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weiseer
by weiseer

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.1

  • Disambiguation5/5

    Each tool has a distinct purpose: listing with filters, personalized matching, single bounty detail, and aggregate stats. No overlap in functionality.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case, making them predictable and easy to parse.

    Tool Count5/5

    Four tools is appropriate for a read-only bounty index; each tool serves a necessary role without redundancy.

    Completeness4/5

    Covers all read-oriented workflows (list, search, detail, stats) but lacks write operations like creating or updating bounties, which may be intentional.

  • Average 3.8/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 3 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.

  • 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.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

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

    Then . Browse examples.

  • Add related servers to improve discoverability.

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.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 bears full responsibility. It reveals the key format but does not mention behavioral aspects such as whether the tool is read-only, includes any side effects, rate limits, or what 'full record' entails beyond the key. Minimal transparency.

    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?

    A single, concise sentence that front-loads the essential information (purpose and key format). No redundant words or phrases.

    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 adequately covers the key format and scope (single bounty record), but given no output schema, it would benefit from mentioning the structure of the returned 'full record' or any additional context. Acceptable for a simple retrieval 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 single parameter 'key' has no description in the schema (0% coverage). The description adds the crucial format 'owner/repo#issue_num', which provides concrete guidance beyond the schema's bare type string.

    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 explicitly states it returns a full record for a single bounty by key, with the key format 'owner/repo#issue_num'. This clearly distinguishes it from sibling tools like list_bounties (list multiple) and get_stats (statistics).

    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 indicates when to use this tool (to get a single bounty record), but does not explicitly state when not to use it or compare to alternatives like list_bounties for multiple records or find_matching for searching. The sibling names provide implicit context.

    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?

    No annotations are provided, so the description must disclose all behavioral traits. It only says 'List', implying read-only, but omits details about pagination, sorting, rate limits, auth requirements, or response format.

    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 short sentences: the first defines the tool's core functionality, the second enumerates filters. No wasted words.

    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?

    For a list-with-parameters tool, the description covers purpose and main filters. However, it lacks details on output format, pagination, sorting, or error handling, which would improve completeness given no output schema.

    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 only 33% description coverage (language and min_dollars). The description compensates by naming the key filters: language, $ floor, bug-fix only, exclude assigned/PR. It adds meaning beyond the bare schema for most parameters.

    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 verb 'List', the resource 'live verified-escrow GitHub coding bounties', and the scope (filterable). It distinguishes from siblings like 'find_matching', 'get_bounty', and 'get_stats'.

    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 lists the available filters but does not explicitly state when to use this tool versus siblings. It implies browsing all bounties, but no guidance on exclusion or alternatives.

    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?

    No annotations exist, so description must convey all behavioral traits. It only describes output (aggregate stats) without mentioning read-only nature, side effects, or auth requirements.

    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?

    Single sentence with no waste, front-loading purpose and details.

    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-parameter, no-output-schema tool, description covers key output aspects. Could mention data freshness or caching, but overall complete.

    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 (0), so baseline is 4. Description adds meaningful context about output structure (by language, bug-fix-vs-feature), which suffices.

    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?

    Description clearly states the tool aggregates stats on the active bounty pool, specifying breakdowns by language and bug-fix-vs-feature, and total $. This distinguishes it from list_bounties (individual listing) and get_bounty (single bounty).

    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?

    Usage is implied through the description of aggregated stats, but no explicit guidance on when to use vs. alternatives like list_bounties or find_matching is provided.

    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?

    With no annotations, the description provides useful behavior: sorting by $ descending and excluding assigned/active-PR bounties. It could mention more (e.g., result limit, read-only nature), but the given info is sufficient for basic understanding.

    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 effective sentences front-load the purpose and then add behavioral details. Every word adds value; no fluff.

    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 core purpose and key behaviors, but lacks details on output format, result limits, and the meaning of parameters like fresh_only. Given no output schema and 4 parameters, it is slightly incomplete.

    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?

    Schema description coverage is only 50%, and the description adds no extra meaning beyond the schema. It indirectly mentions skills and min_dollars but does not explain them further, nor does it address fresh_only or max_attempts.

    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 action (find), resource (bounties), criteria (skill set and dollar floor), sorting (desc by $), and exclusions. It distinguishes itself from siblings like list_bounties and get_bounty as a filtered search tool.

    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 purpose is clear enough to infer when to use it: when filtering bounties by skills and minimum dollars. However, it does not explicitly state when not to use it or mention alternatives, leaving some guidance to context.

    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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