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

Annotations already declare openWorldHint=true, idempotentHint=false, and destructiveHint=false, but the description adds meaningful behavior by saying candidates are queued for enrichment. It also clarifies that queries are searched independently and are never concatenated or replaced with a fixed taxonomy. It omits details about auth, rate limits, or duplicate handling, but the annotations lower the disclosure burden.

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 three sentences and front-loads the core action before moving to query usage and similar_to guidance. Every sentence contributes useful information with no 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 an 8-parameter open-world tool with no output schema, the description covers the main search-and-queue workflow and the two most important query parameters. However, it does not explain max_results behavior, return structure or list_id handling, or how this differs from sibling discovery/search tools, leaving meaningful 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 coverage is 63%, so several parameters are already documented in the schema, including uid, bearer_token, conversation_id, and preferences_mode. The description adds real meaning for queries and similar_to by explaining independent query execution and snowballing, but it does not cover max_results or the preference parameters beyond what the schema provides.

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 verb and resource: search Instagram + TikTok for creator candidates and queue them for enrichment. It is clear what the tool does, but it does not explicitly distinguish itself from nearby siblings such as find_brand_creators or search_ugc_database.

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 clear usage context: pass many varied queries per call because each query is searched independently, and use similar_to to snowball off already-qualified Instagram handles. It does not explicitly state when to choose this tool over alternatives, so it falls short of the highest level.

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