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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, yet the description still adds material context an agent could not infer: results are cached 30 minutes (staleness expectation), the data comes from the public REST API rather than HTML scraping (reliability/structure), and each successful call costs $0.01 USDC via x402 on Solana (a spend decision the agent must make before calling). It also provides an equivalent HTTPS endpoint for non-MCP callers.

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?

Front-loaded with the core purpose and scope in the first clause, then behavior, then pricing/endpoint details. It is dense and long-ish, but every clause carries information an agent needs (cost, caching, auth model, return shape). Minor cost: the sentence runs long before reaching the price, which arguably deserves earlier emphasis.

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, the description correctly compensates by enumerating the returned fields (full_name, URL, description, language, topics, stars, forks, issues, licence, dates, owner type, velocity). Combined with the disclosed payment model, cache TTL, and data source, an agent has everything needed to decide whether to call and what it will get back.

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%, so the baseline is 3, but the description adds real meaning: it clarifies that the 'since' window constrains repo *creation* date (not push date) and that results are ranked by stars with language/topic/min-stars acting as conjunctive filters. It also enumerates the returned fields including the derived stars-per-day velocity, which is not derivable from the params alone.

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 opening sentence gives a specific verb+resource ('Trending new GitHub repositories') and immediately bounds it: repos created in the last day/week/month, ranked by stars, via the GitHub REST search API. That scope cleanly separates it from siblings like github_health (repo health metrics) and repo_posture (security posture).

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 context is clear from the stated scope (discovering newly created, high-velocity repos) and the filterable dimensions tell an agent how to narrow results. What's absent is any explicit exclusion or routing advice – nothing says 'use github_health instead when you already have a specific repo', so the agent must infer that from sibling names.

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