estimate_audience_size

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'deprecated interest-list mode,' which hints at legacy functionality, but doesn't describe key behaviors: whether this is a read-only estimation, if it requires authentication (implied by 'meta_access_token' but not stated), rate limits, or what the output contains. For a tool with 6 parameters and no annotations, this leaves significant gaps in understanding how it operates.

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 a single, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words, making it easy to parse quickly. Every part of the sentence contributes to understanding the tool's use cases.

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 complexity (6 parameters, no annotations, but an output schema exists), the description is incomplete. The output schema means return values don't need explanation, but the description lacks details on authentication needs, parameter interactions, and behavioral traits. It covers basic purpose but misses critical context for effective use, especially with undocumented parameters.

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 description coverage is 0%, meaning parameters are undocumented in the schema. The description adds minimal semantics: it implies 'targeting' and 'interest_list' are used for estimation, and 'interest_list' is deprecated. However, it doesn't explain the purpose of other parameters like 'meta_access_token', 'ad_account_id', 'optimization_goal', or 'interest_fbid_list', nor their relationships. With 6 parameters, the description fails to compensate for the lack of schema documentation.

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 purpose: 'Estimate audience size for targeting specs or validate deprecated interest-list mode.' It specifies the verb ('estimate') and resource ('audience size'), and distinguishes between two use cases. However, it doesn't explicitly differentiate from sibling tools like 'search_demographics' or 'suggest_interests' that might also relate to audience analysis.

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 by mentioning two modes: 'for targeting specs' and 'validate deprecated interest-list mode.' This provides some context on when to use the tool, but it doesn't offer explicit guidance on when to choose this over alternatives (e.g., vs. 'search_demographics' for audience insights) or prerequisites like required parameters. The guidance is present but not comprehensive.

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