Skills

Kill Argument

Two-thread adversarial review: a fresh reviewer constructs the strongest 200-word...

Install

npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill kill-argument -g -a claude-code -y
Category
Engineering
Updated
4d ago
License
MIT
Context cost
Mediumabout 3,000 tokens
Runs scripts
No, instructions only

What it does

Two-thread adversarial review: a fresh reviewer constructs the strongest 200-word rejection memo, then a second fresh reviewer defends the paper point-by-point and surfaces still-unresolved critical issues. Use when user says \"kill argument\", \"adversarial review\", \"hostile review\", \"rebuttal preparation\", \"reviewer-2 simulation\", or before submitting a theory paper that has already passed standard review rounds.

Kill Argument Exercise: Adversarial Attack-Defense Review

Before each reviewer slot, follow Selectable Reviewers: resolve invocation → .aris/reviewer.json → Claude Code default (Codex MCP) with reviewer_route.py through the canonical helper resolver, preserving this slot's tier, fresh contexts, source/image inputs and deterministic gates. Codex examples/pins below apply only to backend=codex; other routes use their own first-call/reply contract. Save the route and actual returned identity; unavailable selections are REVIEW_UNAVAILABLE. Classify acceptance from actual families/completion/scope. Forward invocation reviewer/model/effort overrides to reviewer-bearing children. Generation workers are unchanged.

🔒 Do not wrap this skill in /loop, /schedule, or CronCreate. It is verdict-bearing, it produces an adversarial accept/reject verdict (attack → adjudication). Re-firing it on a wall-clock timer adds no new signal (the attack changes only when the paper changes). Schedule the external wait that precedes it, draft stable → then run this once before submission. See shared-references/external-cadence.md.

Stress-test the headline claims of a paper against the strongest possible rejection argument: $ARGUMENTS

Why This Exists

Standard score-based reviews (/research-review, /auto-paper-improvement-loop) tend to produce balanced weakness lists. Each weakness gets ~equal attention, ranked CRITICAL > MAJOR > MINOR. Empirically, this misses one specific failure mode: the single most damaging argument a reviewer would write in a rejection paragraph, the one sentence that, if a senior area chair reads it, kills the paper.

Read the whole SKILL.md on GitHub

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