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 disclosure. It only lists the data categories returned but does not mention whether the data is aggregated across accounts, whether results are real-time or cached, or how date filters affect the output. For a tool with no annotations, this is a significant gap in transparency.

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 sentence that is concise and front-loads the purpose. It lists the key data categories without extra fluff. However, it could be more structured by indicating the optional date parameters, but the simplicity is acceptable.

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 stats tool with two optional date parameters and no output schema, the description is incomplete. It doesn't explain the meaning of the date range, whether it applies to all categories, or how the data is aggregated. With no annotations and no output schema, the agent lacks crucial context on how to use the parameters and interpret results, making it incomplete for practical use.

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%, so the description must compensate for the two parameters (date_from and date_to). It does not mention them at all, leaving the agent to guess their purpose and format. While the parameter names are somewhat self-explanatory, the description adds no value beyond the schema, which is empty of descriptions. Given low coverage, the score is penalized but baseline 3 is used because the parameter names are reasonably clear.

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 fetches an overall stats overview with specific components (unread feeds, pending posts, failed posts, inactive accounts), which distinguishes it from more specific stats tools like get_account_metrics or get_engagement_trend. However, it does not explicitly name any sibling as an alternative, so it doesn't fully differentiate itself from all possible overlaps.

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 this is for getting a high-level stats summary, but it does not specify when to use this versus get_account_metrics or get_engagement_trend. There is no explicit guidance on context, prerequisites, or when not to use it. The tool name and description suggest it's for a dashboard overview, but that is left to the agent to infer.

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