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

Goes well beyond the annotations by disclosing the credit economics (1 credit per 2 creators, count 20 = 10 credits, no results are free), the 15-minute repeat-call caching that avoids double charging, and the operational caveat that ai_estimate values are estimates that must be surfaced to the user. It also explains why readOnlyHint is false: the call has a real cost. That is exactly the kind of context annotations cannot carry.

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?

Front-loads the purpose in one sentence, then layers the how-to-use, pricing, caching and follow-up routing in a tight sequence with no filler. It is on the dense side for a single paragraph, but every clause carries information an agent needs before calling.

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?

With no output schema, the description correctly fills the gap by describing what comes back (creator id, search_id, ai_estimate) and how each is consumed downstream. Combined with the cost and caching rules, an agent has everything needed to call this correctly and present results responsibly.

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 75% and the description adds real meaning on top: 'any language' for brief, similar_to's three accepted input forms, and the credit consequence of count ('count 20 = 10 credits'). It does not restate the count min/max bounds, which the schema already covers, so it stops just short of a 5.

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?

States a specific verb and resource ('Search Kolect's database of TikTok, Instagram and YouTube creators') and immediately distinguishes itself from siblings like lookup_creators and list_saved_creators by naming them for follow-up work. An agent knows exactly what this tool returns: creators, not accounts or saved lists.

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?

Explicitly prescribes the three modes of use: a plain-language brief, similar_to for lookalike discovery, or both. It even names the accepted forms of similar_to (profile link, @handle, creator id) and routes the agent onward to check_fake_followers, get_emails, save_creators, load_more_results and get_search_results. Nothing about when to reach for this tool is left to inference.

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