Estatisticas de linguagens

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

With no annotations, the description discloses key behavior: it only includes public non-fork repositories and uses the main language of each repo. This goes beyond the schema, though it doesn't describe edge cases (e.g., repos without a language) or return format specifics.

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?

The description is one concise sentence, front-loaded with the main action and object. Every phrase earns its place—no redundant details or filler.

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 1-parameter tool with no output schema, the description provides adequate details on scope and method. It could mention whether the result is a list/map or whether it includes all languages, but the core purpose is clear.

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?

Schema coverage is 100% for the single 'username' parameter. The description adds no new meaning beyond the schema, which already describes it as a GitHub username (login). Baseline of 3 applies.

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?

The description states a specific verb ('Calcula' / calculates), a precise resource (percentage distribution of programming languages in public non-fork repositories of a GitHub user), and the methodology (based on each repo's primary language). This clearly differentiates it from siblings like get_github_profile and list_top_repos.

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?

It gives clear context: use when you need language distribution for a user's public, non-fork repos. It does not explicitly mention when not to use it or name alternatives, but the distinct purpose makes usage straightforward.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.