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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a unique, clearly distinct purpose: indexing documents, searching, fetching chunk details, and statistics. No overlap or ambiguity.

    Naming Consistency4/5

    Most names follow a verb_noun pattern (get_chunk, index_documents), but 'search' and 'stats' are single words without an object, introducing minor inconsistency.

    Tool Count5/5

    4 tools is appropriate for a focused RAG server: indexing, querying with retrieval, chunk access, and monitoring. Each tool serves a necessary role.

    Completeness4/5

    Covers the core RAG workflow (index, search, retrieve). Missing a delete or clear index function, but not a major gap for typical usage.

  • Average 3.7/5 across 4 of 4 tools scored. Lowest: 3.1/5.

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

    • No community issues in the last 6 months
    • 2 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 MIT License.

  • This repository includes a README.md file.

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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

  • Behavior2/5

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

    With no annotations, the description bears full responsibility for behavioral disclosure. It states that the tool returns counts and configuration, implying a read-only operation, but does not mention side effects, permissions, rate limits, or whether data is live or cached.

    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 a single, clear sentence with no extraneous words. It front-loads the purpose ('Index statistics') and immediately lists what is included.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The description covers the return content adequately given the presence of an output schema. However, it lacks details such as the scope (global vs. per-index) or whether 'configuration' includes mutable settings.

    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 tool has no parameters, so schema coverage is 100%. The description adds value by specifying the nature of the returned data (counts and configuration), which is not evident from the empty schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states that the tool provides index statistics including document/chunk/embedding counts and configuration. It distinguishes from siblings like get_chunk (retrieve a specific chunk) and search (query) by focusing on aggregate metrics, though it does not explicitly differentiate.

    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 about when to use this tool versus alternatives (get_chunk, index_documents, search). The agent is left to infer context from the name and description alone.

    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?

    No annotations are provided, and the description is minimal, stating it fetches text and source but does not disclose any behavioral traits like auth requirements or lack of side effects.

    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?

    A single, front-loaded sentence that conveys the purpose with no redundant words.

    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?

    Despite having only one parameter and an output schema (as per context), the description is fairly complete for a simple retrieval tool, though it could explicitly mention that it returns full text and source.

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

    Parameters2/5

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

    Schema coverage is 0% (no description for chunk_id), and the description does not add any information about the parameter beyond its existence.

    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 uses a specific verb ('Fetch') and resource ('chunk'), and distinguishes from siblings like search and index_documents by specifying it retrieves an already-returned chunk.

    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 use after search results are obtained ('returned by search'), but does not explicitly state when to use vs alternatives like search or index_documents.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations provided, so description carries full burden. It does not disclose whether indexing is idempotent, overwrites existing index, or handles large files. Minimal transparency for a state-modifying tool.

    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, front-loaded with the main purpose, then lists parameters in clear format. No wasted sentences.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given an output schema exists, return values are covered. However, the description lacks behavioral context (e.g., side effects, limits) and usage prerequisites, making it only moderately complete.

    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 has 0% description coverage, but description adds meaningful details: path can be absolute or ~-expanded, glob is relative with examples. This compensates effectively.

    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 'Index text/markdown files from a directory into the local SQLite index,' using a specific verb and resource. It distinguishes from siblings like search and get_chunk which are query tools.

    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 indexing before search but does not explicitly state when to use it vs alternatives, or any preconditions like ensuring files are accessible.

    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 full burden for behavioral traits. It discloses mode options, default, and the fallback to lexical if Ollama is offline with a warning in the response. This is good transparency, though it doesn't cover authentication or rate limits.

    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 concise, using a clear docstring format with 'Args' section. The purpose is stated in the first sentence. It could be slightly more compact, but it is well-structured and efficient.

    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 presence of an output schema, the description does not need to explain return values. It covers all parameters, search modalities, and fallback behavior. It could mention sorting or result count details, but overall it is sufficiently complete for a search tool.

    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 schema has 0% description coverage, but the description thoroughly explains each parameter: query (natural-language or keywords), k (range 1-50, default 8), and mode (enum values with detailed behavior, including fallback). This adds substantial meaning 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 the tool's function: 'Search the indexed documents.' It uses a specific verb 'Search' and a distinct resource 'indexed documents', distinguishing it from siblings like get_chunk, index_documents, and stats.

    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 explains how to use the tool (query, k, mode) and mentions fallback behavior for 'hybrid' mode when Ollama is offline. However, it does not explicitly guide when to use this tool versus siblings or provide when-not-to-use scenarios.

    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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