@skeletiq/mcp

Check a queued SkeletIQ generation

get_generation_status

Read-onlyIdempotent

Check the status of a background architecture generation using its job ID, then retrieve the result with get_design when completed.

Instructions

Check a background generation started with wait: false. When status is "completed", read the result with get_design.

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": {
      "job_id": "<job_id>"
    },
    "name": "get_generation_status"
  }
}

Input Schema

Name	Required	Description	Default
`job_id`	Yes	The job_id returned by generate_architecture with wait: false.

Output Schema

Name	Required	Description	Default
`error`	Yes
`job_id`	Yes
`status`	Yes
`project_id`	Yes
`queue_state`	Yes
`refusal_code`	Yes
`architecture_id`	Yes
`clarifying_questions`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 9, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare the tool read-only, idempotent, and open-world. The description adds workflow context: it is a status checker for async jobs and it hands off to get_design upon completion. This goes beyond the annotations, though it does not describe status values beyond 'completed'.

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 with no filler; the trigger condition is front-loaded and the follow-up action is stated in the second sentence. Every word earns its place.

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 simple status-check tool with a full output schema and read-only/idempotent annotations, the description covers when to call it and what to do next. Nothing an agent needs to invoke it correctly is missing.

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 description coverage is 100%, and the job_id parameter is already documented as the value returned by generate_architecture with wait: false. The description adds no new parameter semantics, so baseline 3 applies.

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 action ('check') on a clearly scoped resource ('background generation started with wait: false') and distinguishes it from get_design, which reads the completed result. The title reinforces that it covers queued generations, so an agent can tell it apart without opening the schema.

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?

Gives the exact context for use (background generation with wait: false) and explicitly directs the agent to get_design when status is 'completed'. It does not enumerate exclusions, such as synchronous wait:true usage, but the context is unambiguous for this polling scenario.

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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