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explore_existing_apis

Discover existing APIs that provide specific functionality to avoid reinventing solutions and leverage proven implementations.

Instructions

Explore existing APIs that might provide the needed functionality

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
functionalityYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. However, it only vaguely describes the action ('explore') without detailing traits like whether it's read-only, how results are returned (e.g., list, details), potential rate limits, or authentication needs. For a tool with no annotation coverage, this is inadequate, failing to inform the agent about critical operational aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, straightforward sentence that efficiently conveys the core idea without unnecessary words. It is front-loaded with the main action ('Explore existing APIs'), making it easy to parse. However, it could be more structured by explicitly stating the tool's scope or output, but it earns high marks for brevity and clarity within its limited content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (1 parameter, no annotations, but has an output schema), the description is incomplete. It does not explain what 'explore' entails behaviorally, how results are returned (though the output schema might cover this), or usage context. For a tool with no annotations and low schema coverage, more detail is needed to guide the agent effectively, making it minimally adequate at best.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 1 parameter with 0% description coverage, so the schema provides no semantic information. The description mentions 'functionality' implicitly but does not explain what the parameter represents (e.g., a search query, API category) or how to format it. It adds minimal value beyond the schema, insufficient to compensate for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a vague purpose ('Explore existing APIs that might provide the needed functionality') without specifying what 'explore' entails (e.g., search, list, analyze) or what resource is being explored (e.g., APIs in a registry, codebase, or external sources). It distinguishes from siblings like 'discover_packages' or 'validate_package_usage' by focusing on APIs, but the verb is too generic, making it unclear how this differs from similar tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing a functionality query), exclusions (e.g., not for creating APIs), or direct alternatives among siblings (e.g., 'discover_packages' for packages instead of APIs). The lack of context leaves the agent guessing about appropriate usage scenarios.

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

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