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vitaliiivanovspryker

Spryker Package Search Tool

by vitaliiivanovspryker
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation4/5

    The three tools have distinct primary targets: documentation paths, package code, and package repository search. However, 'search_spryker_package_code' and 'search_spryker_packages' could be slightly confusing as both involve GitHub repositories, though their descriptions clarify one searches code within repositories and the other searches the package repository itself.

    Naming Consistency5/5

    All tool names follow a consistent snake_case pattern with the verb 'search' followed by a specific noun phrase (spryker_documentation_path, spryker_package_code, spryker_packages). This uniformity makes the tool set predictable and easy to understand.

    Tool Count3/5

    With only 3 tools, the server feels thin for a 'Package Search Tool' that might imply broader functionality like installing or managing packages. While the tools cover key search aspects, the limited count may restrict agent workflows, especially if additional operations like package installation or version checking are needed.

    Completeness3/5

    The tools provide search capabilities across documentation, code, and packages, which aligns with the server's name. However, there are notable gaps: no tools for actions like installing packages, checking package versions, or managing dependencies, which are common in package management contexts. This limits the server to read-only search operations.

  • Average 2.9/5 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

  • 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.

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

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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. It states the tool searches documentation path URLs but doesn't describe what the search returns (e.g., list of URLs, relevance scores, pagination), how results are ranked, or any limitations (e.g., rate limits, authentication needs). This leaves critical behavioral aspects unspecified.

    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 that directly states the tool's function without unnecessary words. It's front-loaded with the core purpose and appropriately sized for a simple search tool, earning full marks 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 the tool returns (e.g., search results format), behavioral traits like search scope or limitations, or how it differs from sibling tools. For a search tool with no structured output documentation, this leaves significant gaps for an AI agent.

    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?

    The input schema has 100% description coverage, with the 'query' parameter documented as 'The natural language query to search Spryker documentation path url'. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for high schema coverage without compensating value.

    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: 'search Spryker documentation path urls by query'. It specifies the verb (search), resource (Spryker documentation path urls), and mechanism (by query). However, it doesn't explicitly differentiate from sibling tools like 'search_spryker_package_code' or 'search_spryker_packages', which likely search different resources.

    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. It doesn't mention sibling tools, prerequisites, or specific contexts where this search is appropriate. The agent must infer usage based on the name alone, which is insufficient for optimal tool 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 full burden for behavioral disclosure but offers minimal information. It doesn't mention whether this is a read-only operation, what authentication might be required, rate limits, pagination behavior, or what format results are returned in. 'Search' implies querying, but no operational details are provided.

    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 that directly states the tool's purpose with zero wasted words. It's appropriately sized for a search tool and front-loads the essential information.

    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?

    For a search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what kind of results to expect (code snippets, file paths, repositories), how results are structured, or any limitations. The agent would need to guess about the tool's behavior and output format.

    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 schema already fully documents both parameters. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain query syntax, result ranking, or provide examples. Baseline 3 is appropriate when schema does the heavy lifting.

    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 ('search code') and target ('in Spryker GitHub repositories'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'search_spryker_packages' or 'search_spryker_documentation_path', which likely search different content types rather than code specifically.

    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. It doesn't mention sibling tools or clarify that this searches code specifically (as opposed to documentation or package metadata), leaving the agent to infer usage context from the tool name alone.

    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 full burden for behavioral disclosure but offers minimal information. It mentions searching Github but doesn't describe what type of results to expect, whether there are rate limits, authentication requirements, or how results are structured. This is inadequate for a search 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.

    Conciseness4/5

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

    The description is a single, efficient sentence that gets straight to the point without unnecessary words. However, it could be slightly more informative while maintaining 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?

    For a search tool with no annotations and no output schema, the description is insufficient. It doesn't explain what constitutes a 'package' in this context, what information is returned, or how results are presented. The agent would need to guess about the tool's behavior and output format.

    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?

    The description doesn't add any parameter-specific information beyond what's already in the schema (which has 100% coverage). It doesn't explain how the query should be formulated or what the organisations array actually filters. With complete schema documentation, the baseline score of 3 is appropriate.

    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 as searching the Spryker package repository in Github, which is a specific verb+resource combination. However, it doesn't explicitly distinguish this from its sibling tools (search_spryker_documentation_path and search_spryker_package_code), which likely search different content types within the same ecosystem.

    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 its siblings or alternatives. It doesn't mention any prerequisites, constraints, or typical use cases, leaving the agent to infer usage from the tool name alone.

    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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