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

Annotations already declare readOnlyHint/openWorldHint/idempotent/destructive, so safety is covered. The description adds genuinely new behavior: no live crawl on a miss, that heat is not equivalent to plays, that source_rank only works with a cohort, and that results can include seasons.

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?

Three dense, front-loaded sentences with no filler; the scope constraint and the key caveats come first. The telegraphic phrasing ('Heat is not plays') borders on cryptic, but nothing is wasted.

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?

It conveys purpose, scope, result-shape hints, and two behavioral caveats, which is meaningful given there is no output schema. But with seven undocumented parameters and no annotation-level detail on filtering, the definition is not complete enough for confident 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 7 parameters and 0% schema description coverage, the description must carry the load, but it only maps query to title/genre/tags and touches sort=source_rank and the cohort requirement. Sort values, limit bounds, channel, category, and officialOnly are left entirely undefined.

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 names a specific verb (Search) and resource (the currently published Chinese AI video/manju catalogue) and lists the searchable dimensions (title, genre, tags) plus what comes back (source dates, official/search/introduction destinations). This is clearly distinct from the sibling tools evaluate_video_publish and get_video_platform_rules, which do not search a catalogue.

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 gives operational context (read only, no crawl on miss) and one conditional rule (source_rank requires one cohort), which helps the agent compose a valid call. However, it never states when to prefer this tool over alternatives or when not to use it, so usage is only implied.

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