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

The readOnlyHint annotation already establishes this as a safe, non-mutating read, so the description only needs to add context beyond that. It contributes that the tool is a static capability reference with no input, but says nothing about result stability, caching, or whether the matrix can change over time — minor but real gaps for a pre-flight check tool.

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?

A single dense sentence front-loads what the tool returns, then lists scope, then the sequencing instruction. Every clause carries information and nothing is repeated.

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?

Although there is no output schema, the description effectively describes the return value as a platform-by-data-type support matrix, which is exactly what an agent needs to interpret the result. Combined with the annotations and the empty input schema, nothing material is missing for correct invocation.

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 zero parameters, the baseline is 4, and the description correctly reinforces this with "No input," confirming no argument assembly is needed. No further parameter meaning is required or possible.

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 concrete resource (a JSON matrix of data types) and enumerates both axes: the five data types (metadata, insights, transcript, frames, comments) and the three supported platforms (YouTube +Shorts, TikTok, Instagram Reels). It also names the sibling it feeds into (framefetch_extract), so an agent can distinguish it from framefetch_search and framefetch_account without opening the 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?

"Call before framefetch_extract to confirm support" gives an explicit sequencing rule tied to a named alternative, which is strong guidance for a lookup tool. It stops short of stating when a call can be skipped (e.g., if the platform/data type is already known), so there is no explicit when-not guidance.

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