Spawn parallel adversarial subagents that DRIVE THE REAL SYSTEM (not reason from source) to break new code before it ships — schemas, contracts, parsers, serializers, protocols, state machines, security/redaction, freeze guards. Use as a standard step on any nontrivial feature/task once the implementation is green and BEFORE the final convergence (dootsabha) review. Each agent gets one disjoint attack surface + a "try to break X" charter; every finding is independently reproduced before it is b…
Spawn parallel adversarial subagents that DRIVE THE REAL SYSTEM (not reason from source) to break new code before it ships — schemas, contracts, parsers, serializers, protocols, state machines, security/redaction, freeze guards.
Use as a standard step on any nontrivial feature/task once the implementation is green and BEFORE the final convergence (dootsabha) review.
Each agent gets one disjoint attack surface + a "try to break X" charter; every finding is independently reproduced before it is believed, then fixed with a regression test.
Trigger phrases include "adversarial review", "try to break this", "find the bugs I missed", "harden before done", "attack this schema/parser/contract", and the shux feature-protocol adversarial step.
Similar popular skills
Related neighbors and high-traction skills in the same topics — useful to compare before installing.
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LicenseMIT
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skill mdSKILL.md3,940 B
docsSUMMARY.md771 B
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First seen on skills.sh
First recorded snapshot · 56 installs
SKILL.md
Adversarial review
Static review and design councils miss bugs that only surface when code meets real input. This does the opposite: agents whose job is to break the code by driving the real system. On shux task 078 this pattern found a shipped-blocking bug (a validator that rejected ❤️ ⚠️ emoji) that both the author and three design councils had passed over.
When
Standard step for any nontrivial feature / schema / contract / parser / serializer / protocol / state machine / security or freeze guard — after it compiles green, before the final dootsabha convergence review and before "done". Skip only for trivial or mechanical changes.
Method
Split the attack surface into 2–4 disjoint areas (e.g. round-trip &
canonicalization · the verdict/state model · the security/guard). One agent per area. Run them in parallel, in the background.
Charter each agent (template below): its ONE surface, the PROMISE to falsify,
5–10 concrete hostile inputs, and the hard rule — drive the real system; do not reason from the source alone.
Independently reproduce every finding before believing it. Agents over- and
under-claim; a confident report is a hypothesis. Turn each real defect into a failing test first.
Fix + pin. Every confirmed defect gets a fix AND a regression test (or a new
proptest-generator case) so it cannot return.
Feed forward. Record which vectors were verified clean and any out-of-scope
findings for the owning task.
Charter template
ADVERSARIAL review. Read-only; report findings, do not edit. Target: <file / surface>. Drive the REAL system — build a scratch harness with a path-dep, or run the real binary, and feed it hostile input. Do NOT reason from source alone; that is where the sharpest bugs hide. PROMISE to falsify: `<the invariant — e.g. "any real input round-trips losslessly", "exactly one canonical encoding", "masked content never leaks", "the guard cannot be bypassed">`. Attack vectors — for each, say REAL BUG or CORRECTLY HANDLED, with file:line, the exact triggering input, and whether an existing test catches it: `<5–10 concrete hostile inputs>`. Rank BLOCKER / MAJOR / MINOR. If the code is correct on an attack, say so in one line. End with a ranked defect list + a concrete failing test for the top 3.
Discipline
Real system > reasoning. The blocker on 078 came from an agent that RAN the real
VT on ❤️; static reasoning (and the author) dismissed the same vector as theoretical.
Your own self-checks are not a substitute. Expect to be wrong about your own code
— that is the entire point of the pass.
Verify before fixing. Reproduce independently; downgrade what you can't.
Anti-patterns
Overlapping charters → agents duplicate work and leave gaps. Keep areas disjoint.
"Review this file" → invites static reading. Always say drive the real system.
One mega-agent → weaker than N focused parallel ones.
Trusting a finding without an independent repro, or fixing without a regression test.