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

Annotations already declare readOnly=false, idempotent=false, openWorld=true and destructive=false, so the bar is lower, and the description still adds real behavior: follower bounds never auto-widen, the effective band is echoed back via applied_follower_bounds and follower_policy, and unqualified creators are dropped rather than returned. It does not disclose whether enrichment consumes credits or how queue state is mutated, which keeps it below a 5.

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 core action is front-loaded in the first clause, and the three sentences each carry distinct policy (qualification, follower band, agency email toggle). It is appropriately sized for a 14-parameter tool, though the parenthetical condition on email relaxation is dense enough to slow parsing.

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 14-parameter, non-idempotent, open-world tool with no output schema, the description covers qualification and follower policy but omits how the 'queued candidates' mode is populated, what happens to filtered-out creators, and what the response contains beyond the two echoed policy fields. Adequate but with clear gaps for such a complex tool.

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 79% and min_followers/max_followers already document their 100/9999 defaults, so the description mostly restates the schema's follower policy. It does add the important cross-cutting rule that the band applies in every mode without auto-widening, but says nothing about handles, niche, batch_size, conversation_id, or preferences_mode. Baseline 3 for high schema coverage plus one genuine addition.

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 two-stage action: enrich queued candidates or explicit Instagram handles, then keep only qualified on-niche creators with emails. That is a clear verb+resource statement an agent can act on. It stops short of naming which sibling to use instead (discover_creators, find_brand_creators), so differentiation is only implied through the schema's brand-collab note.

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?

Useful conditional rules are present: the email requirement is relaxed by the accept-no-email preference or an explicit 'emails optional' request, and exclude_agency_emails is only for direct/personal email or no-agency requests. However, there is no statement of when to pick this tool over discover_creators or find_brand_creators, nor any prerequisite such as a prior discovery run populating the queue.

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