Adversarial Review

Adversarial review — presume it broken, find where

A normal review reads code and looks for reasons to approve it. An adversarial review starts from the opposite prior: this was just built, it is presumed broken, and the job is to find where. The builder believes in their work — that belief is exactly the blind spot. So the reviewer must be incentivized to find failure, not confirm success, and must work without the builder's context so it cannot inherit the builder's assumptions.

This skill is the canonical adversarial-review protocol for ATLAS. Reach for it autonomously after building anything non-trivial, before shipping, or when handed unfamiliar code to harden.

When to use it — and which review

• Use this when you want the thing attacked: a feature you just finished, a build before delivery, a flow you suspect is fragile, an unfamiliar codebase you must trust.
• Use /code-review instead for a fast, conservative pass over a diff or PR — it statically reads the change for bugs and cleanups, scores confidence, and never runs the app. That is the right tool for routine change review.
• The line between them: /code-review reads; adversarial-review runs. This skill presumes breakage, fans out diverse hostile lenses in clean contexts, and reproduces findings against the live target before believing them. Heavier, empirical, used deliberately.
• Scale down, don't skip: for a small change one hostile reviewer is enough. Don't fan out a fleet to attack a typo fix — deliberating everything ships nothing.

The four invariants (what makes a review adversarial)

1. Presumed-broken mandate. Every reviewer gets one instruction: "this was just built and is presumed broken; find where." Never "check if it looks ok."
2. Context isolation. Reviewers run in clean contexts (separate subagents) — they get the target and the mandate, not the build's rationalizations. A separate context window is the closest thing to a genuine second opinion.
3. Empirical reproduction. A finding is a hypothesis until reproduced against the real target. Run it. A finding that can't be reproduced is an opinion, not a bug.
4. Senior triage. Reproduce before fixing, fix what's real, re-verify the fix, and name the false alarms. The report is only trustworthy if it admits what wasn't real.

How to run it

1. Frame the target and scale. Name what's under review (a diff, a feature, a running app, a whole codebase) and how to exercise it (commands to run, URLs/flows to walk, entry points). Pick reviewer count by stakes: 1 for a small change, 3–5 lenses for a feature or build.

2. Fan out hostile reviewers in clean contexts. Spawn subagents, each with the presumed-broken mandate and one lens, blind to each other. Choose lenses that fit the target — typically:

   • Correctness — edge cases, off-by-one, race conditions, broken flows, state that lies
   • Security — injection, authz/authn holes, secrets in code, unvalidated input, SSRF/path traversal
   • The empty world — first run, zero data, no config, expired token: does it still stand up?
   • Data integrity — partial writes, lost updates, migrations, constraints that don't hold
   • Failure & limits — network/dependency failure, timeouts, huge inputs, concurrent users
   • UX seams — error messages, loading/empty states, the run instructions a stranger needs (One-shot work dies at the seams and the empty world far more than the happy path — weight those.)

3. Reproduce every finding. Before fixing anything, run the target and confirm the failure actually happens. Capture the evidence (output, screenshot, failing command). Unreproducible → demote to "unconfirmed," don't fix on faith.

4. Triage like a senior. Fix what reproduced, re-run to confirm the fix closed it (and opened nothing new), and record what looked like a bug but wasn't. If a fix opens a real design fork, invoke free-will.

Output — the report

One honest summary:

• Confirmed & fixed — what broke, the reproduction, the fix, the re-verification.
• Confirmed & deferred — real but consciously not fixed now, and why (goes on the gap list).
• False alarms — flagged then disproven. Listing these is what makes the rest credible.
• Residual risk — what this pass could not exercise, and what would attack it next.

Never report "no issues found" from a read alone — that claim requires having run the lenses and reproduced nothing. Report what you actually exercised, not what you assume holds.