List your recent bulk jobs (id, state, error class, timestamps), newest first. Useful to recover a lost job id; details via bulk_status.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max jobs to return (default 50) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears the full burden of behavior disclosure. It conveys that this is a read-only listing operation, scoped to 'your' jobs, ordered newest first, and containing specific fields. It does not discuss pagination or default limit behavior, but for a simple list tool the essential behavior is disclosed.
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?
Two concise sentences carry the purpose, returned content, ordering, use case, and pointer to an alternative. Every clause earns its place, and the most important information is front-loaded.
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 simple list tool with one optional parameter and no output schema, the description is complete: it names the returned fields, ordering, a motivating use case, and the sibling to use for more detail. Nothing essential is missing for correct invocation.
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 coverage is 100% and the only parameter, limit, is already documented with its meaning and default value. The description adds no additional parameter-level detail, so the baseline of 3 is appropriate.
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 states a specific verb ('List'), the resource ('your recent bulk jobs'), and the key fields returned (id, state, error class, timestamps), with ordering ('newest first'). It clearly differentiates from sibling bulk_status by pointing to it for detailed job info.
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 gives an explicit use case—'Useful to recover a lost job id'—and routes the agent to bulk_status for further details. It does not explicitly state when not to use this tool, but the guidance is clear enough for selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Tools are largely organized by language and action, with clear pairs like cpcl_preview/cpcl_validate and zpl_preview/zpl_validate. The ZPL analysis tools (validate, explain, compatibility, command_help) have distinct purposes, though zpl_validate and explain_zpl overlap enough to cause occasional misselection.
Most tools follow a readable {domain}_{action} pattern such as zpl_preview, bulk_submit, and template_list, but there are several deviations: verb-first names like explain_zpl and convert_zpl_dpi, plus noun phrases like zpl_command_help and barcode_png. The mixed conventions are still understandable.
At 21 tools, this sits in the 16-25 'heavy' range, above the ideal 3-15 scope. The count is defensible given four label languages plus barcode, template, bulk, and conversion workflows, but it still feels dense for an agent to navigate.
The surface covers ZPL generation, validation, preview, compatibility, and conversion, plus validation/preview for CPCL, EPL, and TSPL, along with barcode, template, bulk, and language detection features. Minor gaps exist, such as no bulk job cancellation and no compatibility/health tools for non-ZPL languages, but core workflows have no dead ends.