get_metric_summary

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

No annotations are provided, so the description carries full burden. It discloses the metrics computed, default set, and filter keys. However, it does not describe return format or performance implications, but is still adequate for a compute tool.

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 well-structured with a clear purpose, list, and arguments, but could be slightly more concise. It is front-loaded and every sentence adds value.

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 no output schema, the description explains parameters and default behavior well. It lacks detail on return format, but for a summary tool with clear metric names, it is fairly complete.

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 description explains each parameter beyond the schema: query_id as dataset ID, metrics as list with defaults, and filters with specific keys. This compensates for the 0% schema description coverage and adds significant semantic value.

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 computes metric summaries for a dataset, listing specific scalar and distribution metrics, which distinguishes it from sibling tools that retrieve posts or describe queries.

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 explains what the tool does and its default behavior when metrics is omitted, but does not explicitly state when to use this tool versus alternatives like get_posts_by_ids or search_posts. Usage is implied but not directly contrasted.

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