Search micro-KOLs

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

With no annotations provided, the description carries the full burden and excels. It discloses the read order (local SQLite, then shared pool if enabled and thin, otherwise Apify), the Jev labeling of fresh profiles, upload behavior conditioned on sharing, and the graceful handling of a missing APIFY_API_TOKEN (returns setup guidance without exiting). This is thorough and goes well beyond what the schema could 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?

The description is a compact paragraph that front-loads the core purpose and then efficiently lists behavioral details. Every sentence contributes new information without redundancy. It is slightly longer than strictly necessary but remains focused and well-structured.

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's complexity (5 parameters, no output schema, multiple data sources), the description is quite complete. It covers the data source selection, labeling, sharing, and error handling. It does not describe the return format or pagination, but no output schema exists, so the agent is left to infer the response shape. Minor gaps exist but are not critical for basic 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 adds minimal extra meaning—only that the follower range is passed to the Apify actor, which is already implied by the schema. It does not clarify the limit parameter or other nuances beyond what the schema already states.

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 searches micro-KOLs by platform, niche, and follower range, with a specific verb and resource. It distinguishes itself from siblings (score_fit, draft_email) by its search-oriented purpose and data sources. The opening sentence is direct and unambiguous.

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 explains the internal data source fallback logic (cache → pool → Apify) but does not explicitly tell an agent when to choose this tool over siblings or when not to use it. It implies usage through its purpose but lacks direct alternatives or exclusion criteria. The sibling names suggest distinct functions, but no explicit routing guidance is given.

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