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

With no annotations provided, the description carries the full burden of behavioral transparency. It discloses that output is grouped per source, limited by per_source, pre-ranked by swarm health, and that the tool is expected to return a curated recommendation subset. This goes beyond the bare schema and gives the agent useful expectations about the tool's behavior.

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 purpose is front-loaded in a single clear sentence, followed by compact grouping/ranking detail and a structured bullet list of response requirements. Every section earns its place; it is slightly longer than minimal but remains focused and scannable.

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 one optional parameter and no annotations, the description covers the essential invocation context: source list, per_source limit, ranking behavior, and required response shape. It does not explain when to prefer this over search_torrents, but that gap is minor and does not prevent correct invocation.

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?

The input schema already describes per_source with a default and minimum, so schema coverage is 100%. The description reinforces the parameter's meaning by saying results are kept 'per source', but it adds no new format or syntax details beyond what the schema already provides. Baseline 3 is appropriate.

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 opens with a clear verb-resource statement: 'Get the most popular torrents right now across providers.' It then specifies the exact sources and grouping behavior, which distinguishes it from sibling tools like search_torrents, available_sources, and get_torrent. An agent can immediately understand what this tool does and how it differs.

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?

The description does not explicitly say 'use this instead of search_torrents when...', but it strongly implies the intended use case: browsing current popular releases from official top listings. The response requirements about recommending top 5-10 latest releases add practical guidance. It provides clear context without formal exclusions.

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