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

Beyond annotations, the description discloses asynchronous behavior with a specific polling workflow, the exact return shape {status:'dispatched'|'skipped', type}, the skipped condition (apiStatus not GRANTED), and the addon_required 403 error with addonCode and upsellUrl. It also clarifies that it does not alter stored values, giving a complete picture of side effects and failure modes.

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 long but every sentence carries operational value — purpose, conditions, parameter mapping, non-effects, return values, async polling, and error handling are all packed in without redundancy. The core purpose is front-loaded in the first sentence, and the supporting details are logically ordered.

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?

Given there is no output schema, the description covers the return shape, skipped semantics, asynchronous polling procedure (get_import_status, recentRuns, running:false, status 'ok'), and the required addon with a user-facing upsellUrl. It leaves no critical call-time decision unexplained.

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?

With 0% schema description coverage, the description fully compensates by explaining the 'source' enum values ('api_source' lands as api_source.<code>, 'additional_source' lands as custom_<code>) and the semantics of project_id (optional, inferred for single-project customers). This goes well beyond the bare enum and type in 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?

The description opens with a specific verb-resource pair — '(Re)run an ENRICHMENT import' — and immediately clarifies the core action: materialize previously-written source values onto products without re-sending them. This distinguishes it from sibling tools like set_api_source/set_ai_source (which write values) and get_import_status (which reads status).

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 explicitly states when to use: 'retry after an import failed or is stuck, or to apply values you wrote with apply:false', and identifies the related tools by name. It also sets a clear exclusion — 'This does NOT change the stored values' — and describes the optional project_id inference, so an agent knows exactly when to call it.

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