search scope, the return format, and the routing to get_doc. It is front-loaded and free of filler. It loses a point because the parenthetical library list is incomplete and slightly restates the title's 'AdonisJS docs' concept.

    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 schema's thorough parameter descriptions and the absence of an output schema, the description sufficiently explains the return shape and how to proceed. It also gives enough context for chaining with get_doc. It could have mentioned version auto-detection behavior or the full library enum, but the schema already handles those details.

    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 already provides 100% coverage with clear descriptions for all five parameters, including enums for library and version, so the baseline is 3. The description adds little parameter-level meaning beyond a partial library list, and omits vine/japa. It does not compensate for or improve on the schema's parameter documentation.

    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 states a specific verb and resource: 'Keyword search over AdonisJS documentation.' It also distinguishes itself from get_doc by explaining that the output is a ranked list of doc ids meant to be passed to get_doc. Though the parenthetical omits vine/japa libraries, the overall purpose is unmistakable and the schema fills that gap.

    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 clearly frames when to use this tool: when you need to find relevant documentation pages via keyword search. It also tells the agent what to do next: 'pass an id to get_doc to read the page.' It does not explicitly discuss the detect_version sibling or state when not to use search_docs, so it is not a full when/when-not guide.

    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?

    With no annotations, the description carries the behavioral burden. It discloses the return format (plain markdown/asciidoc) and the section-filtering behavior, including the 'cheaper than the full page' performance hint. It does not mention errors or edge cases, but for a read-only doc fetcher this is reasonable.

    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?

    Two concise sentences with no filler. The core purpose and id source are front-loaded, and the section usage tip earns its place by providing actionable guidance.

    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?

    The description is adequate for a fetch-by-id tool: it identifies the id source, output format, and a useful partial-fetch option. The rich schema covers parameters and defaults. A little more context about behavior when no id is found or when maxLength truncates output would round it out, but nothing critical is missing.

    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%, so the baseline is 3. The description adds only a little beyond the schema, mostly reinforcing the 'section' parameter's purpose. It does not need to compensate for missing parameter docs.

    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?

    States a specific verb and resource: 'Fetches a documentation page by id' as plain markdown/asciidoc. The phrase 'from search_docs' distinguishes it from the search sibling and makes the intended fetch-by-id role clear.

    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?

    Implies the correct flow by saying the id comes from search_docs, and gives explicit guidance on when to use 'section' for a cheaper partial fetch. It stops short of stating when not to use get_doc or comparing it directly to detect_version, but the context is clear.

    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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