Opaal: Visual designer for multi-agent Claude Code workflows

Builder TL;DR

What Opaal is: a visual multi‑agent workflow designer for use with Claude Code and other agentic AI platforms — see the project on GitHub: https://github.com/Agravak/opaal.

Key outputs you'll produce in this tutorial: a saved .opaal project file and an exported CLAUDE.md prompt suitable for Claude Code, plus a one‑page decision table mapping agent roles to responsibilities.

Starter artifacts included: three starter templates (Code Review, Feature Build, Bug Fix) you can load and modify from the repo: https://github.com/Agravak/opaal.

Quick binary smoke test (fast checklist):

• [ ] Clone the repo and confirm the app loads (UI opens).
• [ ] Pick a starter template and open it.
• [ ] Export CLAUDE.md and save a .opaal file.

Minimal success: run the smoke test in <90 min (90 minutes is the target hands‑on duration).

Methodology note: this tutorial follows a hands‑on, iterative workflow and uses artifacts exported from the Opaal repo as the canonical inputs.

Goal and expected outcome

Goal: design a working multi‑agent orchestration for a concrete developer workflow (example: a code review pipeline) and export a production prompt for Claude Code. The project homepage is here: https://github.com/Agravak/opaal.

Expected artifacts (acceptance checklist):

• A saved my_project.opaal file.
• An exported CLAUDE.md prompt file that you can paste into a Claude Code session.
• A one‑page decision table mapping agents to responsibilities.

Acceptance criteria (numeric):

• End‑to‑end iteration (create → export → validate) completes in <90 minutes for a simple pipeline.
• Decision table assigns exactly 1 primary responsibility per agent and no more than 6 agents for a simple pipeline.
• Pilot success threshold: at least 60% of pilot users prefer the visual builder vs hand‑written prompts.

Each section below references the upstream repo: https://github.com/Agravak/opaal.

Stack and prerequisites

From the project README and repo: Opaal is described as a visual multi‑agent workflow designer; the canonical source is https://github.com/Agravak/opaal.

Developer prerequisites (checklist):

• Node.js runtime (LTS), npm or yarn installed.
• Desktop capable of running Electron builds (if you choose local dev mode).
• Access to a Claude Code runtime or workspace for prompt validation.
• Local clone of the repo: https://github.com/Agravak/opaal.

Minimum developer environment numbers:

• Node LTS (>= 16.x) recommended.
• Disk: 500 MB free for repo + node_modules.
• Templates: 3 starter templates (Code Review, Feature Build, Bug Fix) included in repo.

Sample commands to prepare your environment (bash):

# clone the Opaal repo
git clone https://github.com/Agravak/opaal.git my-opaal
cd my-opaal
# install (npm or yarn)
npm install
# start dev (Electron dev command per repo README)
npm run dev

If you cannot run the Electron app, you can inspect templates and export logic in the repo directory: https://github.com/Agravak/opaal.

Step-by-step implementation

1. Get Opaal running locally

   1. Clone the repo: git clone https://github.com/Agravak/opaal.git
   2. npm install and run the dev command (see above). Artifact: local .opaal workspace with starter templates.

2. Load a starter template

   1. Open the app and choose a template (Code Review / Feature Build / Bug Fix).
   2. Save as my_project.opaal. Artifact: saved .opaal file.

3. Customize agents (role & prompt)

   1. Add agent cards and edit role prompts.
   2. Keep agent counts modest: 2–6 agents for a simple pipeline; up to 15 for complex pipelines.
   3. Produce the decision table mapping each agent to a single responsibility.

4. Wire phases and connections

   1. Use columns/phases to represent pipeline stages; wire outputs to inputs.
   2. Validate that no connection exceeds 6 hops for predictability.

5. Bind Claude Code skills and export

   1. If Opaal auto‑detects installed Claude Code skills, bind them to agents; otherwise create a binding manifest (example below).
   2. Export CLAUDE.md and the binding config.

6. Iterate, validate, rollout plan

   1. Run the exported CLAUDE.md in a Claude Code environment and validate outputs for 10 sample inputs.
   2. Iterate until failure rate ≤ 10% on pilot samples.

Rollout / rollback plan (gates):

• Canary gate: deploy to 5% of users (or run 5 canary prompts) and monitor failure rate.
• Feature flag: enable the visual prompt in pilot accounts behind a feature flag.
• Rollback gate: if prompt failure rate > 20% or median latency > 3,000 ms over 1 minute window, immediately toggle the feature flag off and revert to previous CLAUDE.md.

Export binding manifest example (yaml):

# binding-manifest.yaml
project: my_project
export: CLAUDE.md
bindings:
  - agent: Reviewer
    skill: code-review-skill
    retries: 2
  - agent: Builder
    skill: build-skill
    timeout_ms: 30000

Reference architecture

Logical flow (high level): Canvas (phases/columns) → Agent cards → Connections → Prompt generator → CLAUDE.md → Claude Code runtime. Repo: https://github.com/Agravak/opaal.

Reference folder layout (example table):

| File / Folder | Purpose | Retention | |---|---:|---:| | templates/ | Starter templates (3) | versioned (keep last 10) | | exports/ | CLAUDE.md, binding-manifest.yaml | backups: daily, retain 30 days | | projects/ | *.opaal project files | store in git LFS for binary safety |

Storage constraints and numbers:

• Keep up to 10 exported CLAUDE.md revisions per project.
• Back up .opaal files daily; retention 30 days (or 90 days for audits).
• Limit CLAUDE.md size to 50,000 tokens (~ about 50k tokens) to avoid runtime truncation in most Claude Code deployments.

Decision table sample (short):

| Agent | Responsibility | Bound skill | |---|---|---| | Researcher | Gather context | web-scrape-skill | | Reviewer | Code review | code-review-skill | | Builder | Synthesize PR | build-skill |

All resources here are tied to the upstream repo: https://github.com/Agravak/opaal.

Founder lens: ROI and adoption path

Productivity ROI assumptions: many authors report spending 20+ minutes crafting multi‑agent prompts by hand; aim to reduce that to ≤5 minutes for template reuse, saving ~15 minutes per prompt.

Pilot plan (2–4 weeks): run a 2–4 week pilot with a small dev team (5–10 users). Track these KPIs:

• Adoption rate target: 60% within the pilot group.
• Authoring time saved: target 15 minutes per prompt (from 20+ to ≤5).
• Template reuse rate: target 4 reuses per template per month.

Monetization / ops notes:

• Track support cost: aim to keep incremental support cost < $1,000/month during initial pilot.
• Licensing review: check repo license and compliance before commercial usage — repo: https://github.com/Agravak/opaal.

Rollout gate: require pilot KPIs met (≥60% adoption and ≤10% prompt failure) before integrating exported prompts into any CI pipelines.

Failure modes and debugging

Common failure modes and debugging steps (numbers and thresholds included):

• Miswired data flow: symptom: unrelated agent output appears in next phase. Debug: reload .opaal, open decision table, and validate connections (max 6 hops). Expected fix time: median 10–30 minutes.

• Skill auto‑detect failure: symptom: binding empty for an agent. Workaround: manually edit binding-manifest.yaml and set retries: 2 and timeout_ms: 30000 as in the example above.

• Export rejected by Claude Code: symptom: immediate reject or error token > limit. Checks:

  • Ensure CLAUDE.md ≤ 50,000 tokens.
  • Run 10 test prompts; if failure rate > 20%, revert to previous export.

Debugging checklist:

• [ ] Reload .opaal file and re‑open the template.
• [ ] Validate decision table: 1 responsibility per agent.
• [ ] Export CLAUDE.md and run 10 tests; capture inputs, outputs, and latencies.
• [ ] If latency median > 3,000 ms, throttle agent parallelism or increase timeouts.

Repro steps template (for filing issues):

1. Save minimal .opaal with 2 agents.
2. Export CLAUDE.md.
3. Paste into Claude Code and run 3 test prompts.
4. Attach logs, median latencies, and failure rates.

Repo reference: https://github.com/Agravak/opaal.

Production checklist

Assumptions / Hypotheses

• Opaal is a visual designer for Claude Code orchestration (source: https://github.com/Agravak/opaal).
• Templates number and role counts (3 starter templates, up to 15 roles) are treated as workshop assumptions; validate them against the live repo before production.

Risks / Mitigations

• Risk: exported prompts exceed token limits and are rejected. Mitigation: trim instructions; target ≤ 50,000 tokens; run preflight token checks.
• Risk: auto‑binding of Claude skills fails. Mitigation: provide binding-manifest.yaml (manual mapping) and set retries: 2; timeout_ms: 30000.
• Risk: adoption stalls. Mitigation: 2–4 week pilot, measure adoption, and require ≥60% adoption before CI integration.

Next steps

• Run the smoke test in this doc within 90 minutes.
• Execute a 2–4 week pilot with 5–10 users and collect metrics (adoption rate, authoring time saved, failure rate).
• Codify CI checks: lint CLAUDE.md on push and run 10 test prompts as a gating job (canary 5% traffic; rollback if failure rate > 20% or latency median > 3,000 ms).

References and repo: https://github.com/Agravak/opaal

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