swing-review

swing-review is a skill for Claude Code from TheStack-ai/swing-skills. It costs 114 tokens per session (2,716 once invoked), scanned A, original, MIT.

An adversarial review guide for deliberately looking for hidden flaws in code, system designs, pull requests, and important decisions. A pull request is a proposed code change awaiting review.

In plain words
What is it for?
Use it for high-stakes reviews and stress tests when you want edge cases, blind spots, and risks surfaced deliberately.
Why use it?
It challenges the strongest assumptions, separates serious problems from minor ones, and requires a possible fix or alternative for each real issue.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the swing-skills plugin — 6 skills shipped together

Good fit Use it for high-stakes reviews and stress tests when you want edge cases, blind spots, and risks surfaced deliberately.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/thestack-ai/swing-skills/swing-review
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add TheStack-ai/swing-skills --skill swing-review
Clone the repo
git clone --depth 1 https://github.com/TheStack-ai/swing-skills

Made for: Claude Code.

Or install swing-skills, the plugin that ships this one along with the rest of its 6 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for swing-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/thestack-ai/swing-skills/swing-review.svg)](https://agentmods.dev/skills/thestack-ai/swing-skills/swing-review)
Your own site
<a href="https://agentmods.dev/skills/thestack-ai/swing-skills/swing-review"><img src="https://agentmods.dev/badge/skills/thestack-ai/swing-skills/swing-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 114 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,716 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00114 $0.02716
Opus 5 $0.00057 $0.01358
Sonnet 5 $0.00023 $0.00543
Haiku 4.5 $0.00011 $0.00272

Measured 8d ago against content hash adb7f73eedd6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

swing-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/swing-review/SKILL.md · 289 lines

How it starts

The opening of the file, as written. The whole thing — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Adversarial Review

Structured Devil's Advocate analysis that surfaces hidden flaws, edge cases, and blind spots.

Rules (Absolute)

  1. Default to finding problems. Conduct rigorous analysis across all three vectors. Report every genuine issue found — do not downplay or omit real concerns. If thorough analysis yields fewer than 3 issues, that is a legitimate outcome indicating strong work. Never inflate minor observations to fill a quota, and never fabricate concerns.
  2. Attack the strongest points. Don't waste time on trivial issues. Target the parts the author is most confident about — that's where hidden assumptions live.
  3. Separate severity levels. Not all issues are equal. Clearly distinguish critical from minor.
  4. Propose alternatives. Every criticism must include a concrete alternative or mitigation.
  5. Steel-man first. Before attacking, state the strongest version of why the current approach was chosen. This prevents straw-man critiques.
  6. No ad hominem. Critique the work, not the author. Be sharp but constructive.

Ambiguous Input Handling

If the subject under review is unclear or too broad, ask one clarifying question before proceeding. Do not review a vague target. Examples of ambiguous input that should trigger a clarification question:

  • "Review my project" (which aspect? architecture? security? specific files?)
  • "Is this okay?" with no context (what is "this"?)
  • A topic so broad that a meaningful adversarial review would be unfocused

One question. Get the answer. Then proceed.

Process

Phase 1: Steel-Man

Before any criticism, articulate:

  • Why was this approach chosen? (Best possible justification)
  • What does it optimize for? (Performance? Simplicity? Time-to-market?)
  • Under what conditions is this the right choice?

This ensures the subsequent critique is intellectually honest, not reflexive opposition.

Phase 2: Adversarial Attack (3 Vectors)

Apply three independent attack vectors simultaneously:

Read the full file on GitHub · 289 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 289 lines · 114 tokens per session scan A adb7f73eedd6

Subscribe to this mod's changes

swing-review is a skill published in the GitHub repository TheStack-ai/swing-skills (40 stars, last pushed 4mo ago), licensed MIT. It adds 114 tokens to every session and 2,716 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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