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

Goes well beyond the annotations (readOnly/idempotent/non-destructive) by disclosing that the customer is identified by the API key rather than a parameter, that an empty list is a valid response, that error codes are 401 and 500, and what fields each entry carries (id, name, dataTable, startType, schedule metadata, member-scraper count). That is meaningful behavior an agent can plan around, especially the auth model and empty-result case.

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?

Well structured and front-loaded: the ownership distinction appears in the first clause, followed by Args/Returns/Examples/Error Handling. Some material is redundant — the three 'Use when' examples largely restate the usage paragraph, and the local-filter example for finding a group by name could be trimmed — but nothing is confusing or padded enough to hurt selection.

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?

No output schema exists, and the description compensates fully by describing `List<GroupDTO>` contents, the empty-list case, and the field that matters downstream (`dataTable`). Auth, error paths, and drill-down next steps are all covered, so an agent has everything needed to call it correctly on the first try.

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?

The tool takes zero parameters, so the schema carries no semantic burden and the baseline is 4. The parenthetical '(none — the customer is identified by the API key on the request.)' usefully explains the implicit scoping, though there are no actual parameters whose meaning could be enriched further.

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 (returns all groups the customer OWNS) and immediately distinguishes it from the sibling that returns groups shared TO the customer. It also defines what a group is organizationally ('level-1 organizational unit', one group per scraper) and names the `dataTable` field, so an agent understands the resource semantically, not just by name.

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 routes between alternatives: shared groups go to scrapewise_get_scraper_shared_group_list, scraper-level drill-down goes to scrapewise_get_scraper_list filtered by groupRef, and data goes to scrapewise_get_scraper_data_group. It also gives a 'Don't use when' case with a cheaper alternative, plus a recommended ordering ('list groups first, then drill in'), which is more than most definitions provide.

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