[GitHub Intelligence] Get the programming language breakdown for a GitHub repository.
Args: owner: Repository owner (e.g. 'microsoft') repo: Repository name (e.g. 'vscode')
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | ||
| owner | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and open-world hints. Description adds that it returns a 'language breakdown', implying a mapping of languages to bytes. However, it does not detail output format, potential errors, or rate limits. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: one purpose sentence and a simple arg list. No unnecessary words. Front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two required parameters and no output schema, the description covers the essential: what it does and what inputs are needed. Could be improved by clarifying the output (e.g., mapping of language to bytes or percentage).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 0% description coverage for parameters. Description compensates by providing explicit examples for owner ('microsoft') and repo ('vscode'), clarifying their meaning. Good but could add constraints like case-sensitivity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Get' and resource 'programming language breakdown for a GitHub repository'. It is specific and distinguishes from sibling tools like get_repo_stats and search_repos which handle different aspects of repositories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention typical use cases, prerequisites (e.g., repository must exist), or when not to use. Only provides parameter examples.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping functionality across categories (e.g., multiple search_arxiv, search_google_scholar, real estate tools, DNS/WHOIS checks). An agent would struggle to differentiate between similar tools from different categories, leading to ambiguity.
Tools follow a 'category__verb_noun' pattern mostly, but verbs vary (get, search, screen, check, etc.) and some categories use different orders (e.g., 'get_repo_stats' vs 'search_repos'). The consistency is acceptable but not uniform across the entire set.
With 152 tools, the server is excessively large for a single MCP server. While it aims to be an all-in-one gateway, the sheer number overwhelms the agent and likely exceeds practical limits for coherent selection.
The server covers a wide range of domains (finance, real estate, news, developer tools, etc.) but has notable gaps (e.g., social media APIs, CRM tools). Coverage is broad but not exhaustive, and some niche areas (e.g., global stock exchanges) are over-represented.