Ralplan (Consensus Planning Alias)

Ralplan is a shorthand alias for $plan --consensus. It triggers iterative planning with Planner, Architect, and Critic agents until consensus is reached, with RALPLAN-DR structured deliberation (short mode by default, deliberate mode for high-risk work).

Usage

$ralplan "task description"

Flags

• --interactive: Enables user prompts at key decision points (draft review in step 2 and final approval in step 6). Without this flag the workflow runs fully automated — Planner → Architect → Critic loop — and outputs the final plan without asking for confirmation.
• --deliberate: Forces deliberate mode for high-risk work. Adds pre-mortem (3 scenarios) and expanded test planning (unit/integration/e2e/observability). Without this flag, deliberate mode can still auto-enable when the request explicitly signals high risk (auth/security, migrations, destructive changes, production incidents, compliance/PII, public API breakage).

Usage with interactive mode

$ralplan --interactive "task description"

Behavior

GPT-5.4 Guidance Alignment

• Default to concise, evidence-dense progress and completion reporting unless the user or risk level requires more detail.
• Treat newer user task updates as local overrides for the active workflow branch while preserving earlier non-conflicting constraints.
• If correctness depends on additional inspection, retrieval, execution, or verification, keep using the relevant tools until the consensus-planning flow is grounded.
• Right-size implementation steps and PRD story counts to the actual scope; do not default to exactly five steps when the task is clearly smaller or larger.
• Continue through clear, low-risk, reversible next steps automatically; ask only when the next step is materially branching, destructive, or preference-dependent.

This skill invokes the Plan skill in consensus mode:

$plan --consensus <arguments>
$plan --consensus --interactive <arguments>

The consensus workflow:

1. Planner creates initial plan and a compact RALPLAN-DR summary before review:
   • Principles (3-5)
   • Decision Drivers (top 3)
   • Viable Options (>=2) with bounded pros/cons
   • If only one viable option remains, explicit invalidation rationale for alternatives
   • Deliberate mode only: pre-mortem (3 scenarios) + expanded test plan (unit/integration/e2e/observability)
2. User feedback (--interactive only): If --interactive is set, use AskUserQuestion to present the draft plan plus the Principles / Drivers / Options summary before review (Proceed to review / Request changes / Skip review). Otherwise, automatically proceed to review.
3. Architect reviews for architectural soundness and must provide the strongest steelman antithesis, at least one real tradeoff tension, and (when possible) synthesis — await completion before step 4. In deliberate mode, Architect should explicitly flag principle violations.
4. Critic evaluates against quality criteria — run only after step 3 completes. Critic must enforce principle-option consistency, fair alternatives, risk mitigation clarity, testable acceptance criteria, and concrete verification steps. In deliberate mode, Critic must reject missing/weak pre-mortem or expanded test plan.
5. Re-review loop (max 5 iterations): Any non-APPROVE Critic verdict (ITERATE or REJECT) MUST run the same full closed loop: a. Collect Architect + Critic feedback b. Revise the plan with Planner c. Return to Architect review d. Return to Critic evaluation e. Repeat this loop until Critic returns APPROVE or 5 iterations are reached f. If 5 iterations are reached without APPROVE, present the best version to the user
6. On Critic approval (--interactive only): If --interactive is set, use AskUserQuestion to present the plan with approval options (Approve and execute via ralph / Approve and implement via team / Request changes / Reject). Final plan must include ADR (Decision, Drivers, Alternatives considered, Why chosen, Consequences, Follow-ups), an explicit available-agent-types roster, concrete follow-up staffing guidance for both ralph and team, suggested reasoning levels by lane, explicit omx team / $team launch hints, and a concrete team verification path. Otherwise, output the final plan and stop.
7. (--interactive only) User chooses: Approve (ralph or team), Request changes, or Reject
8. (--interactive only) On approval: invoke $ralph for sequential execution or $team for parallel team execution with the explicit available-agent-types roster, reasoning-by-lane guidance, role/staffing allocation guidance, launch hints, and verification-path guidance from the approved plan -- never implement directly

Important: Steps 3 and 4 MUST run sequentially. Do NOT issue both agent calls in the same parallel batch. Always await the Architect result before invoking Critic.

Follow the Plan skill's full documentation for consensus mode details.

Pre-context Intake

Before consensus planning or execution handoff, ensure a grounded context snapshot exists:

1. Derive a task slug from the request.
2. Reuse the latest relevant snapshot in .omx/context/{slug}-*.md when available.
3. If none exists, create .omx/context/{slug}-{timestamp}.md (UTC YYYYMMDDTHHMMSSZ) with:
   • task statement
   • desired outcome
   • known facts/evidence
   • constraints
   • unknowns/open questions
   • likely codebase touchpoints
4. If ambiguity remains high, gather brownfield facts first. When session guidance enables USE_OMX_EXPLORE_CMD, prefer omx explore for simple read-only repository lookups with narrow, concrete prompts; otherwise use the richer normal explore path. Then run $deep-interview --quick <task> before continuing.

Do not hand off to execution modes until this intake is complete; if urgency forces progress, explicitly document the risk tradeoffs.

Pre-Execution Gate

Why the Gate Exists

Execution modes (ralph, autopilot, team, ultrawork) spin up heavy multi-agent orchestration. When launched on a vague request like "ralph improve the app", agents have no clear target — they waste cycles on scope discovery that should happen during planning, often delivering partial or misaligned work that requires rework.

The ralplan-first gate intercepts underspecified execution requests and redirects them through the ralplan consensus planning workflow. This ensures:

• Explicit scope: A PRD defines exactly what will be built
• Test specification: Acceptance criteria are testable before code is written
• Consensus: Planner, Architect, and Critic agree on the approach
• No wasted execution: Agents start with a clear, bounded task

Good vs Bad Prompts

Passes the gate (specific enough for direct execution):

• ralph fix the null check in src/hooks/bridge.ts:326
• autopilot implement issue #42
• team add validation to function processKeywordDetector
• ralph do:\n1. Add input validation\n2. Write tests\n3. Update README
• ultrawork add the user model in src/models/user.ts

Gated — redirected to ralplan (needs scoping first):

• ralph fix this
• autopilot build the app
• team improve performance
• ralph add authentication
• ultrawork make it better

Bypass the gate (when you know what you want):

• force: ralph refactor the auth module
• ! autopilot optimize everything

When the Gate Does NOT Trigger

The gate auto-passes when it detects any concrete signal. You do not need all of them — one is enough:

End-to-End Flow Example

1. User types: ralph add user authentication
2. Gate detects: execution keyword (ralph) + underspecified prompt (no files, functions, or test spec)
3. Gate redirects to ralplan with message explaining the redirect
4. Ralplan consensus runs:
   • Planner creates initial plan (which files, what auth method, what tests)
   • Architect reviews for soundness
   • Critic validates quality and testability
5. On consensus approval, user chooses execution path:
   • ralph: sequential execution with verification
   • team: parallel coordinated agents
6. Execution begins with a clear, bounded plan

Troubleshooting

Scenario Examples

Good: The user says continue after the workflow already has a clear next step. Continue the current branch of work instead of restarting or re-asking the same question.

Good: The user changes only the output shape or downstream delivery step (for example make a PR). Preserve earlier non-conflicting workflow constraints and apply the update locally.

Bad: The user says continue, and the workflow restarts discovery or stops before the missing verification/evidence is gathered.