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Submit Design Job (async)

submit_design_job

Start a background design-pattern selection job when the client cannot wait for a long response, returning a job ID immediately for status polling.

Instructions

Start a background design-pattern selection job and return a job_id immediately (returns in <100 ms; the job itself takes minutes). ONLY use this when the calling client cannot wait for a long response. After starting, poll get_design_status(job_id) every 10-30 s until status is 'completed', 'failed', or 'cancelled'.

Input Schema

NameRequiredDescriptionDefault
focusNoOptional focus text.
languageNoOptional target language hint.
paradigmNoOptional paradigm hint.
descriptionYesThe same description argument as select_design_patterns.
architecture_styleNoOptional architecture style hint.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare the safety profile (readOnly=false, destructive=false, idempotent=false), and the description goes well beyond them by disclosing the latency split (returns <100 ms, job takes minutes), the async lifecycle, the polling interval, and the terminal states. That is the operational context an agent needs to drive a job-based tool correctly.

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?

Three short sentences, no filler; the latency fact is front-loaded and the polling instruction follows immediately. Every clause carries information an agent would otherwise have to guess.

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 values need not be explained, and the description still covers the async pattern, latency expectation, follow-up tool, and terminal states. Nothing an agent needs in order to submit and track a job 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 coverage is 100%, with every parameter already documented in the input schema, so the baseline is 3. The description adds only one piece of meaning, that 'description' is the same argument as select_design_patterns, and says nothing about the optional hint parameters (focus, language, paradigm, architecture_style).

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 ('Start a background design-pattern selection job') plus what it returns ('job_id immediately'), and implicitly distinguishes itself from the synchronous sibling select_design_patterns. An agent can tell exactly what this tool does and what it hands back 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 Guidelines5/5

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

Gives an explicit gating condition ('ONLY use this when the calling client cannot wait for a long response') and names the follow-up tool and cadence ('poll get_design_status(job_id) every 10-30 s until status is completed/failed/cancelled'). This is exactly the when/when-not/alternative guidance the dimension rewards.

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