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find_workflow

Read-onlyIdempotent

Find saved workflows that already do what you need. Describe your goal in words: model, subject, resolution, features—then get ranked matches to reuse instead of rebuilding from scratch.

Instructions

Find saved workflows that already DO what you're about to build, so reuse beats rebuilding from scratch. Describe the goal in words - model, subject, resolution, extras - e.g. "flux portrait at 1024 with a face detailer", and get back a few RANKED, compact matches: family, base model, resolution, feature tags (detailer / upscale / lora / controlnet / inpaint / img2img), and why each matched. Profiles are extracted from the saved JSON, so hand-built workflows are covered too. Returns summaries only, never full graphs - load the one you want with import_workflow(name=...). Prefer this over importing+inspecting each result of list_workflows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
intentYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnly, openWorld, and idempotent hints. The description adds meaningful behavioral context: it returns ranked compact summaries only, never full graphs, and it covers hand-built workflows by extracting profiles from saved JSON. No-match behavior is not mentioned, but that is a minor gap given the annotation coverage.

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?

The description is detailed but every sentence earns its place: purpose, query example, output shape, coverage characteristics, and the alternative tool. It is front-loaded with the key value proposition and no 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?

Given that there is an output schema, the description does not need to explain return types in detail. It covers the motivation, input guidance, output summary, safety via annotations, and the appropriate follow-up tool enough for an agent to invoke it correctly.

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 zero, so the description carries the burden. It explains the intent parameter well with an example ('flux portrait at 1024 with a face detailer') and implied fields like model/subject/resolution/extras. However, the limit parameter is not explicitly described, only vaguely implied by 'a few ranked matches.'

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 ('find') with a clear resource ('saved workflows') and a distinct purpose: reuse existing workflows instead of rebuilding. It differentiates itself from list_workflows and import_workflow by describing intent-based ranking search and by explicitly saying it returns summaries only, not full graphs.

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?

The description gives explicit when-to-use guidance: 'Prefer this over importing+inspecting each result of list_workflows.' It also explains how to formulate the intent query and points the user to import_workflow(name=...) when a full graph is needed.

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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