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KemingHe

Python Dependency Manager Companion

by KemingHe
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.1

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The tool has a single, clearly defined purpose: searching Python dependency manager documentation. No other tools exist to cause ambiguity.

    Naming Consistency5/5

    The single tool name 'search_py_dep_man_docs' follows a clear verb_noun pattern (search + py_dep_man_docs). Since there is only one tool, consistency is inherently perfect with no deviations or mixed conventions to evaluate.

    Tool Count2/5

    One tool is too few for a server named 'Python Dependency Manager Companion,' which suggests a broader scope like managing dependencies, not just searching docs. A single search tool feels thin and incomplete for the implied domain, lacking operations like installing, updating, or listing dependencies.

    Completeness2/5

    The tool surface is severely incomplete for the server's purpose. While the search tool is well-described, there are significant gaps: no tools for actual dependency management tasks (e.g., install, update, remove, list dependencies), version checking, or environment management. This will cause agent failures when trying to perform core dependency management workflows.

  • Average 3.2/5 across 1 of 1 tools scored.

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • 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 provided, the description carries the full burden but fails to disclose critical behavioral traits such as the return format (excerpts, full pages, or summaries?), whether results are实时 or cached, rate limits, or authentication requirements. Instead, it focuses heavily on response formatting instructions (progress reports, citations) that describe how the AI should present results to users rather than how the tool itself behaves.

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

    Conciseness1/5

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

    The description is severely bloated with meta-commentary ('why: user confidence'), emoji-laden headers, and extensive instructions about how the AI should format its final response to the user (progress report formats, citation placement). This content belongs in system prompts or tool-calling guidelines, not the tool description. Every sentence does not earn its place; much is redundant with the AI's general instruction set.

    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 existence of an output schema (not shown but indicated in context signals) and 100% input schema coverage, the description adequately covers the tool's scope. It identifies the authoritative source (official docs) and citation requirements. However, it lacks clarity on the output structure despite the output schema existing, relying instead on formatting instructions that assume specific return types without describing them.

    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?

    With 100% schema coverage, the baseline is 3. The description adds significant value through the 'PROVEN QUERY PATTERNS' section, providing specific example strings for the query parameter (e.g., 'project setup tutorial', 'command reference'), and explaining the semantic rationale for top_n values in different contexts (targeted precision vs. exploration). This goes beyond the schema's basic type information.

    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 opening sentence clearly states the tool 'Find[s] comprehensive answers from latest official Python dependency manager documentation,' identifying the specific resource (Python dependency manager docs) and action (find answers). The 'CORE VALUE' section further distinguishes it from general knowledge. However, the purpose is somewhat obscured by the extensive procedural instructions that follow.

    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?

    Extensive guidance is provided on when to use specific query patterns ('workflow tutorial' for learning, 'X vs Y' for comparisons, etc.) and when to adjust top_n (3-5 for specific questions, 7-10 for broad requests). While there are no sibling tools to differentiate from, the description effectively maps user intents to specific parameter configurations.

    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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