Analyse a channel's performance

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

Annotations already cover read-only, idempotent, and non-destructive hints. The description adds valuable behavioral context beyond that: it explains the output is a multiple per video, clarifies the meaning of the multiple (3.2x), and flags how shorts are treated. This goes beyond what annotations alone provide.

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 two sentences, with the core concept (scoring against own median) front-loaded. Every sentence adds distinct value: the first explains the method and purpose, the second explains the output and the shorts caveat. No filler words.

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?

Given the tool's complexity relative to siblings, the description fully covers the key aspects: the metric, the meaning of the result, the use case, and the caveat about shorts. There is no output schema, so explaining the return format is essential and done clearly. Nothing critical is missing.

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 all three parameters are documented in the schema itself. The description does not add extra detail about parameters, but the baseline of 3 applies because the schema carries the full load. No compensation needed.

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 states a specific verb ('Score') and resource (a channel's recent videos) and defines the unique metric (relative to the channel's own median views). This clearly distinguishes it from sibling tools like get_channel_analytics, which would report absolute metrics.

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 says 'Use this before modelling anyone's content,' giving a clear recommended context. It also warns about shorts being non-comparable, an important behavioral caveat. This provides actionable guidance on when and how to apply the tool.

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