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

Annotations indicate destructiveHint=false and readOnlyHint=false, which is neutral, but the description provides crucial behavioral detail: it is queued asynchronously on a worker and the agent must poll get_fix_opportunities fixStatuses for progress. It also clearly states a fill-only-empty policy, which is non-destructive in nature but not fully captured by annotations. This goes beyond annotations to disclose the async behavior and non-overwrite guarantee.

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 dense but highly informative 3-sentence block. It front-loads the core purpose and the four fix types immediately, then provides the critical fill-only-empty behavior, and finally the queuing/progress detail. No wasted words; every sentence earns its place, and the structure is logical for decision-making.

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 the tool is a single-parameter, mutation-style tool with no output schema, the description covers what action each fixType takes, the non-destructive fill-only behavior, and the async nature with how to track progress. It is missing explicit prerequisites (e.g., whether enrichment is required for tags or brand, or if the store must be connected), but those are likely contextually inferable from sibling tools. The core call semantics are complete.

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 input schema has one parameter, fixType, with an enum, but schema description coverage is 0%, meaning the schema does not explain the enum values. The description compensates by explicitly listing and explaining each enum value ('seo' fill empty SEO titles + meta descriptions, etc.), which is exactly the semantic meaning an agent needs. This adds significant value beyond the bare enum.

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 clearly states the verb 'Run' with the resource 'Pollen's automated catalog-wide fixes' and enumerates the four specific fix types (seo, tags, altText, brand) with concrete examples of what each does. It distinguishes itself from sibling tools like apply_description, which is about a single product description, and get_fix_opportunities, which is about listing opportunities rather than applying fixes.

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 implies when to use this tool: when you need to apply a fix that fills empty values, and it explicitly notes that values already set are never touched, which guides usage. It does not explicitly name alternatives or when-not-to-use, but the sibling list and context make it clear that get_fix_opportunities is for discovery and this is for execution. Excluding explicit alternatives is a minor gap.

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