💬 Sample prompts Paste any of these into Claude Code to use this skill
Review plan /adom-plan
Vet this plan vet this plan
Review specific file /adom-plan plans/my-feature.md
Stress-test stress-test the plan
Harden harden the plan
Install this skill

Paste this into Claude Code (VS Code panel, Adom editor, or terminal) to install:

Search the Adom Wiki for the skill "adom-plan — Exhaustive Plan Review" (slug: adom-plan) at https://wiki-ufypy5dpx93o.adom.cloud/wiki/skills/adom-plan and install it into my local ~/.claude/skills/adom-plan/ directory. Fetch the skill_source content from the wiki page and save it as SKILL.md. Then confirm it's installed by showing the first 5 lines.
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What is a skill? Skills are instructions that teach AI assistants like Claude Code how to perform specific tasks. The description below is loaded into the AI as context when you invoke this skill. Well-written skills make the AI significantly more effective. Like Wikipedia, anyone can improve a skill by clicking Edit AI Skill — or have your AI submit an edit on your behalf.

Description

Edit AI Skill

adom-plan — Exhaustive Plan Review

End-to-end planning pipeline: expand a sketch into a detailed plan, then stress-test it via adversarial multi-model debate. Uses ultraplan when available (harness-level deep expansion), otherwise runs a built-in Opus expansion pass. Then launches three adversarial pairs (6 agents: Opus vs Sonnet per category) arguing architecture, implementation, and security from opposite dispositions. A 7th agent red-teams the consensus. Final output is a scored, vetted plan with validation strategies, E2E testing, risk register, and prioritized action items.

Total agents: up to 8 (1 expansion + 6 debate + 1 red-team consensus).

How it works

  1. Phase 0 — Locate the plan (plan file, file path argument, or conversation context)
  2. Phase 0.5 — Expand the plan via ultraplan (if available) or built-in Opus expansion agent
  3. Phase 1 — Fetch platform context (wiki catalog, installed skills, recent commits, existing plans)
  4. Phase 2 — Launch 6 adversarial debate agents in parallel (3 pairs):
    • Architecture: Opus advocate vs Sonnet challenger
    • Implementation: Sonnet optimist vs Opus pessimist
    • Security: Sonnet auditor vs Sonnet red-team attacker
  5. Phase 3 — Red-team the consensus with one final Opus agent
  6. Phase 4 — Scored synthesis with scorecard, contested decisions, risk register, E2E strategy, and action items
  7. Phase 5 — Present summary to user

Key features

  • Adversarial pairing — two agents argue each category from opposite dispositions, surfacing disagreements a single model would self-censor
  • Multi-model diversity — Opus reasons conservatively and architecturally; Sonnet is pragmatic and detail-oriented
  • Structured scoring — 1-5 scale across Feasibility, Maintainability, Platform Leverage, Simplicity; 2+ point deltas auto-flagged
  • Platform awareness — fetches wiki catalog so agents reference real tools, not hypothetical ones
  • The 30-Day Failure Scenario — forces concrete, actionable thinking about what will actually go wrong
  • Consensus red-team — attacks the "safe" decisions everyone agrees on, because the most dangerous risks are the ones nobody flags

Invocation

/adom-plan                          # review the active plan file
/adom-plan path/to/plan.md          # review a specific file

Installation

Bundled with gallia. Available at ~/.claude/skills/adom-plan/ after install.mjs runs. The skill consists of two files:

  • SKILL.md (212 lines) — workflow, phases, synthesis format, guidelines
  • debate-prompts.md (413 lines) — all 8 agent prompt templates (read on demand during execution)

Output

The skill appends a Debate Review Summary to the plan file containing:

  • Scorecard — per-section grades (A/B/C/F) with dimensional scores
  • Consensus Decisions — verified safe items
  • Contested Decisions — where agents disagreed, with recommendations
  • Fragile Consensus — items the red-team flagged
  • Risk Register — consolidated threat table with mitigations
  • Validation & E2E Strategy — complete test plan
  • The 30-Day Failure Scenario — the most likely production failure
  • Action Items — numbered list tagged BLOCKING / RECOMMENDED / NICE-TO-HAVE

Sub-Skills
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What are Sub-Skills?

Sub-skills are community-contributed AI skill extensions for this component. They teach AI assistants about specific tools, configurators, or workflows.

Examples:

  • A manufacturer’s configuration tool for a motor controller
  • A community-written design guide for an amplifier circuit
  • An automated test/validation script for a sensor module

How to add one: Click Add Sub-Skill, provide the URL to your skill and a brief description. Submissions are reviewed by the Adom team before going live.

No sub-skills yet. Be the first to contribute one!

Recent activity

1 commit
  • 🏷
    Release v1.0.0 Drew Owens 12 days ago
    Initial publish of adom-plan skill — adversarial multi-agent plan review
0 revisions · Updated 2026-05-15 18:34:03