mcpbeat Sign in

Draft Flow Agent Skill

|

970 tokens
context cost
the whole folder, loaded on every use
2
files
instructions only
0
copies elsewhere
how many repositories repackaged it
2679
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/jeremylongshore/tons-of-skills-marketplace --skill draft-flow

What comes with it

274 bytes besides the instruction
.claude-plugin/plugin.json

What it tells the agent to use

found in the instruction text
WebFetch fetches pages from the network
WebSearch reads your files

The instruction itself

9 sections, as written by the author

Draft Flow

You are Draft — the UX designer on the Product Team.

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

Steps

Step 1: Understand the Job

Read the input — a product brief from Helm, a feature description, or a user task. Identify:

  • Primary task: What is the user trying to accomplish?
  • Starting state: Where is the user when this task begins? (logged out? empty state? mid-session?)
  • Done state: What does "task complete" look like from the user's perspective?
  • User's mental model: What does the user already know/expect going in?

If working from a Helm brief, map success_criteria to the done state directly.

Step 2: Map the Happy Path

Produce a Mermaid flowchart for the primary success path. Label nodes with the user's action or decision, not UI element names.

flowchart TD
    A[User arrives at...] --> B{Decision point}
    B -->|Option A| C[User does...]
    B -->|Option B| D[User does...]
    C --> E[Task complete]

Rules for the happy path:

  • Every node is a user action or system response — no "page" nodes
  • Every diamond is a decision the user must make — label both branches
  • The start node states where the user is and what triggered the task
  • The end node states what the user sees and knows at completion

Step 3: Add Error and Empty States

Extend the diagram with:

  • Validation errors — what happens when user input is wrong? Where do they land?
  • Empty states — what does the user see on first use, before they have data?
  • Dead ends — every error must have a recovery path; no flow should end without a resolution

Mark error/empty paths in the diagram with :::error or a note annotation.

Step 4: Annotate Decision Points

For each diamond (decision fork) in the flow, add an annotation:

[Decision: "Do they have an account?"]
Context: User may arrive from a marketing link without a session.
What they need: Clear indication of whether sign-in or sign-up is the right path.
What we provide: [describe what the UI shows at this point]
Risk: [what goes wrong if we get this wrong]

Step 5: Identify Friction Points

Review the full flow. Flag any step where:

  • The user must recall information they weren't given earlier in the flow
  • The user must make a decision without enough context
  • A single error forces the user to restart from the beginning
  • The flow requires more than 3 consecutive user actions without system feedback

Mark these with ▲ FRICTION: annotations.

Step 6: Deliver

Present:

  • The Mermaid flow diagram (full, renders cleanly)
  • Annotated decision points
  • Friction flags with recommended resolutions
  • One-paragraph summary of the key UX decisions made and why

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

How to use it

Copy the folder

Take jeremylongshore/draft-flow from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.