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adversarial-challenge

Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits.

Skill by nateslabach

IndexedMIT★ 6
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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/nateslabach-adversarial-challenge

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.

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About

Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-review.

Use cases: design, security, productivity

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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

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  • ~/.claude/skills/adversarial-challenge

What's inside

Skill name
adversarial-challenge
Description
Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-review.
License
MIT
Instructions
71 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# adversarial-challenge

Hostile **devil’s advocate** for an AI-powered workflow. Do not assume the design
is correct. Attack it; do not praise it. Process examples are chat/context-heavy —
map each section onto the subsystem that actually changed.

## Not this skill

| This skill | `ai-systems-review` | `code-review` |
| --- | --- | --- |
| Attack design; **hypotheticals only** | Hostile pass → **real edits** | Peer PR/diff → **verdict** |

**Hard rule:** Do **not** modify project files.

## Operating rules

- Setup: `git status` and `git diff` (staged + unstaged). If the tree is clean, ask which paths to review.
- Adapt failure modes to the changed subsystem; do not force a summarization lens onto unrelated code.
- No praise. No edits. Hypothetical code is for inspection only.

## Process

### 0. Setup

- Run `git status` and `git diff` (include staged). Confirm the change set before attacking.

### 1. Ruthless threat model

- Top failure modes and weird edge cases, especially:
  - Server restarts and deploys
  - Background jobs (never run, run twice, out of order)
  - LLM failures (timeouts, partial responses, malformed JSON, rate limits)
  - Token overflows and bad token estimates
  - High concurrency on the same session/resource
  - Tool/agent races, attachment failures, aborted streams
- For each: *How likely?* *User-visible impact?* *What data/context do we lose or corrupt?*

### 2. Attack the assumptions

Question assumptions including:

- When/why background work (e.g. summarization) runs: thresholds, rapid bursts, stale/missing/partial results
- “Last N messages + summary is enough”: which workflows break; interaction with tools, long tool outputs, attachments
- Infrastructure: fire-and-forget with no queue on deploys/crashes/scale-out; DB/blob always succeeding

For each assumption: argue **why unsafe**, or define **strict conditions** where it’s acceptable and the tradeoffs chosen.

### 3. Concrete code-level critiques

- Point to **specific functions/blocks** (file + function) that are risky.
- Explain **exactly why** (hidden coupling, mixed responsibilities, swallowed errors, happy-path-only).
- Be explicit: “This line is dangerous because…” / “This function will behave badly if…”

### 4. Propose stronger alternatives (no code changes)

- For highest-impact risks, describe how you would redesign/harden (minimal queue behavior, retries, better token accounting, stricter triggers, etc.).
- For each: tradeoffs (complexity, cost, latency) and why it’s better under real load/failures.
- Do **not** modify the code.

### 5. Hypothetical code for review

- Sketch **example** changes for top issues (not final edits).
- Comment with file paths/function names (e.g. `// api/chat/[sessionId]/route.ts`) and what each change solves.
- Goal: concrete, reviewable diffs the user can accept or reject.

### 6. Final verdict

- **Risk summary:** If we ship this as-is, the biggest realistic risks are: …
- **Priority list (3–5)** of hypothetical changes to consider first.

From nateslabach/skills, MIT.

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Last commit (this folder)
Sep 29, 2026 (28 days ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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adversarial-challenge skill. Agent Mart. https://agentmart.dev/skills/nateslabach-adversarial-challenge (last updated 2026-10-24)