scout_niche_channels

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains the core behavior—identifying and ranking channels—and the sorting/filtering options. However, it never states whether the operation is read-only, whether it has side effects, or whether it requires authentication or has rate limits. The phrase 'campaign' adds ambiguity about what happens when invoked. This is a meaningful gap for a tool with zero annotation support.

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 well-structured: a one-sentence purpose, a one-sentence use-case list, and a compact Args block. Every line adds needed information, especially given the 0% schema description coverage. It is longer than a one-liner, but each component is necessary and front-loaded.

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 tool with 7 parameters, no annotations, and no schema descriptions, the description is largely complete for correct invocation: it covers all parameters, defaults, and use cases. An output schema exists, so the return shape is already structured. The main missing piece is an explicit statement of side effects or limitations, but overall the definition is sufficient for an agent to call the 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 description coverage is 0%, so the description must fully document the parameters. It does: every one of the 7 parameters appears in the Args list with a clear meaning and most have examples (e.g. '['ai automation', 'saas tools']' for niches, '5000 or 10000' for min_subscribers, 'ISO 3166-1 alpha-2' for region_code, and the valid sort_by values). This surpasses the schema, which only provides titles and defaults.

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 clearly states the tool's function: 'Launch a multi-niche discovery campaign to identify and rank top YouTube channels.' This is specific and actionable, and the listed use cases (creator scouting, influencer marketing, competitor analysis, sponsorship outreach) add context. It does not explicitly name sibling tools or explain how it differs from similar tools like search_channels or find_viral_outliers, so it falls short of the highest mark for sibling differentiation.

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 description provides clear context for when to use the tool by listing four concrete use cases: creator scouting, influencer marketing campaigns, competitor analysis, and sponsorship outreach. It does not include exclusions or explicitly direct the agent to an alternative, so it stops short of full usage guidance.

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