Imported from akillness/jeo-skills (.agent-skills/webtoon-harness/SKILL.md). Install upstream with npx skills add akillness/jeo-skills --skill webtoon-harness. Copyright stays with the author (MIT).

webtoon-harness — Webtoon Production Agent Team

Keyword: webtoon harness · make a webtoon · produce a webtoon episode · next episode · redraw panel

Respect every source site's terms, robots.txt, rate limits, and copyright when gathering trend data, and respect platform/IP rules when publishing generated webtoons.

webtoon-harness packages the revfactory/webtoon-harness Claude Code harness as an installable jeo-skills plugin. It builds one webtoon episode end to end with 27 specialized agents organized into 4 phase-rebuilt teams: research popular trends → write a dialogue-driven, high-tension, twist-every-episode scenario → render character reference sheets first → render 50+ panels per episode with in-image speech-bubble baking → run a generation–validation loop until every panel passes → assemble a vertical-scroll viewer.

Agent teams require CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1.

When to use this skill

• Produce a full webtoon episode from trend research to a finished vertical-scroll viewer
• Research webtoon trends: genre/trope momentum, platform rankings, reader reactions, hook/twist reverse-engineering
• Write a dialogue-heavy, high-tension scenario with a twist every episode and a 50+ panel beat sheet
• Render character reference sheets first (the single source of truth for cross-episode consistency)
• Batch-render 50+ panels with in-image Korean speech bubbles baked in, then validate and regenerate
• Assemble panels into a no-overlay vertical-scroll viewer and package a release
• Follow-ups: "next episode", "stronger twist", "redraw panel 23", "re-run only the visual phase"

For pure recommendation or critique ("what should I read?"), answer directly — do not run the harness.

Install (plugin)

# Install this routing skill from jeo-skills
npx skills add https://github.com/akillness/jeo-skills --skill webtoon-harness

# Scaffold the full upstream harness (27 agents + 6 skills) into your project's .claude/
bash scripts/install.sh                       # into ./ (current project)
TARGET=/path/to/project bash scripts/install.sh
GLOBAL=1 bash scripts/install.sh              # also install the skill globally (npx skills add -g)

The installer is idempotent. It clones revfactory/webtoon-harness and copies its .claude/agents/ and .claude/skills/ into the target project so Claude Code can discover the agents and the webtoon-orchestrator entry-point skill. See references/install.md.

Execution mode: phase-rebuilt agent teams

Only one team is active per session. For each phase, create a team with TeamCreate, run it, then TeamDelete before building the next phase's team. Each team leaves its artifacts under _workspace/ so the next team can pick them up with Read. Spawn every team member and Agent call with model: "opus".

The 27 agents (4 teams)

Full agent roster and outputs → references/agent-teams.md.

Workflow — 6 phases

Phase 0  Context check     — new series vs next episode; reuse world/style/continuity
Phase 1  Prep              — record brief, create _workspace/
Phase 2  Research          — 4 parallel researchers → trend-brief.md   (web data via scrapling)
Phase 3  Scenario          — high-concept → world → cast → arc → {twist, tension} → beatsheet → script_final
Phase 4  Visual            — style bible → reference sheets FIRST → shotlist+lettering → prompts
                             → 50+ panels (codex-image, batches of 5, ≤5 concurrent)
                             ⇄ panel-validator 6-axis validate–regenerate loop → validation.md
Phase 5  Assembly & QA     — no-overlay index.html (bubbles baked into panels) → qa PASS → RELEASE/ep{NN}/
Phase 6  Wrap-up           — continuity update, next-episode seed

Detailed dataflow and per-phase outputs → references/workflow.md.

Trend research via scrapling (Phase 2)

The research team gathers live data — platform rankings, serialization structure, comment-reaction patterns — and that web extraction routes through the scrapling skill, not ad-hoc browser defaults. Pick the lightest workable Scrapling mode (parser-only → HTTP fetch → JS browser → stealth) and respect each site's terms, robots.txt, rate limits, and copyright. Attach a source URL and observation date to every claim; when sources conflict, record both rather than deleting one.

See references/trend-research-scrapling.md.

Design principles

• Dialogue-driven, high-tension, twist-every-episode — minimize narration; carry tension, info, and reversals through character dialogue and action.
• 50+ panels per episode — split beats finely to match the vertical-scroll rhythm.
• Consistency first — inject reference sheet → consistency token → location token into every prompt; the validator catches md5 duplicates, abrupt background swaps, and broken Korean text.
• In-image bubble baking — speech bubbles and Korean dialogue are rendered into the panel PNG, so assembly is a pure ordered image strip with no text overlay (no double captioning).
• Audit trail — preserve every intermediate artifact under _workspace/; never delete it.

Follow-up routing

• "next episode" → Phase 0 case 2: reuse world/style/continuity, regenerate from 03_episode onward.
• "stronger twist" → partial Scenario re-run (twist-master, script-editor) → re-run affected downstream phases.
• "redraw panel N" → partial Visual re-run (prompt-smith reinforce + that panel-artist re-render + panel-validator re-check) → re-assemble.
• Repeated feedback of the same kind (2×+) → propose improving the relevant skill/agent definition (harness evolution); log the change.

Limits & error handling

References

• Agent Teams (27 agents)
• Workflow (6 phases & dataflow)
• Trend Research via scrapling
• Install / scaffold
• revfactory/webtoon-harness (MIT)
• scrapling skill · harness skill
• Agent Skills Specification