cross-model-review
Metadata
name: cross-model-review
version: 2.0.0
description: >
Adversarial plan review using two different AI models.
v2: Alternating mode — models swap writer/reviewer each round.
Fully autonomous loop — no human input between rounds.
Use when: building features touching auth/payments/data models,
plans that will take >1hr to implement.
NOT for: simple one-file fixes, research tasks, quick scripts.
triggers:
- "review this plan"
- "cross review"
- "challenge this"
- "is this plan solid?"
- "adversarial review"
When to Activate
Activate this skill when the user:
- Says any trigger phrase above
- Shares a plan and asks for adversarial/second-opinion review
- Asks you to "sanity check" a multi-step implementation plan
Do NOT activate for: simple fixes, one-liners, pure research tasks.
Modes
Static Mode (v1 — backward compatible)
Fixed roles: planner always writes, reviewer always reviews. Requires human to trigger each round.
Alternating Mode (v2 — recommended)
Models swap roles each round. Fully autonomous — no human input between rounds.
Flow:
- Round 1: Model A writes the plan. Model B reviews.
- Round 2: Model B rewrites (based on its own review). Model A reviews.
- Round 3: Model A rewrites (based on its own review). Model B reviews.
- ...continues alternating until both agree (reviewer says APPROVED) or max rounds hit.
Why this works:
- Each model must implement its own critique — can't nitpick without owning the fix
- The other model catches over-engineering or proportionality issues
- Natural convergence: each round addresses the other's concerns
Autonomous Orchestration (Alternating Mode)
You (the main agent) run this loop. It's fully autonomous after kickoff.
Step 1 — Save the plan and init
node review.js init \
--plan /path/to/plan.md \
--mode alternating \
--model-a "anthropic/claude-opus-4-6" \
--model-b "openai-codex/gpt-5.3-codex" \
--project-context "Brief description for reviewer calibration" \
--out /home/ubuntu/clawd/tasks/reviews
Captures workspace path from stdout.
Step 2 — The autonomous loop
while true:
step = next-step(workspace)
if step.action == "done":
break # APPROVED!
if step.action == "max-rounds":
ask user: override or manual fix
break
if step.action == "review":
spawn sub-agent with step.model, step.prompt
save response to workspace/round-N-response.json
parse-round(workspace, round, response)
continue
if step.action == "revise":
spawn sub-agent with step.model, step.prompt
save output plan to temp file
save-plan(workspace, temp file, version)
continue
Step 3 — Finalize
When the loop exits with APPROVED:
node review.js finalize --workspace <workspace>
Present: rounds taken, issues found/resolved, rubric scores, plan-final.md location.
CLI Reference
Commands:
init Create a review workspace
next-step Get next action for autonomous loop
parse-round Parse a reviewer response, update issue tracker
save-plan Save a revised plan version from writer output
finalize Generate plan-final.md, changelog.md, summary.json
status Print current workspace state
init options:
--plan <file> Path to plan file (required)
--mode <m> "static" (default) or "alternating"
--model-a <m> Model A — writes first (alternating mode, required)
--model-b <m> Model B — reviews first (alternating mode, required)
--reviewer-model <m> Reviewer model (static mode, required)
--planner-model <m> Planner model (static mode, required)
--project-context <s> Brief project context for reviewer calibration
--out <dir> Output base dir (default: tasks/reviews)
--max-rounds <n> Max rounds (default: 5 static, 8 alternating)
--token-budget <n> Token budget for context (default: 8000)
next-step options:
--workspace <dir> Path to review workspace (required)
Returns JSON: { action, model, round, prompt, planVersion, saveTo }
Actions: "review", "revise", "done", "max-rounds"
parse-round options:
--workspace <dir> Path to review workspace (required)
--round <n> Round number (required)
--response <file> Path to raw reviewer response (required)
save-plan options:
--workspace <dir> Path to review workspace (required)
--plan <file> Path to revised plan markdown (required)
--version <n> Plan version number (required)
finalize options:
--workspace <dir> Path to review workspace (required)
--override-reason <s> Reason for force-approving with open issues
--ci-force Required in non-TTY mode when overriding
status options:
--workspace <dir> Path to review workspace (required)
Exit codes:
0 Approved / OK
1 Revise / max-rounds
2 Error
Detailed Orchestration (for agent implementation)
Spawning reviewers
step = next-step(workspace) # action: "review"
response = sessions_spawn(model=step.model, task=step.prompt, timeout=120s)
# Save raw response to workspace/round-{step.round}-response.json
parse-round(workspace, step.round, response_file)
System instruction for reviewer: "You are a senior engineering reviewer. Output ONLY valid JSON matching the schema. No tool calls. No markdown fences. No preamble."
Spawning writers
step = next-step(workspace) # action: "revise"
revised_plan = sessions_spawn(model=step.model, task=step.prompt, timeout=300s)
# Save raw output as temp file
save-plan(workspace, temp_file, step.planVersion)
System instruction for writer: none needed — the prompt is self-contained.
Error handling
- Reviewer timeout/failure: retry once, then ask user
- Writer timeout/failure: retry once, then ask user
- Parse error on review JSON: re-prompt reviewer once with "Your response was not valid JSON"
- Max rounds hit: present status to user, ask for override or manual fix
Convergence
The loop converges when the reviewer says APPROVED with no open CRITICAL/HIGH blockers. The script enforces this — if reviewer says APPROVED but blockers remain, it overrides to REVISE.
Static Mode (v1 — backward compatible)
For static mode, the original orchestration from v1 still works:
Step 1 — Init
node review.js init --plan <file> --reviewer-model <m> --planner-model <m>
Step 2 — Manual loop
For each round: build reviewer prompt from template, spawn reviewer, parse-round, revise plan yourself, continue.
Step 3 — Finalize
Same as alternating mode.
Integration with coding-agent
Before dispatching any plan to coding-agent that:
- Touches auth, payments, or data models
- Has 3+ implementation steps
- The user hasn't already reviewed adversarially
Run cross-model-review first. Only proceed if exit code 0.
Notes
- Workspace persists in
tasks/reviews/ — referenceable later
issues.json tracks full lifecycle of all issuesmeta.json stores mode, models, current round, verdict, needsRevision flagnext-step is the state machine — always call it to determine what to do- Dedup warnings help catch semantic drift across rounds
- Models must be from different provider families (cross-provider enforcement)
--project-context is injected into reviewer prompts for calibration
