youtube_analyse_niche

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

No annotations are provided, so the description carries full burden. It discloses that it filters out Shorts (<60s) and active live streams automatically—an important behavioral trait. It also enumerates the computed metrics (median views, engagement rates, top tags, etc.), giving a clear picture of what the tool does beyond simply 'analysis.' It stops short of explaining potential rate-limit or quota behavior, but for a read-only data aggregation tool, transparency is strong.

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 concise and front-loaded with the core purpose. It packs substantial detail into two sentences without redundancy. Every sentence adds value—first states the primary role, second enumerates metrics and automatic filters. No 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?

With no output schema, the description compensates by listing the aggregate statistics returned (median views, engagement rates, top tags, duration distribution, publishing day patterns, channel size breakdown). It also clarifies filtering behavior. Minor gaps: it does not specify the exact response structure or how results are sorted, but for a high-level analysis tool, the description gives enough context for an agent to anticipate outputs.

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 100%, so each parameter is already described. The tool description adds some contextual meaning (e.g., that minViews is applied after fetch, and that Shorts are filtered automatically), but it does not provide new semantic details for parameters beyond the schema. Baseline 3 is appropriate.

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 a specific verb+resource: 'High-level niche analysis' for YouTube research. It distinguishes from siblings by highlighting that it searches, fetches metadata, computes engagement metrics, and returns aggregate statistics—something none of the sibling tool names suggest. The phrase 'primary entry point' further clarifies its unique role.

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 identifies itself as 'the primary entry point for YouTube research,' which implies it should be used first for broad niche analysis. However, it does not explicitly mention when to use sibling tools like youtube_get_video_details or youtube_search_niche as alternatives, nor does it provide exclusion criteria. Some context is present, but explicit guidance is lacking.

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