Build, run, and visualize multi-step AI generation workflows. The AI architect translates natural language descriptions into connected node graphs — chain image generation, video creation, enhancement, and editing into automated pipelines.
SkillScore74Maintained
Automatic
◆AI Engineer pack
Last verified 8/10/2026
What it changes
Passed 15 of 20 test cases with the skill, and 5 of 20 without it.
Without skill26%
With skill74%
Checks it passed that the model alone missed
Executes muapi workflow edit specifying workflow ID wf_9921.
Executes muapi workflow delete specifying workflow ID wf_999.
Executes muapi workflow execute with target workflow ID wf_334.
and 11 more in the full report
11 fixed6 passed either way6 still failing0 broke
Pass-rate lift
+48 pp
Tokens
+45%
Agent turns
0%
Response time
-57%
Model gemini-3.6-flashMeasured 8/10/2026v117 of 23 cases passed with skill · 20 comparable
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 11
Prompt
An AI agent is interacting with muapi via Model Context Protocol (MCP) tools. Which MCP tool function retrieves a workflow's node graph and definition?
What was checked, without and with the skill
Checked
Without skill
With skill
Identifies muapi_workflow_get as the MCP tool function for retrieving workflow definitions.
Missed
Passed
case-18 · gemini-3.6-flash · 8/10/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md191 lines6 filesincludes scripts
AI Workflow Builder
Chain any combination of muapi.ai generation steps into automated pipelines. The AI architect converts your plain-language description into a runnable node graph.
Prerequisites
Always ensure the muapi CLI is up-to-date before running any commands. Reinstall from source at the start of every session:
pip install --upgrade /path/to/muapi-cli
Replace /path/to/muapi-cli with the actual path to the muapi-cli directory in the workspace (the directory containing pyproject.toml).
Core Operations
Generate (generate-workflow.sh) — AI architect creates a workflow from a description
Discover (discover-workflow.sh) — Find a relevant existing workflow by natural language
Edit (generate-workflow.sh --workflow-id) — Modify an existing workflow with a prompt
Interactive Run (interactive-run.sh) — Prompt for inputs and execute a workflow
Run (run-workflow.sh) — Execute a workflow, poll node-by-node, collect outputs
CLI (muapi workflow) — Full CRUD + visualization directly from the terminal
Agent Guided Discovery & Selection
As an AI agent, you have the ability to read and understand the purpose of available workflows to select the best one for the user's task (e.g., "create a UGC video").
Discover: Fetch the catalog of available workflows and their descriptions in JSON format.
muapi workflow discover --output-json
Match (Internal Reasoning): Use your LLM capabilities to analyze the name, category, and description fields of the returned workflows. Find the best match for the user's intent.
Analyze: If you find a promising candidate, inspect its structure to ensure it has the necessary nodes and parameters.
muapi workflow get <workflow_id>
CRITICAL RULE: The output of muapi workflow get will include an "API Inputs" table. You MUST read this table to understand what inputs are required.