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Server Quality Checklist

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  • Latest release: v1.2.0

  • Disambiguation5/5

    Each tool has a distinct, non-overlapping purpose: grammar compilation, content ejection, validation, and writing. No ambiguity.

    Naming Consistency5/5

    All tools follow a consistent 'octave_verb' pattern with clear action nouns (compile_grammar, eject, validate, write).

    Tool Count5/5

    4 tools is well-scoped for a domain-specific server covering compilation, validation, output, and file manipulation.

    Completeness5/5

    The tool set covers the core lifecycle of OCTAVE content: compile, validate, output (eject), and write (create/modify/normalize). No obvious gaps.

  • Average 4.1/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 14 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under Apache 2.0.

  • 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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    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.

  • Add related servers to improve discoverability.

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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?

    No annotations provided, so description carries full burden. It discloses validation and optional repairs, focus on specific constraints, but does not detail side effects, permissions, or whether modifications are persisted. Some behavioral context is present via parameters like fix and profile.

    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 sentences concisely convey purpose, behavior, and focus areas without unnecessary detail. Every sentence adds value.

    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 9 parameters and no output schema, the description effectively summarizes tool behavior (validation, repair, canonical form) and key features (diff, grammar hints). It covers the main use cases but could elaborate on return value structure and error handling.

    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 description coverage is 100%, so baseline is 3. The description adds value by linking parameters to purpose (e.g., 'fix' for repairs, 'profile' for strictness) and highlighting focus on I3/I5 constraints, providing meaningful context beyond schema definitions.

    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 performs schema checking and repair suggestions for OCTAVE content, specifies it validates against schema and returns canonical form, and identifies focus on I3 and I5 constraints. This distinguishes it from siblings like compile_grammar and eject.

    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 on when to use this tool vs alternatives. The description does not mention prerequisites, scenarios, or when not to use it. Siblings are not referenced for differentiation.

    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 carries full burden. It mentions input and output format options but does not disclose behavioral traits like side effects, error handling, or performance implications. The information is adequate but not enhanced beyond schema details.

    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, covering purpose, supported outputs, and input methods without any wasted words. It is well-structured and front-loaded with the core action.

    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?

    For a compile tool with three parameters and no output schema, the description covers essential usage. It lacks a description of the return value (the compiled grammar), which is a minor gap given the tool's output-oriented nature.

    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%, so the schema already documents all parameters. The description adds context about the format parameter (associating GBNF with llama.cpp and JSON Schema with vLLM) but does not significantly enhance understanding beyond what the schema provides.

    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 compiles OCTAVE schemas/contracts into constraint grammars, distinguishing it from sibling tools (octave_eject, octave_validate, octave_write) which serve different purposes.

    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 specifies the supported output formats (GBNF, JSON Schema) and input options (builtin schema vs inline content), providing clear context for when to use the tool. However, it does not explicitly state when not to use it or mention 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?

    Despite no annotations, description discloses key behavioral traits: supports multiple projection modes, output formats, template generation, and sections parameter with flexible matching and silent omission. Does not cover permissions or side effects but provides substantial behavioral context beyond basic.

    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 effective sentences: first defines primary action, second summarizes modes, template generation, and output formats. No wasted words, information is front-loaded and accessible.

    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 5 parameters, no output schema, and no annotations, description covers all parameters and their behavior (modes, formats, sections, template generation). It lacks details on return values or error cases, but is sufficient for a conversion tool. Missing only minor context.

    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%, baseline 3. Description adds significant value by explaining modes (e.g., 'executive: STATUS,RISKS,DECISIONS'), format implications (gbnf exports llama.cpp GBNF grammar), and sections parameter behavior (flexible matching, silent omission). This enriches the schema 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?

    Description clearly states the tool ejects OCTAVE content with projection modes, listing specific modes and output formats. It distinguishes from siblings (compile_grammar, validate, write) by focusing on projection and conversion.

    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?

    No explicit guidance on when to use this tool versus siblings. However, the description hints at template generation when content is null, providing some context. Lack of usage alternatives or exclusions reduces clarity.

    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?

    No annotations are provided, so the description carries the full burden. It discloses behavioral traits such as handling creation and modification, detailed op descriptors for changes, error codes, format_style options with deprecation, dry_run behavior, lenient parsing, and parse_error_policy. This is highly transparent.

    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 long but well-structured, starting with a summary and then detailing modes, deprecation, and options. Every sentence adds value, though the op descriptor details could be slightly more concise. Still efficient overall.

    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 (13 params, nested objects, no output schema), the description is very complete. It covers use cases, op structure, error handling, formatting, and deprecation. It does not explain return values, but that is acceptable without an output schema.

    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%, baseline is 3. The description adds significant extra context beyond schema descriptions, explaining the relationship between content and changes, op descriptors, format_style future changes, and the effect of lenient and parse_error_policy. This enhances understanding beyond the 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 it is the unified entry point for writing OCTAVE files, handling both creation and modification. It explicitly distinguishes itself by noting it replaces octave_create and octave_amend, and describes different usage modes (content, changes, normalize).

    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 content vs changes vs omit both, and that it replaces older tools. However, it does not explicitly contrast with sibling tools like octave_validate or octave_compile_grammar, leaving some ambiguity about when not to use this tool.

    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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