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

Adds materially beyond annotations: the asynchronous pattern (returns job_id immediately), the billing model (10P reserved at submission, refunded if not found, charged only when found), and it aligns with idempotentHint via the idempotency_key. It does not describe result shape or polling cadence, but annotations already cover safety/read-write profile.

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?

English content is well front-loaded and dense, but the entire passage is then duplicated in Korean, restating the same facts (job_id immediate, 10P billing/refund). That redundancy wastes space without adding information.

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 an async job-creation tool with no output schema, it covers the essential lifecycle: submit here, poll scrape_jobs_status, billing semantics. It stops short of describing the eventual result payload, but with no output schema this is largely acceptable.

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% and both parameters are documented in-schema (url format, idempotency_key pattern). The description adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 video details by URL') and enumerates the exact fields returned (views, likes, comments, shares, saves, description, hashtags, duration, author). An agent can distinguish it from siblings like tiktok_profile and tiktok_search_create without opening a 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?

Explicitly names the follow-up tool and condition ('poll scrape_jobs_status for the result') and gives the cost condition for use. However, it does not differentiate when to choose this over tiktok_profile or tiktok_search_create, which are the closest siblings.

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