Posts that mention the brand on TikTok

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

Annotations only declare read-only and open-world. The description adds substantial behavioral detail beyond annotations: the four conditions causing ambiguous empty results, the 1,000 post cap, null-not-zero semantics for views/reach, 48-hour thumbnail URL expiry, and the authorization requirement. It also distinguishes between TikTok withholding numbers and measurement of nothing—critical for correct interpretation.

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 long but every sentence carries critical operational detail. It front-loads the purpose and then uses capital-letter warnings to highlight hard constraints. While not concise in word count, it is efficiently structured, with no filler. The use of all-caps for key caveats aids scanning.

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 tool with no output schema, the description covers interpretation of results (null vs zero, empty ambiguity, cap), prerequisites (business account, authorization), and edge cases (age, recency, thumbnail expiry). It also references companion tools for status checks. An agent has everything needed to call this correctly and avoid misreporting silence.

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 57%, so the description must compensate. It adds meaningful context for 'days' (TikTok indexes nothing older than 90 days), 'regions' (filters on the mentioning author's registration country, refuses unpublished codes), and 'fields' (defaults to every field). It doesn't explicitly explain cursor, maxCount, sortField, or sortOrder, but those have schema descriptions or enums. The added context for the mentioned parameters elevates it above 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?

Description clearly states the verb and resource: 'every public post whose CAPTION @-mentions the connected account's handle.' It also differentiates from sibling tools by naming x_mentions and list_threads_mentions as analogous but TikTok-specific. The scope constraints (public, <90 days, business account) are explicit, leaving no ambiguity about what the tool retrieves.

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 explicit when-to-use guidance: it's the brand-monitoring read missing for TikTok, and it instructs the agent to read the four TikTok enforcement caveats before reporting silence. It names the prerequisite (TikTok business account) and points to tiktok_account_status and tiktok_account_insights for checking. It also mentions the authorization need and refers to tiktok_account_status for verifying permission.

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