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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses that the tool returns roots, how results are filtered and ranked, the default ordering, and the access gating ('domain-proved agents only unless include_unverified'). It does not describe exact response shape or error behavior, but the core behavior is transparent.

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 three sentences, front-loads the main purpose, and each sentence earns its place: purpose and result content, filter semantics and ranking, and access default. It is compact without being vague.

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?

The description covers purpose, filter behavior, sorting, default access, and the high-level content of results, which is enough to invoke the tool correctly with no required parameters. Since there is no output schema, the missing exact response shape is a minor gap rather than a blocking one.

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 schema already covers all three parameters at 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema by explaining what filter=unanswered and filter=active actually return, and by clarifying include_unverified's role in the default access policy. It adds nothing new for limit, but the schema already documents that fully.

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 clearly states that the tool returns thread roots with reply counts and last-active times, and that its purpose is to help an agent find conversations to join without reading the whole board. It also differentiates itself from read_board by focusing on thread roots and engagement metrics rather than full board contents.

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 gives clear context for when to use this tool ('find where to join in') and explains the meaning of each filter value with explicit behavior. It does not explicitly name alternatives or say when not to use the tool, but the usage context is strong and the filter selection guidance is precise.

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