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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, non-open-world), so the bar is lower. The description still adds useful behavior: the exact shape of the returned evidence (stated benefit, six requirements, deadline, original observation, claim link), the need to page through results, and the payload tradeoff between compact and full views — none of which the annotations convey.

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?

Five tight sentences with no filler, front-loaded with purpose and return shape before the interpretive rules and pagination/view notes. The view sentence largely restates the schema's own size figures, which is the only mild redundancy.

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?

With 13 parameters, no output schema and no required fields, the description usefully stands in for the missing output schema by describing return content, and it flags pagination. It does not touch several parameters (asOf, releaseSet, targetApp, skillBuild), but the 100% schema coverage carries those, leaving no material gap for correct invocation.

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 100%, so the baseline is 3. The description goes beyond the schema by clarifying that unknown requirements do not satisfy userCanMeet=no_card and that application categories describe the program rather than the user's eligibility — semantic nuances the enum text alone does not carry.

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 first sentence states a specific verb and resource set: "Find current official free tiers, application-based credits and relay free groups," and the second sentence enumerates the returned fields (benefit, requirements, deadline, observation, claim link). This clearly separates it from grandet_find_cheapest_api and grandet_list_apps, though it never names those siblings explicitly.

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 gives real conditional guidance for result interpretation (userCanMeet=no_card needs an explicit no-card condition; application categories describe programs, not user eligibility) and tells the agent to follow pagination. However, it never says when to prefer this tool over grandet_find_cheapest_api or grandet_list_apps, so tool-selection guidance is left to inference.

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