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by wiroai

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TypeScript

Remote

List Studio model runs

list_studio_results

Read-onlyIdempotent

List Studio model runs (images, videos, audio, text) newest first with status, output URLs, text answers, and cost to collect finished outputs or check running jobs.

Instructions

List the model runs Studio started for this key's account (images, videos, audio, text), newest first, with their status, output URLs, text answers and cost. It covers all of your Studio conversations in this key's workspace; teammates' runs are not included. Use it to collect outputs that finished after a turn ended, or to check what is still running. Each run shows when it was created and, for a model that takes a prompt, its prompt, so it can be matched to a request. These runs belong to Studio, so get_task, list_tasks, cancel_task and kill_task cannot read or stop them; poll this tool instead. It reads at most Studio's 100 most recent runs: to collect a period, pass since with limit 100, and the result says when older runs in that period may be missing. Only successful runs are charged. Read-only.

Input Schema

Name	Required	Description	Default
`limit`	No	How many recent runs to read (1-100, default 20). Filters apply after reading, so fewer can come back.
`since`	No	Only runs created at or after this time: ISO 8601 (2026-01-31T09:00:00Z) or Unix seconds.
`state`	No	Only runs in this state (default all).	all

Output Schema

Name	Required	Description	Default
`runs`	Yes
`count`	Yes
`running`	Yes
`nextAction`	No
`mayMissOlder`	No

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.4.1Nov 1, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the readOnly/idempotent annotations, it discloses the visibility boundary (this key's workspace only, teammates' runs excluded), the 100-run retention window with its truncation caveat, the ordering (newest first), and that only successful runs are charged.

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?

Dense but front-loaded: purpose and return fields first, then usage, then the sibling exclusion, then the retention caveat. No filler sentences; each one carries a distinct constraint or routing decision.

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?

An output schema exists, so return-value explanation is not required, and the description still covers scope, ordering, retention limits, and the polling alternative. Nothing an agent needs in order to call this correctly is missing.

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 parameters are already documented. The description still adds meaning the schema does not: the 100-run hard cap, the recommended 'since with limit 100' pattern for collecting a period, and the caveat that the response flags when older runs may be missing.

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?

States a specific verb and resource ('List the model runs Studio started for this key's account') and enumerates what each record contains (status, output URLs, text answers, cost). It also names the sibling tools it is not (get_task, list_tasks, cancel_task, kill_task), so an agent can distinguish it without opening schemas.

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

Usage Guidelines5/5

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

Gives explicit positive usage ('collect outputs that finished after a turn ended, or to check what is still running') and explicit negative routing ('get_task, list_tasks, cancel_task and kill_task cannot read or stop them; poll this tool instead'). It also explains why: Studio runs belong to a different subsystem.

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