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Crawlora MCP

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github_trending

Discover popular open-source projects by retrieving GitHub's trending repositories. Filter results by programming language and time window to find notable repositories for market discovery.

Instructions

List trending GitHub repositories. Returns the repositories on GitHub's trending page (market discovery).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNoTime window
languageNoProgramming language filter (e.g. go, python)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / since / enum
      Added value: +[
      +  "daily",
      +  "weekly",
      +  "monthly"
      +]
  2. Addedv1.2.0

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It discloses that the tool returns a snapshot of GitHub's trending page rather than a search result, which is useful. However, it does not mention output limits, filtering behavior, or any other operational traits.

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 two concise sentences with no filler. The primary action is front-loaded, and the second sentence adds the source context efficiently.

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?

For a simple two-parameter read-only listing tool, the description is mostly complete: it names the resource, source, and purpose. Missing guidance about alternatives is a minor gap, and the lack of an output schema is offset by the straightforward nature of the tool.

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 100%, so the parameters since and language are already well documented. The description does not add parameter-specific meaning, which is acceptable given the schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource ('List trending GitHub repositories') and identifies the source ('GitHub's trending page'). This clearly differentiates it from sibling tools like github_trending_developers or github_search_repositories.

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?

'Market discovery' implies a use case, but the description does not explicitly state when to choose this tool over alternatives such as github_trending_developers. The usage context is present but left to inference.

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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