查看批量任务状态

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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds valuable interpretive context, such as explaining that per-worker details include actual page speed, heartbeat-confirmed PID, and memory metrics, and importantly warns that CPU ratio is normalized to whole-machine logical CPUs to avoid misreporting cumulative multi-core values as percentages. No contradictions with 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 dense but each sentence carries significant information: the first defines the overall purpose and key metrics, the second details worker-level fields and the CPU normalization caveat. It is front-loaded with the main purpose, though the sentence structure is somewhat long. Overall, appropriate for the tool's complexity.

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 presence of an output schema (so return format is already specified), the description provides supplementary interpretation and context, including the monitoring format, worker fields, and CPU calculation semantics. It covers both batch-level and worker-level aspects, making it complete for a complex monitoring tool.

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 has zero parameters and schema coverage is 100% (empty schema). With no parameters, the description does not need to add parameter details, so the baseline of 4 applies. The description appropriately focuses on outputs rather than inputs.

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 that this tool views overall batch extraction progress and enumerates specific metrics returned (book counts, timing, page counts, speed, per-worker task list). It uses a specific verb and resource scope, and its focus on batch-level plus worker-level monitoring distinguishes it from sibling tools like get_job_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?

The tool's use case is implied: it is for inspecting batch extraction progress. However, it does not explicitly state when to use this tool over alternatives like get_job_status or get_processing_history, nor does it mention any exclusions or prerequisites.

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