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Andreymi

tractatus_thinking

by Andreymi

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v4.0.10

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap. The tool's purpose is singular, and its description, while broad, does not create ambiguity between different tools.

    Naming Consistency5/5

    A single tool name 'tractatus_thinking' follows a clear snake_case convention and is self-consistent. There are no other tool names to conflict with, so naming consistency is perfect.

    Tool Count1/5

    The server exposes only one tool, yet the description references numerous distinct operations (start, add, analyze, export, navigate, revise, undo, move). This is an extreme mismatch between the claimed functionality and the actual API surface, making the tool count severely inadequate.

    Completeness1/5

    The tool's description promises a rich set of capabilities for logical analysis and restructuring, but these are all bundled into a single tool with no separate callable functions. Agents cannot directly invoke specific operations, and the surface is severely incomplete relative to the described domain.

  • Average 4/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 0 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.

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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 behavioral disclosure. It goes beyond the schema by explaining capabilities (restructure, separate bundled concepts, reveal dependencies), limitations (some propositions are atomic), and operational nuances (multiplicative relationships, progressive structure generation). However, it does not disclose return formats, session management details, or error behaviors, which would be needed for full transparency.

    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 excessively verbose and repetitive. Phrases like 'structural clarity', 'logical architecture', and 'multiplicative relationships' are repeated across multiple bullet lists. While it is well-structured with headers and bullets, many sentences do not earn their place, making it longer than necessary.

    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 tool is complex (23 parameters, no output schema, no annotations), and the description provides substantial strategic context for when and why to use it. However, it lacks operational specificity: it does not explain what each operation returns, how sessions are managed, or how to chain operations in practice. This leaves notable gaps in the full usage picture.

    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 high-level operational context (lists operations like start, add, export) but does not provide parameter-specific meaning beyond what the schema already contains. It neither detracts nor significantly enhances parameter understanding.

    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 purpose: 'logical concept analysis and structured thinking' and 'break down complex ideas into their fundamental components'. It uses specific verbs like analyze and decompose, and identifies the resource as logical concepts. Although there are no siblings, it sufficiently distinguishes itself from generic thinking tools.

    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?

    The description provides explicit when-to-use guidance, including a dedicated 'When to use this tool' section and a 'Strategic sequencing' section that explains when to use this tool versus sequential thinking. It even names the alternative ('sequential thinking') and describes the complementary relationship, making usage boundaries 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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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