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Agent skill

Scenario Workflow Authoring

by scenario-labs in scenario-labs/skills

A skill your agent uses when a task involves creating or editing a Scenario workflow graph through MCP: building an app from a brief, adding or rewiring nodes (models, prompts, approval gates…

MITAuto-check passedMedia & Creative

Install Scenario Workflow Authoring

skills CLI
$ npx skills add scenario-labs/skills --skill scenario-workflow-authoring -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install scenario-labs/skills scenario-workflow-authoring --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/scenario-workflow-authoring .claude/skills/scenario-workflow-authoring && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
scenario-workflow-authoring
GitHub stars
946
Token cost
~1.9k tokens
SKILL.md length
987 words
Files
4 (incl. scripts, references)
Skills in repo
146
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when a task involves creating or editing a Scenario workflow graph through MCP: building an app from a brief, adding or rewiring nodes (models, prompts, approval gates…

  • Works in 4 steps: recommend with capability: "txt2img" and… → Author editor_info: text1 with… → workflow_create with name, editor_info,… → …
  • A task involves creating
  • SKILL.md covers Overview, Quick reference, Worked example: a… and One output per item needs a loop, plus 2 more sections
  • Runs Python scripts from its folder; calls npx

What it does

Scenario Workflow Authoring is an agent skill from scenario-labs/skills. Use when a task involves creating or editing a Scenario workflow graph through MCP: building an app from a brief, adding or rewiring nodes (models, prompts, approval gates, loops), authoring editorinfo, publishing, unpublishing or renaming, importing an exported workflow JSON, migrating a graph built in Weavy, ComfyUI, or another node tool, copying a workflow, or turning a prompt chain into an app. Running or pricing a workflow is scenario-workflows. Keywords: node graph, editorinfo, CEL.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/editor-info.md`, `references/foreign-graph-import.md` and `scripts/fetch_workflow_examples.py`).

It sits in Media & Creative, covering Diffusion and image models. It works with Model Context Protocol and ComfyUI. The repository describes itself as: Get production-ready images, video, audio, and 3D from any AI agent: skills that pick the right model, price before spending, and keep characters and brands consistent through… The licence is MIT.

When your agent uses it

  • A task involves creating
  • Editing a Scenario workflow graph through MCP: building an app from a brief
  • Rewiring nodes (models
  • Authoring editorinfo

Example prompts

  • “/scenario-workflow-authoring”

Requirements

  • Python 3
  • Node.js

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. recommend with capability: "txt2img" and the user's brief as prompt, following the scenario skill's next_step discipline, then…
  2. Author editor_info: text1 with data.isInput: true, model1 with type: "model", data.modelId and data.isOutput: true, one edge from model1's…
  3. workflow_create with name, editor_info, and inputs_definition naming text1 as a string input. The published input key is the node id…
  4. workflow_publish, then workflow_run with dry_run=true to validate and price. Fix the graph and re-publish if validation fails.

What it can do on your machine

Read from SKILL.md and the folder at commit f6f8ab7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Scenario Workflow Authoring loads about 1.9k tokens when it runs, and up to ~9.9k if it reads all its reference files. Until then it costs about 131 tokens; SKILL.md has 987 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~131
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from scenario-labs/skills at commit f6f8ab7, republished under its MIT licence (© scenario-labs). 987 words, ~1,923 tokens.

Download SKILL.mdSave it as .claude/skills/scenario-workflow-authoring/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
scenario-workflow-authoring
description
Use when a task involves creating or editing a Scenario workflow graph through MCP: building an app from a brief, adding or rewiring nodes (models, prompts, approval gates, loops), authoring editor_info, publishing, unpublishing or renaming, importing an exported workflow JSON, migrating a graph built in Weavy, ComfyUI, or another node tool, copying a workflow, or turning a prompt chain into an app. Running or pricing a workflow is scenario-workflows. Keywords: node graph, editor_info, CEL.
license
MIT

Scenario Workflow Authoring

Overview

A workflow has two representations: editor_info (the editable node graph: nodes, edges, inputKeys) and flow (the compiled runnable form). Authoring through MCP means writing the whole editor_info document: there are no per-node editing tools; every change is a read, modify, write of the full graph through workflow_create or workflow_update. Never hand-write flow: workflow_publish compiles editor_info into it and flips status to ready. Editing a ready workflow's editor_info leaves the stale flow running until you publish again.

Read references/editor-info.md before writing any graph: it holds the node type vocabulary, the node choice doctrine (when an llm node is legitimate), the edge direction rule, per-node data contracts, and a validated minimal example. Create, update, publish, copy and delete live in the tool catalog (scenario_tools_search plus the matching executor, see the scenario skill). workflows_list, workflow_get and workflow_run are direct tools: scope and dry_run go in their top-level arguments, never an executor wrapper. Running and pricing: the scenario-workflows skill. If a sibling skill named here is missing from your available skills, ask the user to install it (npx skills add scenario-labs/skills --skill <name>); unattended, proceed from tool schemas and flag the gap.

Quick reference

StepCallNotes
1. Study a graphworkflow_get on a working workflowCopy the shape, never ids
2. Model contractmodel_schema_getHandle names and required inputs
3. Authoreditor_info + inputs_definitionPer the reference file
4. Createworkflow_createNon-atomic, see below
5. Publishworkflow_publishCompiles flow, needs input+output pins
6. Validateworkflow_run with dry_run=truePrices and runs the real validator

workflow_create is two calls under the hood: a failed create may still have created a draft whose id is in the error. Recover with workflow_update on that id; re-creating duplicates. Seed step 1 with workflow_get: it returns the full graph of any workflow whose id you have, public ones included (an id or app URL the user supplies, or your own team's from workflows_list). To find a public template, use search with target="workflows", public=true, a keyword query, limit=3, and your scope; for example, query="image" with raw filter: 'status = "ready"'. Read ids from workflows, then fetch the chosen graph with workflow_get; search hits are summaries, not graph documents. Workflow search supports keyword text and filters only, so omit image and semantic options. Use workflows_list for browsing your saved workflows. scripts/fetch_workflow_examples.py bulk-exports trimmed featured-workflow graphs for maintainers (setup in its header).

Worked example: a text-to-image app

  1. recommend with capability: "txt2img" and the user's brief as prompt, following the scenario skill's next_step discipline, then model_schema_get: its input names become the model node's handle names, and its required flag marks what must be wired. Use search instead when the user names a model.
  2. Author editor_info: text1 with data.isInput: true, model1 with type: "model", data.modelId and data.isOutput: true, one edge from model1's input to text1's output (edges name the downstream node as source, see the reference), inputKeys: ["text1"].
  3. workflow_create with name, editor_info, and inputs_definition naming text1 as a string input. The published input key is the node id, which is why run inputs have names like text1.
  4. workflow_publish, then workflow_run with dry_run=true to validate and price. Fix the graph and re-publish if validation fails.
Show full SKILL.md (461 more words)Show less

One output per item needs a loop

A multiple-asset input wired straight into a generative model's reference field is one generation conditioned on every item at once: ten product shots in come back as one image blending them, not ten edits. Field names and cardinality are per model, so read them off model_schema_get (array: true marks a list), and read the field's description as well: a few utility tools take a list and return one output per item, which needs no loop. When each item needs its own result, put the model inside a forEach over the list and read the outputs from the forEachEnd (wiring in the reference's forEach section); keep the direct wiring only when the items are meant as joint references for a single output. Inside the loop the current item feeds an array field as a one-item list. forEach runs one billed model job per item, but the dry run prices one iteration whatever the list length (observed: one quote for one or two items, twice that billed for two), so multiply the quote by the item count before quoting the user.

Migrating a graph from another node tool

A pipeline exported by Weavy, ComfyUI, or another node editor does not import: only Scenario's own export round-trips. It is translated node by node, then created, published, and dry-run as above. The mapping table, member resolution, and the report the user gets are in references/foreign-graph-import.md; read it before touching such an export, since its first rule is to reduce the file to a table locally rather than paste it into the conversation.

Common mistakes

  • Writing UI palette names as node types: persisted types are the camelCase vocabulary in the reference, and every generator is type: "model".
  • Wiring edges producer to consumer: persisted edges point the other way.
  • Expecting an editor_info update to change a live app without re-publishing.
  • Retrying a failed workflow_create with a second create instead of workflow_update on the id from the error.
  • Wiring a batch of assets into one model input and expecting one output per item: that is one generation over all of them; loop with forEach.
  • Publishing with no pins: at least one data.isInput node listed in inputKeys and one data.isOutput node.
  • Gating a text node in front of a builder or model: a branch skips only the node wired to its handle, so the consumer stays pending and the job never completes. Gate the node that does the work, or use a CEL ternary for conditional prompt text, per the reference's ifElse section.
  • Double-quoted CEL literals: they evaluate but corrupt the canvas editor, single quotes only.
  • Sending workflow_id to workflow_copy: get, update, publish, run and delete take workflow_id, but copy takes source_workflow_id; the copy inherits everything verbatim and needs its own publish.

© scenario-labs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/scenario-workflow-authoring of scenario-labs/skills.

  • SKILL.md
  • references/editor-info.md
  • references/foreign-graph-import.md
  • scripts/fetch_workflow_examples.py

Open the folder on GitHubat commit f6f8ab7

Compare with similar skills

Scenario Workflow Authoring next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Scenario Workflow Authoring compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Scenario Workflow Authoring this skillscenario-labs/skills946—~1.9kAutomated safety check: PassMIT
Imageguaardvark/guaardvark257—~1.8kAutomated safety check: PassMIT
Opsguaardvark/guaardvark257—~779Automated safety check: PassMIT
ComfyUI Local DriverSlavaSexton/ComfyUI-Agent-Kit105—~12kAutomated safety check: PassApache-2.0
Comfyui Skill OpenclawHuangYuChuh/ComfyUI_Skills_OpenClaw413—~2.7kAutomated safety check: PassApache-2.0
ComfyUI Custom Node BuilderConstantineB6/comfy-pilot230—~897Automated safety check: PassMIT

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Works with

Categories

Questions about Scenario Workflow Authoring

What does Scenario Workflow Authoring do?

A skill your agent uses when a task involves creating or editing a Scenario workflow graph through MCP: building an app from a brief, adding or rewiring nodes (models, prompts, approval gates…. Scenario Workflow Authoring is an agent skill from scenario-labs/skills. Use when a task involves creating or editing a Scenario workflow graph through MCP: building an app from a brief, adding or rewiring nodes (models, prompts, approval gates, loops), authoring editorinfo, publishing, unpublishing or renaming, importing an exported workflow JSON, migrating a graph built in Weavy, ComfyUI, or another node tool, copying a workflow, or turning a prompt chain into an app.

When should I use Scenario Workflow Authoring?

Scenario Workflow Authoring fits situations like: A task involves creating; editing a Scenario workflow graph through MCP: building an app from a brief; rewiring nodes (models; authoring editorinfo.

How do I install Scenario Workflow Authoring in Claude Code?

Run `npx skills add scenario-labs/skills --skill scenario-workflow-authoring -a claude-code`. Or copy the skill folder (skills/scenario-workflow-authoring in scenario-labs/skills) into .claude/skills/scenario-workflow-authoring in your project. Claude Code loads it when a task matches its description.

How do I install Scenario Workflow Authoring in Codex?

Run `npx skills add scenario-labs/skills --skill scenario-workflow-authoring -a codex`. Or copy the skill folder (skills/scenario-workflow-authoring in scenario-labs/skills) into .agents/skills/scenario-workflow-authoring in your project. Codex loads it when a task matches its description.

Can I use Scenario Workflow Authoring in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add scenario-labs/skills --skill scenario-workflow-authoring -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scenario-workflow-authoring, .gemini/skills/scenario-workflow-authoring, .github/skills/scenario-workflow-authoring and .opencode/skills/scenario-workflow-authoring in your project.

What does Scenario Workflow Authoring need to run?

Going by SKILL.md and its folder, Scenario Workflow Authoring needs Python for the scripts in its folder and the command-line tools its instructions call (npx). Our summary lists: Python 3; Node.js.

Does Scenario Workflow Authoring access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Scenario Workflow Authoring safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Scenario Workflow Authoring use?

Scenario Workflow Authoring is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Scenario Workflow Authoring use?

About 1.9k tokens (SKILL.md is roughly 7.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8k tokens, read only when the agent opens those files.

What are the alternatives to Scenario Workflow Authoring?

Skills that share tags, products or a category with Scenario Workflow Authoring: Image (guaardvark/guaardvark, 257 stars), Ops (guaardvark/guaardvark, 257 stars), ComfyUI Local Driver (SlavaSexton/ComfyUI-Agent-Kit, 105 stars) and Comfyui Skill Openclaw (HuangYuChuh/ComfyUI_Skills_OpenClaw, 413 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scenario Workflow Authoring?

scenario-labs (a GitHub organization) maintains it in scenario-labs/skills, which has 946 GitHub stars. The repository holds 146 skills in this directory. The repository was last updated on October 10, 2026.

Source: scenario-labs/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.