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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds useful content-level context beyond that: results are grouped by article, carry download URLs, and rows retain a source column naming the originating filing/tariff/docket/award/series.

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 tight sentences, front-loaded with the resource and scope, then grouping/download detail, then the filter. Nothing is padding, though the final sentence largely mirrors the schema's parameter description.

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 no output schema, the description carries the return-shape burden and does so well, explaining grouping, download URLs, and the source column. It omits only secondary details such as result ordering, pagination, or total counts.

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 100% and the single 'query' parameter is fully documented in the schema. The description restates the same filter semantics ('article slug or topic word') without adding syntax, matching rules, or examples, so it neither compensates nor detracts.

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 the concrete resource ('CSV files behind every chart Open Factory publishes'), how they are grouped (by article), and what comes with them (direct download URLs). This is specific enough to distinguish it from siblings like get_article, get_record, and search_articles, which return different 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?

It says the filter is optional and accepts an article slug or topic word, which implies how to scope results, but it never states when to reach for this tool versus get_article or search_articles. Usage is implied rather than directed.

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