github_trending_scraper

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

With no annotations provided, the description carries the full burden and does well: it discloses the output grain ('one row per repo or developer with stars, forks, stars-in-period and description'), that no API key or proxies are required, and the exact cost model (~$0.002 per Repository, billed to the caller's Apify account). It does not cover pagination, error behavior, or rate limits, which keeps it from a 5.

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?

Two sentences, front-loaded with what is scraped and how results are shaped, followed by the cost/auth caveat. Dense but each clause (filters, output grain, billing) carries information; the dash-separated list is slightly packed but not wasteful.

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?

With no output schema and no annotations, the description does the heavy lifting: it names the return fields, the billing model, and the no-key/no-proxy setup for a 5-parameter tool. The main residual gap is that return format details (types, ordering, empty-result behavior) are left unspecified.

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 description coverage is 100%, so the enum options, defaults, and bounds for mode/since/languages/maxResults/spokenLanguage are already fully documented in the schema. The description only echoes the language and time-window concepts without adding syntax or format detail beyond the schema, so the baseline 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?

States a specific verb and resource — scraping github.com/trending for repositories or developers — with the supported time windows and filter dimensions (programming and spoken language). It is immediately distinguishable from siblings like github_repo_health, which inspect a specific repo rather than the trending feed.

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?

Usage is implied by the 'trending' framing and the cost note, and the description implies when this tool fits (discovery of what's hot). However, it never states when NOT to use it or points to an alternative such as github_repo_health for per-repo metrics, leaving the routing decision to inference.

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