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openai_list_tasks

List async image tasks by filtering with task IDs, trace IDs, application ID, user ID, or time range. Returns a paginated list of tasks that were recorded with a callback URL.

Instructions

List async image tasks using batch query filters.

Returns a paginated list of async image task records. You must provide at
least one filter: ids, trace_ids, application_id, user_id, or a
created_at_min / created_at_max time window.

Note: tasks are only created when the original request included a
callback_url. Synchronous (non-callback) calls are not stored.

Use this when:
- You want to list multiple tasks at once
- You want to see all tasks for an application or user

Returns:
    JSON object with 'items' array and 'count' field.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsNoList of task IDs to retrieve.
typeNoFilter by upstream type. Options: 'images', 'images_generations', 'images_edits'.
limitNoNumber of tasks per page. Default is 12.
offsetNoPagination offset. Default is 0.
user_idNoList all tasks belonging to the specified end user.
trace_idsNoList of custom trace IDs to retrieve.
application_idNoList all tasks belonging to the specified application.
created_at_maxNoLatest task creation timestamp (Unix seconds, inclusive).
created_at_minNoEarliest task creation timestamp (Unix seconds, inclusive).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description discloses key behavioral info: tasks only created with callback_url, return format (JSON with items and count), and pagination via limit/offset. Lacks rate limit or auth details but sufficient for core behavior.

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

Conciseness5/5

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

Concise, well-structured with bullet points. First sentence fronts the purpose. Every sentence adds unique information without redundancy.

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

Completeness5/5

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

Given 9 optional parameters, no annotations, but presence of output schema, the description covers essential constraints (required filter, callback_url condition) and return format. Sufficient for an agent to use correctly.

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

Parameters4/5

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

Schema coverage is 100% so baseline is 3. Description adds value by stating the 'at least one filter' requirement and explaining callback_url context, which are not in the schema's parameter descriptions.

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

Purpose5/5

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

The description clearly states it lists async image tasks using batch query filters, with the verb 'list' and resource 'async image tasks'. It distinguishes from sibling tool openai_get_task which retrieves single tasks.

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

Usage Guidelines4/5

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

Explicitly provides 'Use this when' scenarios (listing multiple tasks, viewing all tasks for an application or user). Also notes that tasks are only stored with callback_url, implying when not to use. Could explicitly mention single-task retrieval via get_task.

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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