Creators x Brands: UGC creators who are your customers

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

Beyond the sparse annotations, it discloses the async job pattern (returns job_id plus instant CxB matches, fresh grading usually within 2 minutes, get_job waits), concrete rate limits (5 creators per email on free, 3 or 10 fresh searches every 5 hours on paid), and payment gating via a Stripe link that must be paid before the search starts. It also states the side effect that the full list with contacts is emailed to the supplied address.

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?

It is front-loaded with the search criteria and the return behavior before pricing detail, and every sentence is informative. The pricing and fair-use passage is lengthy and largely duplicates the plan parameter description, which is the main redundancy.

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 12 parameters, an async job handoff, and no output schema, the description does the heavy lifting: it explains what is returned immediately, when fresh results arrive, and where the full contact list goes. It stops short of describing failure modes other than unpaid plans, so it is strong rather than exhaustive.

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 92%, so the schema already documents nearly every parameter, including plan limits, country as preference vs requirement, and the default follower range. The description adds little parameter-level meaning beyond the email requirement and asking for email plus product_url in one question, so the baseline 3 applies.

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 names a specific verb and resource ('Starts a search for real TikTok creators') and pins down scope with concrete criteria: judged from bio and posts, active in the last 30 days, views at least 0.3x followers, brand's customer. It also distinguishes itself from topic- or follower-count-driven searches, so an agent can tell it apart from a generic creator lookup.

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 a clear selection rule ('Use it when the brief is about who the creator is, not just a topic or follower count') and routes the agent to the get_job sibling immediately after calling. It does not compare against request_outreach or get_request, so the when-not guidance is incomplete.

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

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

Goes well beyond the annotations by disclosing long-poll blocking behavior, the repeat-until-terminal-state loop, and the rich result payload (quoted evidence per must-have, follower/view metrics, contact route, funnel counts). Annotations already cover the read-only/idempotent safety profile, so this added operational context is the right kind of contribution; only failure behavior is left unstated.

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-loaded with the core purpose, but the long parenthetical is bloated and contains a redundant repetition ('how many were found, and the funnel (how many were found, active and checked)'). The wait_seconds range is restated from the schema, so a few phrases do not earn their place.

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 takes on the burden of describing return values in detail, and it covers the async/polling lifecycle. It stops short of describing the failure state payload or behavior for an unknown/expired job_id, which matters for a job-status 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 50%: wait_seconds is already documented in the schema, and the description largely repeats its range while adding the blocking semantics. job_id is never explicitly explained, though 'of a find_creators search' implies it is the identifier returned by that tool.

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: retrieve status and results of a find_creators search, and names the sibling find_creators that produces the job. An agent can distinguish this from find_creators (which starts a search) without opening either schema.

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?

Gives explicit polling guidance: it waits up to 45 seconds, and you should 'call it again until status is done or failed.' The implicit sequencing after find_creators is clear from the opening clause, though no exclusion is stated relative to get_request, which could also look like a retrieval tool.

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

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

The annotations already establish that the operation is read-only, idempotent, and non-destructive. Beyond that, the description enumerates seven possible states and explains that the latest message and an initially conditional list of accepting creators are included, though it says nothing about freshness, errors, or polling behavior.

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 single compact sentence front-loads the purpose and then lists the returned information. The status enumeration and 'once there are any' clause convey useful state and availability details without 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 a simple one-argument read, the description covers the possible states and principal returned information well, which is especially valuable because there is no output schema. Missing request_id provenance and an explicit distinction from get_job prevent full completeness.

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?

With 0% schema description coverage, the description should document request_id, but it never names the parameter or explains where to obtain its value, such as from a request_outreach response. The reference to request_outreach permits a weak inference about the identifier's origin but does not adequately compensate for the undocumented schema.

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 identifies the resource as a request_outreach request and specifies that the tool reports its status, CxB's latest message, and creators who accepted. This clearly distinguishes status inspection from initiating outreach, though it does not explicitly differentiate the similarly named get_job sibling.

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?

Naming a request_outreach request provides clear context for inspecting an existing outreach request after that workflow has begun. It does not explicitly address polling, exclusions, or when an agent should use get_job instead.

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

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

Goes well beyond the annotations by disclosing the human-in-the-loop workflow: a person replies with a quote within a day and nothing is sent to creators until that quote is accepted. That is the single most important behavioral fact about this tool (real outreach, spend, latency) and the description surfaces it plainly, along with the request_id return.

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?

Four short sentences, front-loaded with what the agent gets ('Done for you') followed by inputs, then the approval gate, then the return value. No filler or restatement of the schema.

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 15-parameter mutation with no output schema, the description covers the workflow, the required inputs and the returned request_id adequately. It stops short of saying how to follow up on that request_id (presumably via get_request), which is a minor gap given the sibling tool exists.

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 already 80%, and the description adds the required-vs-optional framing plus the relationship between job_id and find_creators and what creator_handles are for. It doesn't touch the richer parameters (must vs nice, country as preference, follower defaults), but the schema covers those well.

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 action (CxB contacts creators on the brand's behalf with the brief) and the return (who said yes, with rates). It also implicitly separates itself from find_creators by naming it as the source of an optional job_id, so an agent can place it among its siblings without opening a schema.

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?

Gives clear preconditions: supply the brief, budget, timeline and contact_email, plus optionally a job_id from find_creators or explicit creator handles. It does not explicitly state when NOT to use it (e.g. use find_creators first if you have no candidates), but the context needed to invoke it is unambiguous.

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