coda_list_pack_formula_analytics

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

The description adds useful behavioral context beyond annotations: it specifies the return data (invocation counts, error rates, execution times) and notes the access restriction (pack maker only). Annotations already indicate read-only, idempotent, and open-world; description complements them without contradiction.

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 three sentences: first states the purpose, second lists the return data, third notes access restriction. Every sentence adds value without redundancy, and it is front-loaded with the verb and resource.

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 tool has an output schema and five parameters with full schema descriptions, the description sufficiently covers what the tool returns (per-formula analytics) and its access constraint. It could mention pagination implied by cursor, but the overall completeness is high.

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% with clear descriptions for all parameters. The description does not add additional meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.

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 lists analytics data for individual formulas within a pack, specifying metrics like invocation counts, error rates, and execution times. The name and description distinguish it from pack-level analytics (e.g., coda_list_pack_analytics), but there is no explicit contrast with siblings.

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 mentions that the data is 'only available to the pack maker,' implying a prerequisite. However, it does not specify when to use this tool versus other analytics tools (e.g., coda_list_pack_analytics, coda_get_pack_analytics_summary) or provide guidance on alternatives.

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