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chaoz23

dmcheck-mcp

by chaoz23
OverviewSchemaRelated ServersScoreDiscussions
Python
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Server Quality Checklist

58%
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  • Latest release: v0.5.4

  • Disambiguation5/5

    The two tools are completely distinct: 'run' executes the analysis and returns findings, while 'rules' simply provides the rule set. There is no overlap or ambiguity between them.

    Naming Consistency4/5

    Both names are short, lowercase, and readable, but 'run' is a verb while 'rules' is a noun, so they don't follow a uniform verb_noun pattern. Despite that, the naming is simple and not chaotic.

    Tool Count4/5

    With only 2 tools, the server is slightly under the typical 3-15 range, but the domain is narrowly scoped to checking transcripts against a rule set. The count feels appropriate for the purpose, with no unnecessary extras.

    Completeness5/5

    The tool set fully covers the domain: 'rules' provides the rule definitions, and 'run' applies them to a transcript. There are no obvious missing operations for a read-only checking service.

  • Average 3.1/5 across 2 of 2 tools scored. Lowest: 2.2/5.

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

    • No community issues in the last 6 months
    • 19 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 carries full responsibility. It does not disclose any side effects, return behavior, or prerequisites. It only describes a static 'rule set' without explaining what happens when invoked.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness2/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single short but under-specified phrase. While not verbose, it fails to provide meaningful information, similar to a tautological label.

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

    Completeness1/5

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

    Given the absence of annotations, output schema, and parameters, the description must fully explain the tool's purpose and behavior. It does not, leaving the tool's functionality entirely ambiguous.

    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?

    There are zero parameters, so the schema already completely covers parameter semantics. The baseline of 4 applies; the description does not detract from this.

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

    Purpose2/5

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

    The description 'The rule set with one-line definitions' lacks a verb and does not state what action the tool performs. It reads as a noun phrase, making it unclear whether the tool retrieves, defines, or updates rules. It does not distinguish it from the sibling tool 'run'.

    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 information is provided about when to use this tool versus the sibling 'run'. There is no context on scenarios or 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?

    With no annotations, the description carries the behavioral transparency burden. It discloses output characteristics (findings list types, citation to charter rule) and a key design principle: false accusations are the worst bug, so ambiguity leads to silence. However, it does not mention side effects, permissions, or whether it reads or writes the 'ledger_path' and 'charter_path' files, which leaves some behavioral gaps.

    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 compact: three sentences, each adding unique value. It front-loads the main purpose, then lists concrete output categories, then states a behavioral guardrail. There is no fluff or repetition of the tool name.

    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 the absence of annotations, no output schema, and low parameter coverage, the description gives a solid high-level picture but misses important context like the semantics of 'ledger_path', the exact return structure/value format, and any mutating side effects. It is adequate for a competent agent but leaves clear gaps that would require external investigation or guessing.

    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 description coverage is only 25%, and the description does not compensate. It clarifies that 'transcript_path' and 'charter_path' are the transcript and charter respectively through the main sentence, and 'gm' is documented in the schema, but 'ledger_path' is never explained. The description adds no semantic detail for this parameter, making it hard for an agent to know what to provide.

    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 opens with a specific verb and resource: 'Referee a tabletop session transcript against a table charter.' It clearly states the tool's core function and distinguishes it from the sibling 'rules' tool by focusing on running the referee analysis rather than just defining rules. It also enumerates concrete outputs (conduct findings with cited violations), making the purpose unmistakable.

    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 clear context: use this tool to referee a transcript against a charter and get conduct findings. It does not explicitly mention when not to use it or compare it with the sibling 'rules' tool, which would justify a 5, but the intended usage is clearly implied by the imperative phrasing and output description.

    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.
  • Evaluate tool definition quality.

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