MyDesigns

Get deep search results

get_deep_search_results

Read-onlyIdempotent

The designs a deep_search_designs run has made, by its jobId. RUNNING: still researching or designing, which usually takes a few minutes; the designs so far are listed; check again later, not over and over. DONE: all made. In a chat that shows cards, a card shows the seller each design's image and title, so the reply there needs no pictures of its own; in a chat that shows no cards, show each design with its picture. The titles are long, search-friendly ones: shorten them for create_products if the seller wants. A design on trademarkHold has text a trademark check flagged; tell the seller before they sell it. Problems say why a niche found nothing or a design was skipped. NOT_FOUND: no deep search by that id for this seller.

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": {
      "jobId": "<jobId>"
    },
    "name": "get_deep_search_results"
  }
}

Input Schema

Name	Required	Description	Default
`jobId`	Yes	The jobId deep_search_designs returned.

Output Schema

Name	Required	Description	Default
`status`	Yes
`designs`	Yes
`jobGuid`	Yes
`problems`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 4, 2026

TDQS

A4.1/5.0

Behavior5/5

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

Beyond the readOnly/idempotent annotations, it enumerates the possible states (RUNNING, DONE, NOT_FOUND) and what each means for the caller, and calls out polling etiquette so the agent does not spam the endpoint. It also discloses two data-level behaviors an agent could not infer: trademarkHold text flagged by a trademark check, and a 'problems' explanation for empty niches or skipped designs.

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?

The purpose is front-loaded and the status-based guidance is organized as labeled fragments (RUNNING/DONE/NOT_FOUND), which scans quickly. The telegraphic style and missing articles make a couple of sentences harder to parse than necessary, but no sentence is filler.

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 shape need not be described, yet the description still explains the states and the presentation choice between card chats and non-card chats. Combined with the trademark warning and polling advice, an agent has everything needed to invoke and act on the result.

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?

There is a single parameter at 100% schema description coverage ('The jobId deep_search_designs returned'), so the schema already carries the meaning. The description reinforces the origin of the value but adds no format, constraints, or failure semantics beyond what the schema states.

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 first sentence names the specific resource (the designs a deep_search_designs run has made) and the lookup key (jobId), which cleanly separates it from the sibling that starts a run. The wording is elliptical ('The designs a deep_search_designs run has made') but an agent can still tell what it returns and how it relates to deep_search_designs.

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: on RUNNING, 'check again later, not over and over'; on DONE, everything is made; on NOT_FOUND, the id does not belong to this seller. It also routes downstream behavior (shorten titles before create_products, warn the seller about trademarkHold). It stops short of explicitly saying to call deep_search_designs first, though the jobId reference implies it.

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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