adversarial-review
Forces an adversarial mindset on a plan, PRD, design, or code change — break it rather than bless it.
Skill by Arcanada-one
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/arcanada-one-adversarial-review
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: design, testing
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/adversarial-review
What's inside
- Skill name
adversarial-review- Description
- Forces an adversarial mindset on a plan, PRD, design, or code change — break it rather than bless it. Loaded at the /dr-plan checkpoint and /dr-qa.
- License
- MIT
- Instructions
- 68 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Adversarial Review — Break It Before Production Does
The default failure mode of review is confirmation: a reader who wants the
artifact to be correct finds reasons it is. This skill inverts the stance. Your
job is to construct the strongest case that the artifact is **wrong,
incomplete, or unsafe** — and only then weigh that case against its defence.
This is the *general* adversarial lens. Two sibling skills sharpen specific
axes: `edge-case-hunter` (boundary and failure inputs the artifact does not
handle) and `structure-review` (organisation, completeness, internal
contradiction). Load whichever the task calls for; this skill covers the
mindset and the whole-artifact attack.
## The core rule: "no findings" is an alarm, not an all-clear
If an adversarial pass produces zero findings, that is evidence the pass was
shallow — not that the artifact is flawless. Before you may record "no
material findings", you MUST have done at least one of:
- named the artifact's single most load-bearing assumption and tried to falsify it;
- traced one concrete failure scenario end-to-end and shown it cannot occur;
- identified what the artifact does NOT claim to handle, and confirmed that scope cut is deliberate and stated.
A clean pass with none of the above is not a pass — it is an un-run review.
## How to attack an artifact
Work outside-in. Cheap, high-yield attacks first.
1. **Attack the premise.** What must be true for this to be the right thing to
build/ship at all? If that premise is unstated or unverified, that is the
finding — everything downstream inherits it.
2. **Attack the strongest claim.** Find the sentence the artifact most depends
on ("this is idempotent", "this cannot deadlock", "the gate blocks X").
Assume it is false and look for the path that makes it false.
3. **Attack the boundaries.** Empty input, maximal input, concurrent callers,
partial failure, retry, the second run, the resumed run. (Hand off depth
here to `edge-case-hunter`.)
4. **Attack the seams.** Every interface between two components is a place
where each side assumes the other's contract. Name one assumption each side
makes that the other does not guarantee.
5. **Attack reversibility.** If this is wrong in production, how is it detected,
and how is it undone? An action that cannot be observed-wrong or rolled back
raises the bar on every finding above.
## Steelman before you dismiss
For each finding, before discarding it as "won't happen", write the one-line
scenario in which it does. A finding you cannot even phrase as a concrete
scenario is genuinely out of scope; a finding you *can* phrase but dismiss on
gut feel is a deferred incident. Record the scenario either way — it is the
audit trail for the decision.
## Output
Report findings ranked most-severe first. For each: one-sentence defect + a
concrete failure scenario (inputs/state → wrong outcome). Separate confirmed
defects from open questions. End with the single highest-leverage thing to fix.
Never soften a real finding to preserve momentum — a blocked artifact caught in
review is cheaper than a shipped one caught in production.
## When to load
- `/dr-plan` Transition Checkpoint — after "is the plan testable?", ask "what would break this plan?" before locking it.
- `/dr-qa` — as an explicit adversarial layer over the implementation, not only a conformance check.
- Any Level 3-4 design or PRD decision where a wrong call is expensive to reverse.From Arcanada-one/datarim, MIT.
More from Arcanada-one/datarim
- 0.642score
human-outcome-reporting
Arcanada-one
Explain human-facing task outcomes with requirements, evidence, honest acceptance status and read-only re-explanation, inside or outside Datarim.
SkillAFreshness: A★ 16Claude Code +9 - 0.640score
finishing-a-development-branch
Arcanada-one
Use when implementation is complete and all tests pass.
SkillAFreshness: A★ 16Claude Code +9 - 0.639score
hypothesis-validation
Arcanada-one
Use when a product decision depends on an uncertain claim and needs a bounded, falsifiable check.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
diataxis-docs
Arcanada-one
Diátaxis documentation taxonomy mandate four orthogonal categories tutorials how-to reference explanation for every Datarim-managed repo and product site
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
customer-delivery
Arcanada-one
Enforce delivery from a verbatim requirement through pre-work knowledge selection, production evidence, and disposition; excludes enabling-only closure.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
brainstorming
Arcanada-one
MUST use this before any creative work — features, components, functionality, behavior changes.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
artifact-context
Arcanada-one
Canonical conventions for native agents generating or editing Datarim artifacts, including stage headers, frontmatter, and exact contract quotations.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
compliance
Arcanada-one
Post-QA hardening — detects task type (code, docs, research, legal, content, infra) and applies the matching verification checklist before archiving.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
consilium
Arcanada-one
Assemble a panel of Datarim agents for multi-perspective analysis of decisions.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
context-window-self-clearing
Arcanada-one
Preserve Datarim task continuity while orchestrated Claude Code or Codex sessions compact or clear context at deterministic pressure thresholds.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
cron-agent-patterns
Arcanada-one
Layered timeout defense for cron-orchestrated agents calling external APIs (LLM CLI, HTTP, subprocess) — nested tiers, anti-patterns, headroom.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
ai-quality
Arcanada-one
Five pillars of AI-assisted development — decomposition, TDD, architecture-first, focused work, context.
SkillAFreshness: A★ 16Claude Code +9
Signals
- Stars
- 16
- Forks
- 1
- Open issues
- 0
- Last commit (this folder)
- Oct 4, 2026 (25 days ago)
- Last release
- Oct 22, 2026 (6 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/Arcanada-one/datarim
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from Arcanada-one
- 0.642score
human-outcome-reporting
Arcanada-one
Explain human-facing task outcomes with requirements, evidence, honest acceptance status and read-only re-explanation, inside or outside Datarim.
SkillAFreshness: A★ 16Claude Code +9 - 0.640score
finishing-a-development-branch
Arcanada-one
Use when implementation is complete and all tests pass.
SkillAFreshness: A★ 16Claude Code +9 - 0.639score
hypothesis-validation
Arcanada-one
Use when a product decision depends on an uncertain claim and needs a bounded, falsifiable check.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
compliance
Arcanada-one
Post-QA hardening — detects task type (code, docs, research, legal, content, infra) and applies the matching verification checklist before archiving.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
brainstorming
Arcanada-one
MUST use this before any creative work — features, components, functionality, behavior changes.
SkillAFreshness: A★ 16Claude Code +9 - 0.637score
artifact-context
Arcanada-one
Canonical conventions for native agents generating or editing Datarim artifacts, including stage headers, frontmatter, and exact contract quotations.
SkillAFreshness: A★ 16Claude Code +9
Cite this page
adversarial-review skill. Agent Mart. https://agentmart.dev/skills/arcanada-one-adversarial-review (last updated 2026-10-24)