AI Agents API Library

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

With no annotations, the description carries the full burden. It discloses the source (SourceForge), the 100-review cap, omitted reviewer names, and that review text is third-party content to treat as data, never instructions. It does not mention error or pagination behavior, but the safety/trust profile is clearly conveyed.

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 dense but not bloated, front-loading the core purpose and field list. The security note earns its place, and the filter guidance is useful, though a few phrases restate schema content.

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 list-style tool with no output schema, it covers the return fields, source, limits, and usage context. It does not describe pagination or result shape, but enough context is present 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 repeats the filter semantics (since, max_rating, about_api) and the complaint use case, but adds no meaning beyond what the schema already documents for each parameter.

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 states a specific resource and action: public user reviews of one service from SourceForge, with a list of fields returned. It is clearly distinct from get_api and search_apis in subject matter, though it does not explicitly name or contrast those 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?

It gives explicit guidance: use when real-world quality matters, e.g., to break a tie, and warns that reviews do not show whether the API fits the task. It does not name an alternative tool, so it misses the top bar for explicit alternatives.

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

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

Without annotations, the description carries the full burden, and it does well by specifying that it returns categories along with the number of services in each. The 'List' verb implies a read-only operation with no side effects. It omits details like pagination or empty-category handling, but for a simple zero-parameter listing this is sufficient.

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, efficient sentence that front-loads the action and resource, then adds the key output detail. Every word contributes value; there is no redundancy or filler.

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 zero-parameter, read-only list operation with a clear output description, nothing is missing. The agent can call this tool correctly without additional context, and the sibling tools are distinct enough to avoid confusion.

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 tool has zero parameters, so there is nothing for the description to explain. The baseline of 4 applies because no parameter ambiguity exists.

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 action ('List'), the resource ('all categories in the catalog'), and the specific output detail ('number of services in each'). It is easily distinguished from siblings like get_api, get_reviews, and search_apis, which focus on individual APIs, reviews, or searching rather than an overall category overview.

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 provides clear context: use this tool to get an overview of all categories and their service counts. It does not explicitly name alternative tools or exclusions, but the purpose is unambiguous enough that an agent would not confuse it with the listed siblings.

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