Find Influencers by Keyword or Niche

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds substantial behavioral detail beyond these: it explains the flat row format, that every row carries row_status and error_reason for silent failure readability, the exact pricing model ($0.001 per run plus $0.007 per creator), and the APIFY_TOKEN requirement. It also explicitly says 'Read only,' consistent with the annotations. No contradiction found.

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 efficiently organized: it leads with the core purpose, then the output shape, then exclusions, then error handling, then pricing, then auth. Every sentence contributes new information with no redundancy or fluff. The length is justified by the complexity of the tool (10 parameters, multi-platform, pricing, and exclusions). It is front-loaded with the most critical decision-relevant facts.

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 tool with 10 parameters, no output schema, and no sibling tools, the description is remarkably complete. It covers the purpose, the exact output fields (handle, profile URL, display name, follower count, search term, creator_id, similar creators), what it does not do, error handling, pricing, auth requirements, and read-only nature. An agent has everything needed to decide when to call it and to interpret its results. There are no significant gaps.

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% and each parameter has a detailed description in the schema, including defaults, ranges, and behavioral notes (e.g., us_only does nothing here, batch_size loses rows above measured point). The tool description itself does not add parameter-specific semantics beyond what the schema already provides. Since the schema carries the full burden, 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 searches multiple platforms for creators based on keywords or niche keyword sets, then filters by follower range. It explicitly names the platforms and the output structure. It also distinguishes itself from related tools (Influencer Profile Scraper, Link in Bio Scraper, Newsletter Detector) by stating what it does not do, so an agent can tell it apart even without sibling definitions.

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 explicit usage context: it is 'Discovery only' and explicitly lists what it does not do, naming the alternatives that do those things. It also mentions that it requires an APIFY_TOKEN and consumes Apify credits, which is essential for invocation. This gives clear when-to-use and when-not-to-use guidance.

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