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gztchan

ossinsight-mcp

by gztchan

ossinsight_request

Query GitHub repository analytics through OSS Insight API endpoints to access trending repositories, contributor statistics, and collection rankings.

Instructions

Call any OSS Insight GET endpoint under /v1 and return JSON.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesEndpoint path, such as /repos/pingcap/tidb/stargazers/countries
queryNo
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 the tool calls GET endpoints and returns JSON, which covers basic behavior, but fails to disclose critical traits such as authentication requirements, rate limits, error handling, or whether it's read-only (implied by 'GET' but not stated). For a tool with no annotations, this leaves significant gaps in understanding its operational context.

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: 'Call any OSS Insight GET endpoint under /v1 and return JSON.' It is front-loaded with the core action and outcome, with zero wasted words. Every part of the sentence earns its place by specifying the tool's scope and output format.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (a general-purpose API caller with 2 parameters, no annotations, no output schema, and many sibling tools), the description is incomplete. It lacks details on authentication, error handling, rate limits, and differentiation from siblings. Without annotations or output schema, the description should provide more context to guide effective use, but it falls short.

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 50% (only the 'path' parameter has a description). The description adds minimal value beyond the schema: it implies 'path' is for endpoints and 'query' is for parameters, but doesn't explain semantics like endpoint examples beyond the schema's 'such as' note or how 'query' maps to API parameters. With low schema coverage, the description doesn't fully compensate, so it meets the baseline.

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: 'Call any OSS Insight GET endpoint under /v1 and return JSON.' It specifies the verb ('Call'), resource ('OSS Insight GET endpoint'), and scope ('under /v1'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools, which are more specific endpoints, so it doesn't reach 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 Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by mentioning 'any OSS Insight GET endpoint under /v1,' suggesting it's a general-purpose tool for accessing various endpoints. However, it lacks explicit guidance on when to use this tool versus the more specific sibling tools (e.g., 'list_collections' or 'repo_stargazers_history'), which could lead to confusion. No exclusions or alternatives are 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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