list_audiences

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains that values are discovered from local cache and are dynamic, but it does not explicitly state safety traits (e.g., read-only, no side effects) or mention whether the cache might be stale or require syncing beforehand.

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 concise, with the core function stated first and the rationale in the second sentence. Every sentence provides value and there is no redundancy or unnecessary detail.

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?

Given the simplicity (0 params) and presence of an output schema, the description is mostly complete. It covers what the tool does, where it reads from, and why it uses live values. It could mention prerequisites like cache syncing, but that is a minor gap.

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 tool has zero parameters and the schema coverage is 100%, so the baseline is 4. The description adds context about why there are no parameters (it scans actual values in use) which is helpful, though not strictly necessary.

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 it lists distinct audience tiers from local cache with post counts. It differentiates itself from sibling tools by focusing on audience tiers specifically, and the context about discovering actual values rather than hardcoded enums adds clarity.

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 implies usage for discovering dynamic audience values rather than relying on a static enum, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. No sibling tool is referenced for comparison.

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