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

Annotations already cover the safety profile (readOnly, destructive=false, idempotent=false, openWorld), so the bar is lower. The description adds real context beyond them: the @/# prefix stripping, the 1-20 limit clamping semantics, and the full set of returned record fields — the latter is particularly valuable since there is no output schema. It does not mention rate limits, latency, or auth needs for the underlying scraper.

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?

Information-dense and front-loaded: the purpose and mode options come first, then the parameter shape, then the return fields. The field enumeration runs long as a single comma-delimited sentence, but given the absence of an output schema that space is earned rather than 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?

With no output schema, the description properly compensates by listing return field names, and it covers mode selection, query normalization, and limit clamping. It stops short of describing failure behavior (invalid username, empty hashtag, blocked scraping) which an agent calling a live open-world scraper would benefit from knowing.

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 baseline is 3. The description still adds meaning beyond the schema by disclosing the body structure as {mode, query, limit} and by stating that a leading @ or # in the query is stripped — a normalization behavior the schema does not document (the schema only says 'hashtag without #').

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?

States a specific verb and resource ('Get TikTok videos') and immediately enumerates the three supported lookup modes (username, hashtag, search keyword), which maps directly onto the tool name and title. The 'videos' framing also implicitly separates it from the sibling tiktok-comments tool without needing to name it.

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 opening sentence tells the agent which query types this tool handles and the schema-level mode enum clarifies which mode corresponds to each query shape. It does not name alternatives (e.g. tiktok-comments, instagram) or state when NOT to use it, so the routing guidance is clear but not exhaustive.

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