Workflow Skill Creator

When rules conflict, higher priority wins.

Phase Flow

Load references only when entering the phase that needs them.

Loading discipline:

• During Phase 2 recording: only load recording-guide.md. Do not load compilation or delivery docs.
• During Phase 3 compilation: only load compilation-contract.md + compilation-checklist.md. Do not load recording docs.
• Load action-registry.md or engine-runtime.md only when encountering rare actions or debugging runtime errors.

Additional references (load on demand):

• engine-runtime.md — Engine schema during Phase 3 or 4
• action-registry.md — API action parameters during Phase 2 or 3
• tools.md — CLI commands and selector fields reference

Principles

Three recording rules (walk-is-evidence, decide-before-walk, recover-by-walk) and selector discipline govern all phases. See recording-guide.md § Three Rules.

Escalation Rules

STOP and ask the user when:

• Device unreachable after 2 retries → report connection issue
• Device locked or screen off during walk → report to user, ask to unlock
• App requires login and no credentials provided → ask user for credentials
• quality-gate score < 90 after 3 evidence repair cycles → root cause needs device re-recording
• Target element never found after scrolling entire page → task may be impossible on this app version
• App crashes repeatedly during recording → app may be unstable, report to user
• Rule 3 recovery fails after 3 walks → report state mismatch, ask user to restore

Path Variables

Set both before running any command:

• $SKILL_DIR = this skill's install location (contains scripts/, references/, agents/). When loaded by an AI agent, resolve from the skill's own file path. Example: if SKILL.md is at ~/.claude/skills/workflow-skill-creator/SKILL.md, then $SKILL_DIR=~/.claude/skills/workflow-skill-creator.
• $DIR = the workspace root created by init (e.g., ./my-skill). All commands treat --dir $DIR as workspace root and access $DIR/authoring/ internally — never pass the authoring/ subdirectory as --dir.

All CLI commands use node $SKILL_DIR/scripts/skill_cli.js or node $SKILL_DIR/scripts/device_cli.js. Full command reference: tools.md.

Phase 0: Admission

User provides task + device IP. Agent resolves everything else. Full guide: admission-guide.md.

Do NOT proceed to Phase 1 until all inputs confirmed.

Phase 1: Setup

node $SKILL_DIR/scripts/skill_cli.js init --dir $DIR --name <skill-name> --task "<task>" --base-url $BASE_URL --app <pkg> --app-name "<display-name>"

All parameters come from Phase 0 resolution. init resets device to home screen, grants all permissions to the target app, and captures initial checkpoint. The first recorded step validates against this checkpoint.

If the task starts from inside the app, the first recorded step should be launch with the target package — do NOT navigate manually before recording.

Phase 2: Record

Full rules: recording-guide.md.

init → strategy → status (gives first walk command) → [ decide → walk → confirm ] × N

Strategy first: Before the first walk, analyze the task — classify each target (position vs identity vs dynamic), plan verify approach (static vs structural), determine shortest path. See recording-guide.md § Strategy.

Walk is the only device interaction during recording. All operations go through walk shortcuts: --launch, --selector, --scroll, --key. Mistakes are cheap: walk --delete-step N. Each walk returns a diff with recommended_verify and a ready-to-run next command.

Do NOT proceed to Phase 3 until all walks accepted and last step verified.

Phase 3: Compile + Review

Dispatching sub-agents: Use your platform's subagent/tool capability (e.g., Claude Code Agent tool, Codex task). Pass:

• Instructions: the content of the agent's .md file (e.g., agents/quality-reviewer.md)
• Context: "Review child skill artifacts in workspace: $DIR"
• Expected output: $DIR/authoring/quality-review.json

If your platform does not support subagents, follow the .md file yourself (self-review fallback).

compile-view → compile-plan → compile-write → quality-review → quality-gate

compile-write is fully automated — generates the complete child skill package and validates it. compile-plan is a dry-run preview. The AI does not write workflow JSON manually. Details: compilation-contract.md.

quality-review is a mandatory pipeline stage:

• Default: dispatch quality-reviewer sub-agent (isolated review, eliminates self-assessment bias)
• Fallback: if sub-agent unavailable, self-review against compilation-checklist.md. Follow the same process and output format defined in quality-reviewer.md. Write the result to $DIR/authoring/quality-review.json with "self_reviewed": true added at root level.

quality-gate expects $DIR/authoring/quality-review.json with overall_score at JSON root level:

{"verdict":"PASS","overall_score":95,"layers":{...},"fix_suggestions":[...]}

Score < 90 → Evidence Repair Loop (no device needed):

1. Read fix_suggestions from quality-review.json
2. For each issue, read the step's dump file (authoring/dumps/step{N}_after.dump.txt)
3. Fix from evidence:
   • Selector stacked unnecessary fields → confirm single field is unique in dump, repair --step N --selector
   • Dynamic data as selector (filename, timestamp) → find position or structural alternative in dump, repair --step N --selector
   • Verify only works under recording conditions → find structural proof in dump, repair --step N --verify
   • Exploration waste steps → repair --delete-step N
4. compile-write → quality-review → quality-gate
5. If still < 90 and issues marked "insufficient evidence" → re-record only those specific steps on device

Repair command: repair --dir $DIR --step N --selector '...' / --verify '...' / --delete-step N. Modifies session.json without device. See tools.md.

Phase 4: Deliver

Generate child skill package per child-skill-guide.md.

The package includes SKILL.md, assets/workflow-script.json, assets/business-spec.json, scripts/run.js, and agents/openai.yaml. The user is responsible for running and verifying the child skill on their device.