risk-gate

name	risk-gate
description	Triages a diff/PR/branch by change risk and escalates only the risky parts to deeper review. Runs a cheap deterministic scoring pass (danger paths like auth/payments/migrations, change size, blast radius, churn) to bucket changed files Low/Medium/High, then escalates only HIGH-risk files to a heavyweight separate-model review (review-board or codex-second-opinion). Use when user says "risk gate", "what's risky here", "triage this diff", "is this safe to merge", or invokes /risk-gate. This is the cheap entry point of the review ladder — start here when unsure how much review a change deserves.
user-invocable	true
argument-hint	[PR number | branch | (default: working diff)]
allowed-tools	Bash, Read, Write, Glob, Grep, Agent

Risk Gate

A triage-then-escalate conductor. Most changes are low-risk and don't need a heavyweight multi-model audit; a few are dangerous and deserve everything you've got. Risk Gate spends the expensive review only where it pays by scoring the diff cheaply first.

risk = likelihood-of-failure × impact-of-failure. The score approximates both: impact from where the change lands (auth, payments, migrations, money/LLM spend), likelihood from how much/complex the change is (churn, size, blast radius).

---

Step 1: Resolve the target & score it (cheap, deterministic)

Resolve the diff base (PR / branch / working tree — see review-board for the same resolution), then run the scorer:

python3 "${CLAUDE_PLUGIN_ROOT}/skills/risk-gate/scripts/risk_score.py" [BASE_REF]

It emits JSON: per changed file an added/removed count, a score, a bucket (high/medium/low), and the reasons that fired. The signals and their weights are documented in ${CLAUDE_PLUGIN_ROOT}/skills/risk-gate/references/risk-signals.md — read it if you need to explain or tune a score. Weights are heuristic defaults, not law: treat the buckets as a starting point and apply judgment in Step 2.

If there are no changes, stop and say so.

Step 2: Confirm the buckets (judgment pass)

The script is keyword/size based and will mis-rank some files. Skim the diff for each medium/high file and adjust:

• Promote a low/medium file to high if it touches an invariant, a security boundary, or irreversible state the keywords missed.
• Demote a high file that's a rename, comment, generated artifact, or pure test churn.

State the final bucketing and why anything moved.

Step 3: Escalate ONLY the high-risk set

• No high files → no escalation. Report the risk map, recommend a normal review, stop. (This is a valid, common outcome — don't manufacture risk.)

• Some high files → escalate just those files to deep review. Prefer, in order of availability:

  1. The review-board skill (multi-lens + Codex), scoped to the high-risk files.
  2. Else, the codex-second-opinion skill (separate-model) if the Codex CLI is present.
  3. Else, spawn your own parallel Claude lens audit over the high-risk files.

  Pass the deep reviewer only the high-risk file list so it doesn't waste the expensive run on trivia.

TEMPLATE / TUNING: the escalation threshold and which deep reviewer to call are the two knobs you'll adjust. Default threshold = any high file.

Step 4: Report

Write ./.risk-gate-out/RISK-REPORT.md:

1. Risk map — table: | File | Bucket | Score | Why |, sorted high→low.
2. Escalated — which files went to deep review and the reviewer's verdict.
3. Gate decision — one line: proceed / review-then-proceed / block until fixed.

Print the map + decision to the user.

Error handling

Scenario	Action
No changes	Stop; report empty diff.
risk_score.py errors	Surface stderr; fall back to a manual skim and say the score was unavailable.
No deep reviewer available (no review-board / Codex)	Do the Claude lens audit yourself; note reduced model diversity.
Deep review finds nothing on a high-risk file	Keep it flagged review-then-proceed; a clean deep review lowers, not erases, risk.