pkg-peep
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
The two tools address distinct aspects of NPM package data: download statistics versus package metadata. There is no overlap or ambiguity between them.
Naming Consistency5/5Both tools follow a consistent get_npm_[noun] pattern, making their purpose predictable from the name alone.
Tool Count3/5With only two tools, the server feels thin for a general-purpose package inspection utility. This falls at the lower end of the acceptable range, earning a borderline score.
Completeness3/5The server covers basic metadata and download stats, but lacks common operations like version listing, search, or readme retrieval. Agents needing those features would hit a dead end.
Average 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
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- No critical vulnerability alerts
- No high-severity vulnerability alerts
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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 present, so the description carries the full burden for behavioral disclosure. It states the basic function but omits critical details such as how period interacts with startDate/endDate, whether the period and custom range are mutually exclusive, possible rate limits, or the structure of the returned statistics.
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 concise sentence, front-loaded with the key verb and resource, and contains no redundant or filler information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (period enum, date range parameters, no output schema, no annotations), the description is far too minimal. It fails to explain the relationship between period and startDate/endDate, what constitutes 'download statistics' (e.g., counts, points in time), or any usage constraints, leaving significant ambiguity for the agent.
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?
Schema description coverage is 100% — all four parameters have clear descriptions in the input schema. The description adds no extra semantic value beyond what is already documented, so the baseline score of 3 is appropriate.
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 clearly states the tool retrieves NPM package download statistics using a specific verb ('Get') and resource ('download statistics'). However, it does not explicitly differentiate from the sibling tool get_npm_package_info, only implying a focus on downloads rather than package metadata.
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?
No guidance is provided on when to use this tool versus the sibling get_npm_package_info. There are no exclusions, prerequisites, or alternative tool mentions, leaving the agent without contextual direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but only says 'comprehensive metadata' without detailing what fields are returned, whether network calls are made, or any limitations. The behavior is not transparent beyond the core purpose.
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, concise sentence that is front-loaded with the action and resource. Every word contributes to defining the tool's purpose with no wasteful or redundant content.
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?
The tool is simple with one well-defined parameter, but the term 'comprehensive' is vague and does not clarify expected output or edge cases. It is minimally sufficient but leaves the agent guessing about what metadata is actually included.
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?
Schema coverage is 100% for the single 'package' parameter, which is already described as 'NPM package name'. The description adds no extra semantic meaning beyond restating the resource, so the baseline of 3 applies.
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 clearly states the tool fetches comprehensive NPM package metadata, with a specific verb and resource. It does not explicitly distinguish itself from get_npm_downloads, though the scope of 'comprehensive metadata' implies broader info than just downloads.
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?
No guidance is provided on when to use this tool versus the sibling get_npm_downloads. The description only states the basic action, leaving the choice of tool to inference from names.
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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Glama performs regular codebase and documentation scans to:
- 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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