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

Annotations already declare this a read-only, idempotent, non-destructive, closed-world operation, so safety is fully covered. The description adds genuinely useful behavior beyond that: that only the most recent jobs are shown, and that payloads and results over 4000 characters are truncated to a prefix — a real constraint an agent could otherwise misinterpret as corrupt data.

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?

Three short sentences, each earning its place: what is returned, when to reach for it, and the truncation caveat. The use-case trigger is front-loaded immediately after the identification sentence, with no filler or restatement of the title.

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 an output schema present, the description doesn't need to enumerate return fields, and the truncation note plus 'most recent' scoping covers the main interpretive risk. The one residual gap is that it never says how many jobs 'most recent' spans or that paging is available, both of which live only in the schema.

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 coverage is 67% and limit/offset are already documented inline (including the 'keep paging while has_more is true' hint), so the schema does most of the work. The description adds no syntax or meaning for any parameter, and article_id — the required one — is undocumented in both places; it's only implied by 'for an article'.

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 resource (analysis/generation jobs for an article) and states what each row carries: status, payload and result. It is clear what the tool returns, but it doesn't distinguish itself from look-alike siblings such as article__optimize_log or article__score, so the agent must infer which log to pull.

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?

It gives a concrete triggering condition — 'Use this when generated content looks wrong' — which is exactly the kind of diagnostic context an agent needs. What's missing is the negative case: no statement of when another tool (e.g. article__optimize_log) is the better choice when the problem is optimization rather than generation.

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