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

While annotations already mark this read-only, idempotent, and open-world, the description discloses a non-obvious behavioral trait: some returned videos may use a different sound, so callers must verify music_id. This is exactly the kind of caveat an agent needs and goes well beyond the annotations.

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?

Two sentences with no filler. The core purpose comes first, and the crucial caveat about feed behavior follows immediately. Every sentence adds value and is easy to scan.

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 low-complexity, read-only tool with full schema parameter coverage, the description covers purpose, behavior, and the key output field to verify. There is no output schema, so a bit more detail about the return shape could help, but the caveat and 'feed' framing keep this adequately complete for an agent.

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 the parameters are already well documented. The description adds no new parameter-level semantics; 'music_id' refers to an output field rather than an input parameter, so this dimension stays at the baseline.

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 the resource clearly: videos TikTok associates with a sound. It lacks an explicit verb like 'list' or 'fetch', but the phrase 'Videos TikTok associates with a sound' conveys the operation well enough and distinguishes it from sound resolution or hashtag video tools.

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 gives important context on how to interpret results ('feed seeded by the sound, not a strict filter') and instructs checking music_id. It does not explicitly name sibling alternatives or state when to choose this tool over tiktok_sound_resolve or tiktok_search_sounds, leaving the selection logic mostly implied.

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