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aradar46

reuse-before-generate

by aradar46
OverviewSchemaRelated ServersScoreDiscussions
TypeScript

Server Quality Checklist

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

  • Latest release: v0.2.4

  • Disambiguation1/5

    Both tools have nearly identical descriptions and appear to perform the same search across multiple sources. An agent cannot distinguish when to use one over the other.

    Naming Consistency2/5

    The names use different verbs ('check' vs 'reuse') and different noun forms ('building' vs 'generate'), with no consistent pattern. The naming is confusing and inconsistent.

    Tool Count2/5

    With only 2 tools that are essentially redundant, the number feels too low for the ambitious scope described (searching GitHub, npm, GitLab, Show HN, etc.). A single tool would suffice.

    Completeness1/5

    The server claims to handle search for reusable projects, but having two identical tools leaves no clear separation of concerns. Obvious gaps like dedicated filtering or fetching specific details are missing.

  • Average 4.5/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 88 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • 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.

  • This repository includes a glama.json configuration file.

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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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

  • Behavior4/5

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

    No annotations are provided, so the description fully conveys behavioral traits. It lists sources searched, types of results returned, and warns about generic keywords. It also clarifies agent responsibility for relevance judgment. This is detailed and honest.

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

    Conciseness3/5

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

    The description is long, especially the keywords advice, but it is front-loaded with the core purpose. Each sentence is informative, but some repetition and length could be trimmed without losing meaning. Adequately structured.

    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?

    The description covers the tool's purpose, search sources, result types, and agent responsibilities. However, it does not detail the return format (only mentions 'complete retrieval evidence'), and the tool is complex with a sibling tool that could have been contrasted more explicitly. Mostly complete but leaves some questions.

    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 coverage is 100%, but the description adds significant value: for 'keywords', it gives extensive guidance on selecting effective terms with concrete examples. 'queries' is explained as optional and how to use it. 'description' is clarified as a plain-language requirement. This goes well beyond the schema.

    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's purpose: 'Run this BEFORE scaffolding a new project or a substantial new module.' It specifies the sources searched and the outputs returned. The sibling tool 'reuse_before_generate' contrasts, making the distinct purpose clear.

    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 explicitly says when to use the tool (before scaffolding) and provides detailed instructions on how to use it, including agent responsibilities and keyword selection. However, it does not explicitly state when not to use it or mention alternatives directly.

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

  • Behavior5/5

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

    Despite no annotations, the description thoroughly discloses the tool's behavior: it searches multiple platforms, returns both reusable projects and competing products along with retrieval evidence, and requires the agent to follow scoring instructions. It does not explicitly state read-only nature, but the description implies it is a search/retrieval tool with no side effects, which is sufficient for transparency.

    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 well-structured with key information front-loaded. It is somewhat long but every sentence adds value, explaining the tool's function, sources, outputs, and usage responsibilities. Minor redundancy could be trimmed, but overall it is efficient for the complexity.

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

    Completeness5/5

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

    Given the tool has 3 parameters (2 required), nested objects, and no output schema, the description is highly complete. It covers what the tool does, what sources it searches, what it returns, and the agent's responsibilities. The agent can confidently use this tool without ambiguity.

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

    Parameters5/5

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

    Schema coverage is 100%, but the description adds substantial meaning beyond the schema. The keywords parameter has a detailed explanation with examples of how to formulate precise terms and avoid noise. The queries object's fields are explained even though optional. This significantly aids correct parameter usage.

    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's purpose: to be run before scaffolding a new project or module, and it searches multiple repositories for reuse. It distinguishes itself by listing the specific sources and the output including both reusable projects and competing products. The sibling 'check_before_building' implies different usage, so this tool's scope is well defined.

    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?

    The description explicitly says 'Run this BEFORE scaffolding a new project or a substantial new module.' It also provides guidance on when not to rely on the tool for keyword extraction, warning against generic terms. It sets expectations for the agent's responsibility in relevance judgment and following scoring instructions, making usage context very clear.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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