queue-inspector-mcp

Get job

get_job

Read-only

Retrieve complete job details including payload, attempts, retry limit, last error, and timestamps from a queue.

Instructions

Fetch full detail for one job: payload, attempts, retry ceiling, last error and timestamps. Binary payloads are returned base64-encoded and flagged.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "queue": "<queue>",
      "id": "<id>"
    },
    "name": "get_job"
  }
}

Input Schema

Name	Required	Description
`id`	Yes	Job or task id.
`queue`	Yes	Queue name, as reported by list_queues.
`backend`	No	Which backend owns the queue. Optional when the queue name is unique across backends.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 8, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already provide readOnlyHint=true, and the description aligns with a read operation. The description adds behavioral context beyond annotations by noting that binary payloads are base64-encoded and flagged. No contradictions.

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?

Two sentences that are concise and front-loaded. The first sentence communicates the core purpose and visible outputs, the second adds an important detail about binary encoding. No extraneous information.

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

Completeness4/5

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

The description adequately explains what the tool returns with specific fields and handles binary payloads. Given no output schema, this is sufficient for a single-job detail retrieval. However, it could mention the return format (e.g., JSON object) for completeness.

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?

Schema coverage is 100% with clear descriptions for each parameter (id, queue, backend). The description does not add additional meaning to parameters beyond what the schema already provides, so a baseline score of 3 is appropriate.

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 uses a specific verb 'Fetch' and resource 'full detail for one job', listing specific fields (payload, attempts, retry ceiling, last error, timestamps). This clearly distinguishes it from siblings like list_jobs (list of jobs) or delete_job (delete).

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

Usage Guidelines3/5

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

The description implies usage for retrieving detailed information about a specific job but does not explicitly state when to use this tool versus alternatives like list_jobs, retry_job, or delete_job. No exclusions or prerequisites are mentioned.

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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