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ray_job_list

Read-only

List submitted Ray jobs with ID, status, entrypoint, and start time. Set a limit and check the truncated flag to page through complete job history.

Instructions

[READ] Submitted Ray jobs: id, status, entrypoint, start time.

Returns {"jobs": [...], "returned": N, "limit": L, "truncated": bool}. When truncated is true there are more jobs than were returned — re-run with a higher limit rather than treating the result as the whole history.

Args: target: Inference target name from config; omit for the default. limit: Maximum job rows to return. Default 100.

Input Schema

NameRequiredDescriptionDefault
limitNo
targetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, but the description adds real behavioral context: the exact return envelope keys and, importantly, the truncation semantics with an explicit corrective action. That is the kind of non-obvious trait the schema and annotations cannot convey, since there is no output schema.

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?

Front-loaded with purpose, then return shape, then the actionable truncation warning, then args — a sensible order. The Args block partly repeats defaults already present in the schema, which is minor waste in an otherwise tight description.

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?

For a 2-parameter, no-required-input, no-output-schema read tool, the description covers purpose, both parameters, the return envelope, and the truncation edge case. An agent has everything needed to call it and interpret the result 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 description coverage is 0%, so the description must carry both parameters — and it does: `target` is "Inference target name from config; omit for the default" and `limit` is the maximum rows with a default of 100. The meaning is recovered, though "from config" remains slightly vague about where that name comes from.

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 leads with a specific verb+resource ("Submitted Ray jobs") and enumerates the visible fields (id, status, entrypoint, start time), which is more than enough for an agent to know what this returns. It is implicitly distinguished from ray_job_cancel by the "[READ]" marker, but no sibling is named explicitly, keeping it just short of a 5.

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?

It gives concrete conditional guidance: omit target to use the default, and if `truncated` is true re-run with a higher limit instead of treating the result as complete. What's missing is any statement of when to pick this over adjacent tools like ray_cluster_resources or ray_dashboard_status, so there are no exclusions.

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