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export_metadata_jsonl

Preflight and atomically export completed-image metadata as JSONL. Supports AutoTrain or extended layout for object-detection annotation workflows.

Instructions

Preflight and atomically export completed-image metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
overwriteNoWhether an existing destination may be replaced.
dataset_idYesActive dataset identifier to export.
export_modeNoAutoTrain-compatible or extended layout.autotrain
output_pathYesAuthorized destination file path.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
dataYesReport the result of a completed metadata export.
Behavior3/5

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

With no annotations provided, the description carries the full burden. It reveals key behaviors: a preflight check and atomic export. However, it does not disclose whether the operation is destructive, what permission scope is needed, what happens if the preflight fails, or the format of the output, leaving significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence. It is front-loaded with the key action and resource. While it is not verbose, it could be more informative without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the presence of an output schema and 100% parameter coverage, the description is too brief. It does not explain what 'preflight' entails, what 'atomic' means in practice (e.g., rollback behavior), or the structure of the exported metadata. For a complex export operation, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers all 4 parameters with descriptions, achieving 100% coverage. The tool description does not add any parameter-specific information beyond the schema, so it scores the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the verb 'export' and specifies the resource as 'completed-image metadata', which is clear and distinguishes from siblings like list_images or get_dataset. However, it does not explicitly mention the JSONL format, which is part of the tool name, so it could be slightly more specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives such as list_images or get_dataset. There is no mention of prerequisites, when-not-to-use, or references to sibling tools, leaving the agent to infer usage context.

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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