ralplan

ralplan is a skill for Claude Code, Codex from Orinks/AccessiWeather. It costs 14 tokens per session (2,368 once invoked), scanned A, original, MIT.

A shorthand command for making a detailed software plan through several reviewing roles: a planner, an architect, and a critic. They repeat the discussion until they agree on the plan.

In plain words
What is it for?
Use it to plan features, migrations, security work, production fixes, compliance-related changes, or other tasks where you want review and expanded testing plans.
Why use it?
It reduces the risk of starting complex or risky coding work with missing steps, weak design decisions, or inadequate tests.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/orinks/accessiweather/ralplan
Any agent
npx skills add Orinks/AccessiWeather --skill ralplan
Clone the repo
git clone --depth 1 https://github.com/Orinks/AccessiWeather

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ralplan

README.md
[![agentmods](https://agentmods.dev/badge/skills/orinks/accessiweather/ralplan.svg)](https://agentmods.dev/skills/orinks/accessiweather/ralplan)
Your own site
<a href="https://agentmods.dev/skills/orinks/accessiweather/ralplan"><img src="https://agentmods.dev/badge/skills/orinks/accessiweather/ralplan.svg" alt="Measured on agentmods" height="20"></a>
Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,368 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.02368
Opus 5 $0.00007 $0.01184
Sonnet 5 $0.00003 $0.00474
Haiku 4.5 $0.00001 $0.00237

Measured 4d ago against content hash 457712ad363b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ralplan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.codex/skills/ralplan/SKILL.md · 163 lines

How it starts

The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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-5.5 Guidance Alignment

Use the shared workflow guidance pattern: outcome-first framing, concise visible updates for multi-step planning, local overrides for the active workflow branch, evidence-backed planning and validation expectations, explicit stop rules, right-sized implementation/PRD shape, and automatic continuation for safe reversible steps. Ask only for material, destructive, credentialed, external-production, or preference-dependent branches.

This skill invokes the Plan skill in consensus mode:

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

The consensus workflow:

  1. Planner creates an adaptive plan (right-sized to task scope; do not default to exactly five steps) 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 the structured question UI (omx question in attached tmux; native structured input outside tmux when available) 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 the structured question UI 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

Read the full file on GitHub · 163 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 163 lines · 14 tokens per session scan A 457712ad363b

Subscribe to this mod's changes

ralplan is a skill published in the GitHub repository Orinks/AccessiWeather (24 stars, last pushed 10d ago), licensed MIT. It adds 14 tokens to every session and 2,368 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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