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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description adds genuinely new behavior: per-call price of ¥0.1, billing only on success, and automatic refund for failures or empty results — cost/risk information an agent cannot get from structured fields. Pagination depth or result caps are still unstated.

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?

Four short sentences ordered purpose → return → usage → cost, so the most decision-relevant information is front-loaded. Every sentence carries distinct information, though the pricing sentence could be tightened slightly.

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?

There is no output schema, and the description compensates by describing the return payload (post list, content ID, basic engagement metrics) and the chaining path to detail/comments. The only real gap is pagination semantics for the page parameter and any result-count limits, which matter for a search tool at this price point.

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%, with page, query, and the _token fallback auth all documented in the schema itself, so baseline 3 applies. The description mentions the returned content ID but adds no syntax, length, or encoding guidance for the query keyword beyond the schema.

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 ('按关键词搜索微博') and immediately names the return shape (post list with content ID and basic engagement data). This clearly separates it from siblings like weibo_hot_search (trending) and weibo_user_posts (author-scoped) without needing the 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 three use cases (keyword monitoring, content discovery, building candidate sets) and explains the downstream flow — the returned ID feeds weibo_post_detail and weibo_post_comments. It stops short of naming when NOT to use it or pointing at the sibling alternative (e.g., hot search for trending), so it is clear context without exclusions.

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