quota-dashboard-mcp
Server Quality Checklist
Latest release: v1.0.1
- Disambiguation5/5
Each tool serves a distinct purpose: health check, per-provider details, and unified summary. No overlap in functionality.
Naming Consistency5/5All tools follow snake_case and a consistent verb_noun pattern (check_quota_health, get_provider_quota, get_quota_summary).
Tool Count5/5Three tools is appropriate for a quota dashboard, covering health check, per-provider detail, and summary without unnecessary bloat.
Completeness4/5Provides essential read operations for quota monitoring. Minor gap: no tool to update thresholds or configure providers, but the domain appears read-only by design.
Average 3.8/5 across 3 of 3 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 8 commits in the last 12 weeks
- Last stable release on
- 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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as side effects, authentication requirements, rate limits, or idempotency. It only states the function. The schema descriptions for parameters offer some context, but the tool description itself lacks transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence that efficiently communicates the core purpose and supported providers. It is front-loaded and concise, though it could benefit from a bit more detail about the return structure without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should at least hint at the return format or structure, but it does not. The tool is simple with few parameters, and the schema provides good parameter detail. However, the lack of return information and behavioral context makes it only minimally complete for complex usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have schema descriptions covering 100% of their semantics. The tool description does not add any additional meaning beyond what is in the schema; the supported providers list is redundant. Baseline score of 3 is appropriate due to high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool returns detailed quota information for a single provider and lists supported providers, which clearly indicates the tool's purpose and scope. It distinguishes from sibling tools (get_quota_summary, check_quota_health) by focusing on per-provider detail, but the verb 'returns' is generic and could be more specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for getting detailed quota of a single provider, but it does not explicitly mention when to use this tool versus alternatives like get_quota_summary or check_quota_health. No when-not-to-use guidance or explicit alternative references are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that providers without a configured token report a config error instead of failing the whole call, which is useful behavioral context. However, it does not describe the return structure or other edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first sentence immediately states the purpose, and the second adds a key behavioral detail. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of parameters and output schema, the description adequately covers the tool's behavior. The error handling detail is valuable. It could elaborate on the return format, but overall it is sufficient for an agent to understand and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the description naturally cannot add parameter details. Per the rules, baseline 4 applies, and the description adds no unnecessary confusion.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a unified quota summary across all configured providers, listing examples (Claude Code Max, Kimi, Z.ai). This differentiates it from siblings like get_provider_quota, which targets a single provider.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when an aggregated view across providers is needed, but does not explicitly state when not to use it or compare with alternatives like check_quota_health or get_provider_quota.
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 bears full burden. It transparently describes that it flags providers based on threshold and token validity, and returns a health report. However, it does not confirm read-only behavior or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences concisely convey the tool's purpose and output. The key action is front-loaded in the first sentence, making it efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description adequately explains inputs and outcomes. It covers what the tool checks and what it returns, leaving no obvious gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'threshold' is fully covered by the schema (100%). The description adds context by specifying default 80% and that it triggers warnings, adding value beyond the schema's basic description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool flags providers exceeding a threshold or with token issues and returns a health report. It distinguishes from siblings by focusing on health checking rather than simple quota retrieval or summary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for health checking but does not explicitly state when to use this tool versus alternatives like get_provider_quota or get_quota_summary. No when-not-to-use guidance is provided.
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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