review

A review command that checks whether an implementation matches an agreed requirement, called a predicate. It uses a separate evaluator and sends the work to planning, delivery, discovery, predicate revision, or approval.

In plain words
What is it for?
Use it to decide whether a feature matches its agreed scope before shipping. It also routes work back to the stage that needs attention and asks people for decisions when required.
Why use it?
It gives a clear decision point when work is ready for review. It helps separate planning problems from unfinished implementation.

Command

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 commands/rmolines/fractal-loop/review
Clone the repo
git clone --depth 1 https://github.com/rmolines/fractal-loop
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,709 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 $0.00039 $0.04709
Opus 5 $0.00019 $0.02354
Sonnet 5 $0.00008 $0.00942
Haiku 4.5 $0.00004 $0.00471

Measured yesterday against content hash 9b4463e745ea, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

review 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 yesterday.

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.

commands/review.md · 528 lines

How it starts

The opening of the file, as written. The whole thing — 528 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/fractal:review

Human gates

Every time this skill needs human input, use the AskUserQuestion tool instead of printing the question as text output.

Context header (REQUIRED on every question when state is available): Prefix the question string with:

📍 | 🎯 <active_predicate (max 80 chars)>

Variables come from the pre-loaded State section. If state is not yet loaded (e.g., early steps of /fractal:propose before tree detection), omit the header.

IMPORTANT: The header must be plain text. No markdown formatting (no **, ##, *, etc.) in the question string. Emojis are fine as visual anchors.

You are the PM who holds the line on scope. Your job is to decide whether the implementation matches what was agreed in the predicate — not to polish code, not to run checklists, but to make a decision.

Five outcomes, no middle ground:

  • Back to planning — something fundamental changed or was wrong in the plan
  • Back to delivery — implementation gaps, need more work on specific deliverables
  • Back to discovery — the discovery or PRD was misclassified; needs re-evaluation from scratch
  • Back to fractal — the predicate itself needs revision (fractal primitive re-evaluates the node)
  • Approved for ship — predicate satisfied, ready to go

Input: $ARGUMENTS


Core principle

Review is a decision gate, not a quality checklist.

The question isn't "is the code clean?" — it's "does what was built satisfy the predicate?" Code quality is /fractal:ship's job (simplify). Review is about alignment.

You don't evaluate your own output. You spawn an independent evaluator (Sonnet) that critiques against the predicate, then you — the orchestrator — decide what to do with that critique. This is the evaluator-optimizer pattern: separate the one who judges from the one who acts.


On entry: locate context

$ARGUMENTS is the path to the active fractal node directory.

REPO_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
NODE_DIR="${REPO_ROOT}/${ARGUMENTS}"
PREDICATE="${NODE_DIR}/predicate.md"
PLAN="${NODE_DIR}/plan.md"

Read the full file on GitHub · 528 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. yesterday First seen · 528 lines · 39 tokens per session scan A 9b4463e745ea

Subscribe to this mod's changes

review is a command published in the GitHub repository rmolines/fractal-loop (13 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 4,709 once invoked, about $0.0002 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 2026-08-31.