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Talismanic

URL Shortener MCP

by Talismanic
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'shorten' has a single, clear purpose that cannot be confused with any other tool in this set.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'shorten' follows a clear verb-based pattern appropriate for its function, with no other tools to compare against for inconsistency.

    Tool Count2/5

    A single tool for a URL shortener server is too few for the apparent scope, as it only covers shortening URLs without any complementary operations like retrieving, updating, deleting, or listing shortened URLs. This minimal set limits functionality and may cause agent failures in broader workflows.

    Completeness2/5

    The tool surface is severely incomplete for a URL shortener domain. While 'shorten' allows creation, there are no tools for retrieving, updating, deleting, or managing shortened URLs (e.g., get_url, list_urls, delete_url), creating significant gaps that will hinder agent performance in typical use cases.

  • Average 3.2/5 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 Apache 2.0.

  • 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?

    No annotations are provided, so the description carries full burden. It states this is a URL shortening operation but doesn't disclose behavioral traits like whether this requires authentication, rate limits, what happens with invalid URLs, or what the output format looks like. The mention of 'cleanuri API' adds minimal context but lacks operational details.

    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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second provides parameter documentation. There's zero wasted text, and the structure is clear with a brief introduction followed by args.

    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 tool's low complexity (single parameter, no annotations, no output schema), the description is minimally adequate. It covers the basic purpose and parameter, but lacks important context like output format, error handling, or API constraints. Without an output schema, the description should ideally hint at what gets returned.

    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 description coverage is 0%, so the description must compensate. It explicitly documents the single parameter 'original_url' with a clear explanation ('The URL to shorten'), which adds meaningful semantics beyond the bare schema. However, it doesn't provide format examples or validation rules (e.g., must be a valid HTTP URL).

    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 the tool's purpose with a specific verb ('shorten') and resource ('URL'), and identifies the external service ('cleanuri API'). It doesn't need to distinguish from siblings since there are none. However, it could be slightly more specific about what type of shortening service cleanuri provides.

    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?

    The description provides no guidance on when to use this tool versus alternatives (though there are no sibling tools). It doesn't mention prerequisites, rate limits, or any constraints. The only usage context is the API name, which is insufficient for proper guidance.

    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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  • Evaluate tool definition quality.

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