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Jasonrve

bifrost-budget

by Jasonrve
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    There is only one tool, so there is no possibility of confusing it with another. Its description clearly scopes it to retrieving a Bifrost quota snapshot.

    Naming Consistency5/5

    The single tool name 'get_quota' follows a clear verb_noun convention and is descriptive. There are no other names to create inconsistency.

    Tool Count3/5

    One tool is minimal and feels thin for a server named 'bifrost-budget'. It may be acceptable as a narrow quota-check adapter, but the count is borderline.

    Completeness2/5

    The tool surface only supports reading a quota snapshot, with no create, update, delete, or list operations. This leaves significant gaps if the server is meant to support budget or quota management workflows.

  • Average 4/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 11 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

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  • 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

  • Behavior4/5

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

    With no annotations, the description carries the full burden. It discloses that the tool calls a configured endpoint, uses the caller's Authorization header when present, and falls back to explicit virtual_key/x-bf-vk/BIFROST_VIRTUAL_KEY in non-production environments. It stops short of describing precedence, error behavior, or rate limits, but the core behavioral profile is visible.

    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 one dense sentence that front-loads the core behavior and then adds only relevant auth context. Every clause earns its place, and there is no filler or repetition of the title or schema.

    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 tool with two optional parameters and an output schema, the description covers the main behavior and authentication fallback well. However, api_base_url is left completely unexplained, and the precedence between Authorization header and virtual_key is not stated. These are clear gaps for an agent trying to call the tool correctly in edge cases.

    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 0%, so the description must compensate. It does explain virtual_key as an explicit fallback credential, but it never mentions api_base_url or how it relates to the 'configured quota endpoint.' The agent is left to guess whether api_base_url overrides configuration, which is a significant semantic gap.

    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 states a specific verb and resource: 'Return the caller's Bifrost quota snapshot by calling the configured quota endpoint.' It clarifies that the result is caller-specific and not a global quota, going well beyond the title. Even without sibling tools, an agent knows exactly what operation this performs.

    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 gives clear context for how authentication works: it uses the caller's Authorization header when present, with virtual keys available 'for local and non-production fallback use.' It does not explicitly list when not to use the tool or mention alternatives, but with no siblings and a clear read-only purpose, the usage context is strong.

    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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