mcp-trial
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
get_repo and recent_commits are clearly distinct: one fetches repository metadata, the other lists recent commit messages. There is no ambiguity between them.
Naming Consistency3/5Both names use snake_case but follow different patterns: get_repo uses a verb_noun construction while recent_commits is an adjective_noun phrase. The inconsistency is minor but noticeable.
Tool Count3/5With only 2 tools, the server feels thin for a GitHub-related purpose. It is slightly under the typical well-scoped range, though acceptable for a narrow read-only trial.
Completeness2/5The tools only cover repository metadata and recent commits. Obvious gaps like branches, issues, pull requests, and other common repository operations are missing, which would significantly hinder agents needing broader repo access.
Average 3.5/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 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
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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?
With no annotations, the description carries the burden of behavioral disclosure. It usefully clarifies that only the default branch is inspected and that only messages are returned, but it does not mention ordering beyond 'most recent,' pagination, authentication needs, or rate-limit behavior. This is adequate but not richly transparent.
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?
One short, front-loaded sentence that states the core behavior without filler or redundancy. Every word contributes meaning, making it easy for an agent to parse quickly.
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?
For a simple read-only listing tool, the description covers the main action and branch scope, and an output schema exists to describe return values. However, it leaves the limit parameter's semantics completely unaddressed and assumes the agent infers the standard owner/repo relationship, so the context is minimally sufficient rather than complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description does not explain any of the three parameters (owner, repo, limit). It adds no meaning beyond the raw property names and default value already present in the input schema, so it fails to compensate for the low schema coverage.
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 ('List') and a specific resource ('recent commit messages'), clearly scoping them to 'a repository's default branch.' This distinguishes it from the sibling get_repo, which is about repository metadata rather than commit messages.
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 recent commit messages are needed, but it provides no explicit guidance about when not to use it or how it compares to the sibling get_repo. It does not include exclusions or alternative recommendations, so usage guidance is only implicit.
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?
With no annotations, the description carries the behavioral transparency burden. 'Get summary info' conveys a read-only operation and names the returned fields, but it does not mention authentication needs, rate limits, error behavior, or edge cases like repositories without a last push.
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?
A single, tightly structured sentence front-loads the action and resource, then enumerates concrete outputs. There is no filler, repetition, or unnecessary detail.
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 two-parameter read-only metadata tool, the description is largely complete: it states the operation, target resource, and output fields. A note about when to prefer recent_commits would improve it, but that gap is already reflected in the usage guidelines score.
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?
The schema has no parameter descriptions and the description does not define 'owner' or 'repo' beyond the general reference to a GitHub repository. The parameter names are fairly self-evident, but the description adds no meaningful semantic depth.
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?
Begins with 'Get summary info for a GitHub repository' which is a specific verb plus resource, and lists concrete fields (description, stars, language, last push) that clearly distinguish it from the sibling tool recent_commits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus recent_commits, nor does it provide prerequisites or exclusions. Usage context must be inferred from the word 'summary' and the listed output fields.
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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