记录运营指标

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

The annotations provide no strong safety signals (readOnlyHint=false, destructiveHint=false), so the description must carry the behavioral burden. It does disclose that the tool writes to a local ledger and does not fetch pages, but it does not explain whether repeated calls append or overwrite existing metrics, or what happens after a successful write.

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 a single, tightly written sentence with no filler. The core action is front-loaded, and the clarifying exclusion '不抓取页面' earns its place by preventing a common misuse.

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 six parameters, no output schema, and zero schema description coverage, this description is too sparse. It omits how draftId relates to the metrics, whether data is accumulated or replaced, and what the result of the operation looks like.

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 0%, so the description must compensate, but it only says 'public metrics' and does not map properties like likes, saves, views, follows, comments, or draftId to specific meanings. The parameter names are self-descriptive, but draftId's role is left entirely unexplained.

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 names a specific verb ('写入' / write), a specific resource ('本地台账' / local ledger), and a clear input class ('人工查看到的公开指标' / manually observed public metrics). The explicit qualifier '不抓取页面' distinguishes this from page-fetching or scraping tools such as check_content.

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 a clear condition: only record metrics that were manually observed, and explicitly states that this tool does not crawl pages. It does not name a specific alternative sibling to use when fetching is required, so it stops short of full guidance.

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