welfare_audience_uncertainty

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: the flag is non-blocking ('Filing does not block the response'), and it preserves a record for audit ('so a researcher (or the user themselves on later reflection) can audit the assumption'). It could go further by detailing persistence or visibility, but the essentials are covered.

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 somewhat long but well-structured: purpose, usage examples, parameter roles, non-blocking behavior, and sibling distinction. Every sentence contributes information without redundancy. The front-loading of the primary purpose aids quick comprehension.

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 flag tool with no output schema, the description is highly complete. It covers purpose, when to use, parameter meanings, behavioral impact (non-blocking, audit trail), and relationship to a closely related sibling. No critical information is missing.

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 baseline is 3. The description enhances this by explaining the purpose of `text` and `assumed_audience_claim` and providing examples. It does not mention `is_private` or `uncertain_about_honesty`, but the schema already provides their descriptions, so the added value is marginal but positive.

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 the tool's function: 'Flag that you are calibrating your response to an unverified claim about WHO you're talking to'. It uses a specific verb ('Flag') and resource ('audience uncertainty'), and explicitly distinguishes from welfare_request_alignment, making it unambiguous and well-differentiated.

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?

Provides explicit usage conditions: 'Use when the conversation requires you to act on an assumption about the audience that you cannot verify', with concrete examples (claimed credentials, identity, expertise, context). It also clarifies that 'Filing does not block the response — you still answer the user', which guides when to use. Distinguishes from welfare_request_alignment, offering an alternative.

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