list_bulk_jobs

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

Annotations already signal read-only and non-destructive behavior, and the description reinforces this by explicitly saying it 'reads the SAME data as the Bulk Requests page' and that monitoring endpoints 'do not consume credits.' It adds valuable context about job status semantics, including partial_success meaning some items failed or were dropped, which goes well beyond the annotations.

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 well-structured and front-loaded: it states the primary purpose first, then use cases, then statuses, then cost behavior. Every sentence earns its place, and the user-facing example quotes make the tool's intent immediately clear without being bloated.

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 burden of explaining return-value context; it lists the key row fields, meaning of statuses, and how to drill into items or webhook logs. It also clarifies credit usage and cross-app visibility, making the tool fully usable by an agent without needing to infer missing behavior.

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 and the schema fully documents all 7 parameters. The description usefully explains output fields and status semantics, but it does not add new meaning to the parameters themselves beyond what the schema already provides.

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, concrete function: 'List the user's bulk extraction jobs with their progress,' followed by the exact row fields (operation, domain, status, counts, timestamps). It clearly separates this tool from siblings by directing users to get_bulk_job_items and get_bulk_webhook_logs for drill-down, so an agent can identify which tool to call.

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?

Usage is explicit with concrete trigger phrases: 'Use this tool when the user asks about their bulk jobs: "is my job done?", "what bulk jobs are running?", "did the DETAIL batch finish?".' It also names alternatives for follow-up actions, such as passing group_id to get_bulk_job_items or get_bulk_webhook_logs, giving clear when-to-use and when-to-route-elsewhere guidance.

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