NPM Context Agent MCP

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose targeting specific aspects of npm package analysis, with no ambiguity or overlap. For example, get_package_info provides general metadata while get_package_quality focuses on npms.io metrics, and get_package_size handles bundlephobia data.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case throughout, using descriptive action verbs like 'get', 'search', and 'compare' paired with specific nouns. This creates a predictable and readable naming convention across all nine tools.
Tool Count5/5
Nine tools is well-scoped for npm package analysis, providing comprehensive coverage without bloat. Each tool earns its place by addressing distinct aspects like metadata, dependencies, versions, quality metrics, and search functionality.
Completeness4/5
The tool set provides excellent coverage for npm package research and comparison, including search, metadata, dependencies, versions, quality metrics, and bundle analysis. Minor gaps might include package installation/management operations or deeper GitHub integration beyond README access, but core workflows are well-supported.
Average 3/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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, so the description carries the full burden of behavioral disclosure. It states the action (compare) but doesn't describe what the comparison entails (e.g., returns a structured output, side-by-side view), any limitations (e.g., only works for certain package types), or potential side effects. For a tool with no annotation coverage, this is a significant gap in transparency.
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?
The description is extremely concise with a single sentence, 'Compare two packages side-by-side', which is front-loaded and wastes no words. It efficiently conveys the core action without unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which should document return values), the description doesn't need to explain outputs. However, with 2 parameters at 0% schema coverage and no annotations, the description is too minimal—it doesn't clarify comparison aspects or usage context. For a simple comparison tool, it's borderline adequate but lacks depth for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no details on parameters. The description mentions 'two packages' but doesn't specify what 'packageName1' and 'packageName2' represent (e.g., package IDs, names, versions) or any constraints (e.g., must be valid packages). This fails to compensate for the lack of schema documentation, leaving parameters largely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Compare two packages side-by-side' clearly states the verb (compare) and resource (packages), making the purpose understandable. However, it's vague about what aspects are compared (e.g., versions, dependencies, quality) and doesn't distinguish from sibling tools like 'get_package_dependencies' or 'get_package_quality', which might offer overlapping functionality. This leaves room for ambiguity in tool selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_package_dependencies' and 'get_package_quality', it's unclear if this tool aggregates such data or serves a different purpose. There's no mention of prerequisites, exclusions, or specific contexts for use, leaving the agent to guess based on tool names alone.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves metadata but doesn't describe what 'comprehensive' entails, potential rate limits, authentication needs, error conditions, or the format of returned data. This leaves significant gaps for an AI agent to understand how to use it effectively.
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?
The description is extremely concise with a single, front-loaded sentence that directly states the tool's purpose. There's no wasted verbiage, and it efficiently communicates the core function without unnecessary details, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description doesn't need to explain return values, which helps. However, with no annotations, 2 undocumented parameters, and multiple sibling tools, the description is too minimal. It should clarify the scope of 'comprehensive' metadata and when to use this versus other package tools to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 2 parameters with 0% description coverage, and the tool description doesn't mention parameters at all. It doesn't explain what 'packageName' and 'version' represent, their expected formats, or whether 'version' is optional for latest versions. This fails to compensate for the lack of schema descriptions, making parameter usage ambiguous.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Get') and resource ('comprehensive package metadata'), making it easy to understand what it does. However, it doesn't distinguish this tool from its siblings like 'get_package_versions' or 'get_package_dependencies', which also retrieve package metadata but for specific aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_package_versions' or 'get_package_quality', it's unclear if this tool should be used for general metadata or as a fallback when more specific tools aren't available. No explicit when/when-not statements or prerequisites are mentioned.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information, implying a read-only operation, but doesn't cover aspects like rate limits, error handling, authentication needs, or what the output contains (though an output schema exists). This is a significant gap for a tool with zero annotation coverage.
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?
The description is a single, efficient sentence with zero waste—it directly states the tool's function and source. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly without unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is minimally adequate. It specifies the action and source, but lacks usage guidelines, parameter details, and behavioral context. The output schema mitigates some gaps, but overall completeness is limited, aligning with a baseline score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters are undocumented in the schema. The description adds no meaning beyond the schema—it doesn't explain what 'packageName' or 'version' represent, their formats, or examples. For a tool with 2 parameters and low coverage, this fails to compensate, leaving semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Get bundle size information from bundlephobia', specifying the action (get), resource (bundle size information), and source (bundlephobia). It distinguishes from siblings like get_package_info or get_package_dependencies by focusing specifically on size metrics, though it doesn't explicitly contrast them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like get_package_info (which might include size) or compare_packages (for relative sizing), there's no indication of context, prerequisites, or exclusions, leaving the agent to infer usage.
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 provided, the description carries the full burden of behavioral disclosure. It states the tool searches the npm registry by keyword, implying a read-only operation, but doesn't disclose any behavioral traits like rate limits, authentication needs, pagination, or what happens with invalid queries. For a search tool with zero annotation coverage, this is a significant gap in transparency.
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?
The description is a single, efficient sentence that directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, making it easy for an agent to quickly understand the core functionality. Every word earns its place, with no wasted information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is incomplete. It covers the basic purpose but lacks usage guidelines, parameter details, and behavioral context. The presence of an output schema means the description doesn't need to explain return values, but it should still address other aspects like when to use it versus siblings, which it fails to do.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate for the lack of parameter documentation. It mentions 'by keyword', which hints at the 'query' parameter, but doesn't explain the 'limit' parameter or provide any details on parameter formats, constraints, or usage. With 2 parameters and no schema descriptions, the description adds minimal value beyond what's inferred from the tool name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('search') and resource ('npm registry for packages'), specifying it's by keyword. It distinguishes from siblings like 'get_package_info' or 'compare_packages' by focusing on keyword-based search rather than specific package retrieval or comparison. However, it doesn't explicitly differentiate from all siblings, such as 'get_download_stats' which might also involve searching, so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'search_packages' over 'get_package_info' for finding packages, or when to use it in conjunction with other tools like 'compare_packages'. There's no context on prerequisites, such as needing a query parameter, or exclusions, leaving the agent to infer usage from the tool name alone.
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 provided, the description carries the full burden of behavioral disclosure. It states it 'gets' data, implying a read-only operation, but doesn't specify if it requires authentication, rate limits, or the format of returned statistics. This leaves significant gaps for a tool that likely interacts with an external API.
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?
The description is a single, efficient sentence with zero waste, front-loading the core functionality. It's appropriately sized for a simple tool, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and a simple input schema, the description is minimally adequate. However, it lacks details on behavioral aspects like API constraints or error handling, which are important for completeness in a real-world usage scenario.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it adds no information about parameters beyond what the schema implies. The schema clearly defines 'packageName' and 'period' with an enum, so the baseline is 3, as the description doesn't enhance understanding of what these parameters mean in context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get download statistics') and resource ('from npm'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'get_package_info' or 'get_package_quality', which might also provide statistical data, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_package_info' or 'compare_packages', nor does it mention prerequisites or exclusions. It's a basic statement of function without context.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves dependencies but doesn't mention any behavioral traits like whether it's read-only, if it requires authentication, rate limits, or what happens with invalid inputs. This leaves significant gaps for a tool with no annotation coverage.
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?
The description is a single, efficient sentence that directly states the tool's function without any unnecessary words. It's appropriately sized and front-loaded, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there's an output schema (which handles return values), no annotations, and low complexity, the description covers the basic purpose but lacks details on usage, parameters, and behavior. It's minimally adequate but has clear gaps, especially with 0% schema coverage and no annotations to compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description mentions 'for a package', which implies the 'packageName' parameter, but doesn't explain what 'version' does or provide any additional meaning beyond the basic schema. With 0% coverage, this adds minimal value, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('dependencies, devDependencies, and peerDependencies for a package'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from siblings like 'get_package_info' or 'get_package_versions', which might also provide dependency-related information, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings such as 'get_package_info' that might include dependencies, there's no indication of when this specific tool is preferred or what its unique context is, leaving usage unclear.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on traits like rate limits, authentication needs, response format, or error handling. This is a significant gap for a tool with no annotation coverage.
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?
The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter) and the presence of an output schema, the description is somewhat complete. However, with no annotations and 0% schema coverage, it lacks behavioral context and parameter semantics, making it only minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It implies the 'packageName' parameter is used to fetch metrics but doesn't add meaning beyond what the schema's property name suggests. With only one parameter, the baseline is 4, but the description fails to provide any semantic context, lowering the score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('quality metrics from npms.io'), making the purpose understandable. However, it doesn't specifically differentiate this tool from its siblings like 'get_package_info' or 'get_download_stats' that might also provide quality-related metrics, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_package_info' that might include quality metrics, there's no indication of what makes this tool unique or when it should be preferred, leaving usage unclear.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions retrieving content from GitHub but doesn't specify aspects like rate limits, authentication needs, error handling, or response format (though output schema exists). This leaves significant gaps for a tool interacting with external APIs.
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?
The description is a single, efficient sentence that directly states the tool's function without any wasted words. It's front-loaded and appropriately sized for its purpose, earning full marks for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (external GitHub access) and lack of annotations, the description is incomplete—it doesn't cover behavioral traits like API constraints. However, the existence of an output schema reduces the need to explain return values, making it minimally adequate but with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it doesn't explain the parameters 'packageName' or 'version' beyond what's implied. It adds minimal value over the schema, as it doesn't clarify parameter meanings, formats, or examples, resulting in a baseline score due to the output schema's presence.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get README file content') and resource ('from a package's GitHub repository'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_package_info' or 'get_package_quality', which might also provide README-related data, so it misses full sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_package_info' that might include README content, there's no indication of when this tool is preferred, such as for raw README text or specific GitHub access, leaving usage context implied at best.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states a read operation ('Get'), implying it is likely safe, but does not mention any behavioral traits such as rate limits, authentication needs, or what the output contains (e.g., list format, pagination). This leaves significant gaps for a tool with no annotation coverage.
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?
The description is a single, efficient sentence with zero waste. It is front-loaded and appropriately sized for the tool's simplicity, making it easy to parse quickly.
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?
Given the tool's low complexity (1 parameter) and the presence of an output schema, the description is complete enough for basic understanding. However, without annotations and with 0% schema coverage, it could benefit from more context on behavior or usage, but the output schema mitigates some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate. It mentions 'packageName' implicitly by referring to 'a package', but does not add meaning beyond the schema, such as format examples or constraints. With 1 parameter and low coverage, the baseline is 3 as it minimally addresses the parameter but lacks detailed semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'all available versions of a package', making the purpose understandable. However, it does not explicitly differentiate from sibling tools like 'get_package_info' or 'get_package_dependencies', which might also provide version-related information, so it lacks sibling differentiation for a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_package_info' that might include version data, there is no explicit or implied context for choosing this tool, leaving the agent without usage direction.
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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