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SkinnyMonk

EAG MCP Demo

by SkinnyMonk
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Python
Local

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The three tools cover completely different areas: local note CRUD (notes_file), visual dashboard (show_dashboard), and external web search (web_search). There is no overlap or ambiguity.

    Naming Consistency4/5

    All tool names use snake_case and are descriptive, though the pattern varies slightly (notes_file is a noun, show_dashboard is verb+noun, web_search is noun+verb). Still consistent and readable.

    Tool Count4/5

    With only 3 tools, the set is small but well-suited for a demo server. Each tool has a clear purpose and none feel redundant. A few more tools might be expected for a full-featured service, but for a demo it's appropriate.

    Completeness5/5

    The notes_file tool provides full CRUD and listing, show_dashboard adds visualization, and web_search covers external search. There are no obvious gaps for the stated demo purpose.

  • Average 4.1/5 across 3 of 3 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

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  • 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

  • Behavior2/5

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

    No annotations are provided, so the description must fully disclose behavioral traits. It lists actions but does not mention potential destructive effects (update/delete), error handling, atomicity, or file locking. The transparency is minimal beyond basic CRUD semantics.

    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 a single introductory line followed by a list of actions and examples. Every sentence serves a purpose, and the structure is front-loaded with the core purpose.

    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 tool's simplicity (3 parameters, output schema present), the description covers the action parameter well. However, it does not clarify behavior for empty 'key' or 'content' defaults, nor potential side effects. Still, it is largely complete for a basic CRUD tool.

    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 schema has 0% description coverage, but the description adds meaningful context by providing examples for each action, clarifying how 'key' and 'content' are used per action. This adds value beyond the schema definition.

    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 'CRUD on local notes.json' and enumerates each action with examples, making the tool's purpose unmistakable. It is distinct from siblings 'show_dashboard' and 'web_search'.

    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 implicitly conveys when to use the tool (to manage notes), but does not provide explicit guidance on when not to use it or discuss alternatives. Given the unrelated siblings, no confusion arises, but explicit exclusions are absent.

    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?

    Without annotations, the description discloses the return format (plain-text block with abstract, source URL, topics) and behavior for no results. However, it omits API limitations, rate limits, and whether the operation is read-only.

    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 concise sentences, front-loaded with purpose. Every sentence adds value with no redundancy.

    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?

    The tool has an output schema (not shown), reducing the need to describe return values. The description covers usage context and edge cases adequately for a simple single-parameter search tool.

    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?

    The schema has one parameter 'query' with no description (0% coverage). The description does not elaborate on query semantics beyond implying a search term, failing to add meaningful guidance.

    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 searches the web via DuckDuckGo API, specifying the output format and appropriate use cases (well-known entities). This differentiates it from sibling tools like notes_file or show_dashboard.

    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 a clear context for when to use the tool ('Best for well-known entities'), but does not explicitly exclude or compare to alternatives. Given unrelated siblings, this is sufficient.

    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, the description discloses that it reads notes.json fresh on each call, informing the agent about data source and potential performance. Missing edge cases like missing notes.json, but sufficient for a simple 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?

    Two sentences with no redundancy. Front-loaded purpose, then usage and behavior. 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?

    For a zero-param, no-output-schema tool, the description covers main action, usage context, and a behavioral trait. Misses what happens when no notes exist, but overall adequate.

    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?

    No parameters exist, so schema coverage is 100%. The description provides no extra param info, but baseline for zero-param tools is 4.

    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 renders saved notes as a Prefab card grid. It uses a specific verb-resource combination and distinguishes itself from siblings (notes_file for saving, web_search unrelated).

    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?

    Explicitly instructs to call AFTER saving via notes_file, establishing a clear ordering and naming the prerequisite sibling. This guides the agent on when to invoke the 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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