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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description is consistent with them. It adds useful behavioral context beyond annotations, notably that the tool is free of per-call credits and that omitting group_id scans recent deliveries across all jobs.

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 compact and well-structured: purpose, concrete use case, scoping guidance, and cost note each earn their place. It front-loads the most important information and avoids redundant restatement of the schema.

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?

For a 9-parameter, fully optional tool with no output schema, the description gives enough context to call it correctly: what it returns conceptually, when to use it, how to narrow scope, and cost implications. The schema covers the remaining parameter syntax details.

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 description coverage is 100%, so the baseline is 3. The description adds extra meaning for group_id by tying it to list_bulk_jobs and explaining the omit-to-scan-all behavior, which is not fully conveyed by the bare schema text.

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 tool checks webhook delivery logs for bulk jobs, including whether completion notifications were delivered, delivery status, and timestamps. It distinguishes itself from sibling tools like get_error_logs and list_bulk_jobs by naming the exact resource and debugging scenario.

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 gives a concrete trigger for use: when a job shows as completed but the user's system never received the webhook. It also explains the key scoping choice between group_id and scanning all jobs. However, it does not explicitly mention when not to use it or name alternatives.

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