get_insights

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

With no annotations, the description carries full burden. It explains return behavior (normalized metrics, objective-aware extraction) and the compact mode option. However, it lacks details on authentication, rate limits, or data volume limits, which are relevant for a data retrieval 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 concise, starting with a clear purpose sentence and using bullet points for arguments. It is front-loaded but could be slightly more efficient by merging the objective-aware mention into the first line. Still, no unnecessary sentences.

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 the return nature but not exact fields. It covers key parameters and usage patterns. Missing details on error handling, pagination for breakdowns, or rate limits slightly reduce completeness for a complex tool with 7 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?

The input schema has 0% description coverage for parameters, so the description compensates fully by explaining each parameter's purpose, valid values (e.g., object_id format, time_range presets, breakdowns, level, archetype, compact, limit). This adds significant meaning beyond the schema's types and defaults.

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 retrieves performance insights for Meta Ads objects, specifying the types of objects (account, campaign, ad set, ad) and highlighting objective-aware extraction. It distinguishes from siblings like get_bulk_insights by focusing on single-object insights with metric selection.

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 various advertising objectives (ecommerce, lead_gen, etc.) but does not provide explicit guidance on when to use this tool versus siblings like get_bulk_insights or when not to use it. No alternatives are mentioned.

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