CountdownMCP
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
The two tools have clearly distinct purposes: one retrieves usage information, the other provides advisory ranking for work. There is no overlap or ambiguity between them.
Naming Consistency5/5Both tools follow the same verb_noun pattern with the 'countdown_' prefix: countdown_get_usage and countdown_advise_work. The naming is consistent and predictable.
Tool Count3/5With only 2 tools, the server feels thin, but it is appropriately scoped for its narrow purpose of usage monitoring and work advising. It falls into the borderline category.
Completeness4/5The tool surface covers the core needs: reading usage and advising on work. Minor gaps exist (e.g., no explicit plan management or limit adjustment), but the described advisory scope is adequately served.
Average 4.3/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 12 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
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.
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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?
Annotations already mark it as read-only, idempotent, and non-destructive. The description adds behavioral context: 'Advisory only; it does not store tasks or override dependencies', clarifying it never mutates state. It doesn't cover errors, but output schema is present.
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 totaling 28 words, front-loaded with the primary purpose and containing no filler or redundant information.
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?
For a simple advisory ranking tool, the description covers purpose, input type, and side-effect profile, and the output schema handles return values. However, it leaves ambiguous how the 'current Codex usage window' is obtained (given sibling countdown_get_usage) and does not clarify the role of currentTaskId, so it is not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%; the description does not explain any parameters. The optional currentTaskId is completely unmentioned, and while the tasks schema has self-explanatory field names, the description only hints at the structure via 'TodoMCP WorkCandidate v1 tasks', leaving the agent without additive semantic guidance.
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 states a specific verb ('rank') and resource ('ready work') against the 'current Codex usage window', and clarifies it applies to 'TodoMCP WorkCandidate v1 tasks'. It clearly differentiates from the sibling tool by noting its advisory nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says to use with 'TodoMCP WorkCandidate v1 tasks' and provides context ('rank ready work against the current Codex usage window'). It lacks explicit 'when not to use' or reference to the sibling countdown_get_usage as an alternative, but the advisory-only disclaimer implies no persistence.
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?
Annotations already declare this as safe and idempotent. The description adds meaningful behavioral context by specifying the exact data it returns (plan, usage, reset window, credits, limit state), which goes beyond the generic annotations.
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 a single, front-loaded sentence beginning with the practical usage context. Every clause adds value by naming the accessible information, with no filler or redundant content.
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 zero-parameter, read-only tool with an output schema and annotations, the description is complete. It covers why, when, and what to expect, making it fully sufficient for an agent to select and invoke correctly.
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 tool has zero parameters, and the description correctly focuses on the tool's function rather than parameter details. Since there are no inputs to explain, the description fully satisfies parameter semantics without additional explanation.
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 uses a specific verb ('read') and clearly identifies the resource and scope: current Codex plan, remaining usage, reset window, credits, and limit state. It also provides the timing for use, which further distinguishes it from the sibling tool countdown_advise_work.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool: 'before large or multi-stage work.' It gives clear context, though it does not mention when not to use it or compare with countdown_advise_work as an alternative.
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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