Search indexed sponsorships by brand name, category and creator size.
Args:
query: Substring of the brand name (case-insensitive).
category: Category enum value, e.g. 'vpn_privacy' (see list_categories).
min_subscribers: Only creators with at least this many subscribers.
limit: Maximum results (1-200).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| category | No | ||
| min_subscribers | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden, and it uses it well: query is a case-insensitive substring, min_subscribers is a lower bound, limit caps at 200, and 'indexed' hints at a pre-computed dataset. It does not detail return shape or error behavior, but the main filtering semantics are disclosed.
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 one-line summary is front-loaded and the Args block follows a clean, scannable format. Every line adds information; there is no filler or repetition of schema defaults.
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?
All call parameters are fully specified and no output schema exists, so the agent can construct a valid request. Still, the description never states what the tool returns (shape/fields of a sponsorship object) or how multiple filters combine, which are gaps for a tool with no output schema and no annotations.
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 0%, yet every one of the four parameters receives a purpose-specific explanation beyond plain names (e.g., 'case-insensitive', 'only creators with at least', 'maximum results (1-200)'). The category example plus reference to list_categories compensates for missing enum metadata.
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 opens with 'Search indexed sponsorships', naming a specific verb, resource, and the three filtering dimensions (brand name, category, creator size). This clearly differentiates it from siblings get_brand/get_creator, which retrieve single entities, and list_categories, which lists enum values.
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 primary use case — searching sponsorships by filters — is clear, and the hint 'see list_categories' tells the agent where to find valid category values. However, it never explicitly contrasts with get_brand/get_creator or states when a direct lookup should be preferred over this search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct access pattern: get_brand by brand slug, get_creator by YouTube handle, list_categories for taxonomy, and search_sponsorships for filtered discovery. There is slight overlap between get_brand and search_sponsorships when looking up a brand, but the exact-slug vs substring/filter distinction makes the boundaries clear.
Tool names follow a consistent verb_noun pattern: get_ for direct lookup, list_ for enumeration, and search_ for queries. Naming style is uniform with lowercase and underscores.
Four tools is a well-scoped size for a read-only sponsorship index. Each tool covers a core access pattern without redundant additions.
The tool surface covers the main lookup and discovery workflows: by brand, by creator, by category, and by filtered search. Minor gaps like pagination or a full index dump are absent, but agents can still answer typical sponsorship questions.