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gralliry

opencode-balance-mcp

by gralliry
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.2

  • Disambiguation5/5

    The two tools query distinct resources: one for Go subscription quota and one for Zen prepaid balance. Their descriptions clearly differentiate the data returned (usage percentages vs. balance in USD units), making confusion unlikely.

    Naming Consistency5/5

    Both tool names follow the exact same pattern: 'query_' prefix followed by the resource type ('go_usage' and 'zen_balance'). This is fully consistent and predictable.

    Tool Count4/5

    With only two tools, the surface is minimal, but the server's scope is narrowly defined as querying two distinct balance types. The count feels appropriate given the focused purpose, though slightly thin if broadenability was expected.

    Completeness4/5

    The server covers the two core balance query operations for its domain. Missing a combined query or historical data are minor gaps that agents can work around, but the essential read operations are present.

  • Average 4.4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 7 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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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

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden. It adds value by disclosing that credentials are pre-configured via CLI args or env vars, which prevents unnecessary auth handling. However, it does not mention potential error conditions, whether the action is read-only (though implied by 'query'), or any rate limits. It neither contradicts nor fully discloses behavior.

    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 sentences with no wasted words. The first sentence states purpose and outputs; the second clarifies argument and credential requirements. Information is front-loaded and every word serves a purpose.

    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 query tool with no output schema, the description covers the essential details: what it returns and that no arguments are needed. It does not specify the exact format of the reset countdown (e.g., seconds, minutes), which could cause minor ambiguity, but overall the tool is simple enough that the description is nearly 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?

    The tool has zero parameters, so baseline is 4. The description reinforces this by explicitly stating 'No arguments needed,' which adds clarity beyond the empty schema. Since there are no parameters to document, this is fully adequate.

    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 queries OpenCode Go subscription quota and enumerates specific outputs (usage percent, estimated USD spent, reset countdown). It uses a specific verb 'query' and resource 'Go subscription quota,' making it distinguishable from the sibling tool query_zen_balance.

    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?

    It explicitly states 'No arguments needed' and explains how credentials are provided, which tells the agent it doesn't need to pass authentication. It does not explicitly name the sibling or contrast usage, but the purpose is clear enough that the agent can infer when to use it. Lacks an explicit 'when not to use' but provides sufficient context.

    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 carries the full burden and discloses useful behavioral details: balance units in 1e-8 USD, negative values meaning credit, formatted USD output, and auto-reload settings. It also clarifies credential sourcing, which is important operational behavior.

    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 efficiently written sentences convey the purpose, output, required arguments, and credential mechanism with no filler. Every clause earns its place and the core subject is front-loaded.

    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?

    For a zero-parameter read-only query tool with no output schema, the description is complete: it names the resource, details the returned data, explains the unit semantics, states no arguments are needed, and tells where credentials come from. Nothing necessary for correct invocation is missing.

    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?

    There are zero parameters and schema coverage is 100%, so the baseline is 4. The description reinforces that no arguments are needed and goes further by explaining how authentication is already handled, which adds meaning beyond the empty 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 names a specific verb (Query), a specific resource (OpenCode Zen prepaid balance), and the scope (pay-as-you-go balance). It lists the exact data returned, which distinguishes it from the sibling query_go_usage without needing to compare schemas.

    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 clearly states that no arguments are needed and explains how credentials are supplied, which is essential contextual guidance for invoking the tool. It does not explicitly name the sibling as an alternative, but the resource and data scope make the intended use 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 the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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