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parasxos

cpp26-adapter

by parasxos
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Server Quality Checklist

83%
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  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool serves a distinct purpose: compiler_status checks compiler support, lookup_paper retrieves full paper details, and search performs free-text queries. There is no functional overlap.

    Naming Consistency4/5

    All tool names use lowercase with underscores, but 'compiler_status' and 'lookup_paper' follow a verb_noun pattern while 'search' is a single verb. The inconsistency is minor.

    Tool Count5/5

    With 3 tools, the server is well-scoped for its purpose. Each tool provides essential functionality without being excessive or too sparse.

    Completeness4/5

    The tools cover searching, retrieving paper details, and checking compiler support. A missing feature is a way to list all papers, but the search tool can approximate this with broad queries.

  • Average 4.6/5 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
    • Last stable release on
    • 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.

  • This repository includes a glama.json configuration file.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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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?

    No annotations provided, so the description carries the burden. It discloses the output format (YAML frontmatter and prose body) and error conditions (FileNotFoundError for unknown/missing papers). It implies a read operation, which is appropriate.

    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 and well-structured: a main sentence followed by Args, Returns, and Raises sections. Every sentence adds value, and the key purpose is front-loaded.

    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 straightforward lookup tool with one parameter and an output schema, the description covers purpose, parameter usage, return content, and error cases. It is fully self-contained and 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.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has one parameter 'paper_id' with only a title. The description adds meaning by specifying it's a 'WG21 paper identifier' with examples (e.g., 'P2996'), which goes beyond the schema's type definition.

    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 it returns the full markdown reference for a C++26 paper, with a specific verb and resource. It distinguishes from siblings like compiler_status and search by focusing on paper lookup.

    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 explains when to use the tool (to get a paper's reference) with an Args section for the parameter and a Raises section for errors. It does not explicitly mention alternatives or when not to use, 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.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description details the fuzzy matching algorithm (rapidfuzz WRatio), field weighting (title ×2), and edge cases (empty list for blank query or empty index). It lacks mention of read-only nature but is otherwise transparent.

    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 each sentence adding value. It starts with the primary purpose, then details matching, parameters, and return format, without redundancy.

    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 tool complexity and available schema/documentation, the description covers purpose, parameters, behavior, and return values. Minor omission: no explicit statement that the tool is read-only, but overall complete for agent usage.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description explains both parameters beyond the schema: 'query' is exemplified with realistic queries, and 'top_k' is described with default value and purpose. Since schema coverage is 0%, this is essential and well-done.

    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 it is a free-text search over the C++26 paper index, with specific verb and resource. It distinguishes from sibling tools (compiler_status, lookup_paper) by focusing on fuzzy search.

    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 example queries, implying use for free-text search. It does not explicitly exclude cases or mention siblings, but the context makes its usage 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?

    With no annotations, the description discloses that it is informational only, returns a dict with specific fields, and handles unknown papers/compilers. It does not mention side effects or rate limits, but the read-only nature is implied. A score of 4 is appropriate as it adds sufficient context.

    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 a clear first line, usage guidelines, args, and returns. It is front-loaded with the purpose and every sentence adds value. No redundancy.

    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 the tool has 2 parameters and an output schema, the description is fully complete: it explains parameter formats, return structure, and behavioral constraints. It addresses edge cases like unknown papers. No gaps.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The description adds significant meaning beyond the schema: it specifies that 'paper_id' is a WG21 paper ID with example 'P2996', explains 'compiler' with key examples and default behavior when omitted. Schema coverage is 0%, so the description fully compensates.

    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 'Look up compiler implementation status for a C++26 paper' with a specific verb and resource. It distinguishes from sibling tools 'lookup_paper' and 'search' by focusing on compiler status, not general paper info or search.

    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 says 'Use it for classifying review diagnostics as bug-vs-compiler-lag, never for choosing which idiom to write' and 'the model must not gate recommendations on this', providing clear when-to-use and when-not-to-use guidance.

    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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  • Confirm that there are no obvious security issues.
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