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Glama
anjor

Coinmarket

by anjor
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: get_currency_listings retrieves a list of cryptocurrencies, while get_quotes fetches specific price quotes. There is no overlap or ambiguity between these functions, making it easy for an agent to select the right tool.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun naming pattern with 'get_' prefix and snake_case formatting. This uniformity makes the tool set predictable and easy to understand at a glance.

    Tool Count2/5

    With only 2 tools, the server feels thin for a cryptocurrency data domain. Key operations like historical data, market metrics, or exchange information are missing, suggesting the surface is underdeveloped for typical agent workflows in this area.

    Completeness2/5

    The tool set is severely incomplete for cryptocurrency data. It lacks essential operations such as historical price data, market cap rankings, exchange rates, or detailed asset information. Agents will face significant gaps when trying to perform comprehensive analysis or monitoring tasks.

  • Average 2.8/5 across 2 of 2 tools scored.

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

    • 0 of 1 community issues answered or closed 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.

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    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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 the full burden of behavioral disclosure. 'Get cryptocurrency quotes' implies a read-only operation, but it doesn't specify critical traits like whether it requires authentication, rate limits, data freshness, error handling, or output format. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

    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 extremely concise at three words, with zero wasted text. It's front-loaded with the core action and resource, making it easy to parse quickly. For such a simple tool, this brevity is appropriate and efficient.

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

    Completeness2/5

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

    Given the tool's complexity (2 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'quotes' entails, how parameters work, or what the output looks like. While conciseness is high, the lack of behavioral and parameter details makes it inadequate for an agent to use the tool effectively without guessing.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters1/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has 2 parameters (slug, symbol) with 0% description coverage, meaning the schema provides no documentation on their meaning or usage. The description 'Get cryptocurrency quotes' adds no information about these parameters—it doesn't explain what 'slug' or 'symbol' represent, whether they're required, or how they affect the query. With 0% schema coverage, the description fails to compensate, leaving parameters entirely undocumented.

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

    Purpose3/5

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

    The description 'Get cryptocurrency quotes' clearly states the action (get) and resource (cryptocurrency quotes), which establishes the basic purpose. However, it doesn't specify what 'quotes' means (e.g., current prices, historical data, bid/ask spreads) or differentiate from the sibling tool 'get_currency_listings' (which might provide different data like market cap or volume). The purpose is understandable but vague in scope.

    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 the sibling 'get_currency_listings' or other alternatives. It doesn't mention prerequisites, context (e.g., real-time vs. delayed data), or exclusions. Without any usage context, the agent must infer based on tool names alone, which is insufficient for reliable selection.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • 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 of behavioral disclosure. It states what the tool does but doesn't reveal any behavioral traits such as rate limits, authentication needs, data freshness, or response format. This is a significant gap for a tool with zero annotation coverage.

    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 a single, efficient sentence with no wasted words. It's front-loaded with the core purpose, making it easy to parse and understand quickly, which is ideal for conciseness.

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

    Completeness2/5

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

    Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'latest' means (e.g., real-time, delayed), the scope of listings (e.g., all cryptocurrencies, top 100), or the return format, leaving gaps in understanding the tool's behavior and output.

    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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the input requirements. The description doesn't need to add parameter details, and it appropriately doesn't mention any, earning a baseline score of 4 for this context.

    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 action ('Get') and resource ('latest cryptocurrency listings'), providing a specific verb+resource combination. However, it doesn't differentiate from the sibling tool 'get_quotes', which might also retrieve cryptocurrency data, so it doesn't fully distinguish from alternatives.

    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 guidance is provided on when to use this tool versus the sibling 'get_quotes' or other alternatives. The description lacks context about use cases, prerequisites, or exclusions, leaving the agent without clear direction on tool selection.

    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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