Agent skill

Named Persona Adversarial Review

by alirezarezvani in alirezarezvani/claude-skills

Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan).

MITAuto-check passedDevelopment

Install Named Persona Adversarial Review

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill named-persona-adversarial-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alirezarezvani/claude-skills named-persona-adversarial-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/engineering-team/skills/named-persona-adversarial-review .claude/skills/named-persona-adversarial-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
named-persona-adversarial-review
GitHub stars
28k
Token cost
~2.7k tokens
SKILL.md length
1,225 words
Files
2 (incl. references)
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan).

  • Works in 4 steps: Read twice → Ground the principles first → Review (3 independent — 2 engineers + 1… → …
  • Automated review findings feel generic
  • SKILL.md covers Example Output, Problem, Attribution discipline (read… and Rules, plus 9 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Named Persona Adversarial Review is an agent skill from alirezarezvani/claude-skills. Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan). Complements abstract-role adversarial review with named, sourced perspectives. Use when automated review findings feel generic, when a PR has architectural or UX impact, or when the author wants pre-submit hardening beyond standard checks.

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/persona_principles.md`).

It sits in Development, covering Code review. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • Automated review findings feel generic
  • A PR has architectural
  • The author wants pre-submit hardening beyond standard checks

Example prompts

  • “/named-persona-adversarial-review”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Read twice
  2. Ground the principles first
  3. Review (3 independent — 2 engineers + 1 product)
  4. Synthesize & post

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Named Persona Adversarial Review loads about 2.7k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 100 tokens; SKILL.md has 1,225 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 1,225 words, ~2,717 tokens.

Download SKILL.mdSave it as .claude/skills/named-persona-adversarial-review/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
named-persona-adversarial-review
description
Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan). Complements abstract-role adversarial review with named, sourced perspectives. Use when automated review findings feel generic, when a PR has architectural or UX impact, or when the author wants pre-submit hardening beyond standard checks.

Named-Persona Adversarial Review

TL;DR: Abstract roles find abstract problems. Named engineers with documented, sourced philosophies find problems you would actually fix — as long as you cite the real principle and never invent the quote.

Triggers: "review this PR with real engineers" | "named persona review" | "philosophy-grounded review"

Example Output

CRITICAL [Torvalds]: Special-case error handling at auth.ts:47 duplicates the
  happy path. Torvalds' documented "good taste" principle: restructure so the
  special case disappears rather than adding a branch. (confidence: high — TED 2016)
WARNING  [Thompson]: parseConfig() does three unrelated things; the Unix
  "do one thing well" principle argues to split it. (confidence: high)
NOTE     [Jobs]: Error "EACCES:13" leaks an errno at the user surface; "start
  from the customer experience" argues for a human message. (confidence: high — WWDC 1997)
Verdict: CONCERNS — fix CRITICAL before merge.

Problem

Abstract adversarial review ("act as a saboteur") produces generic findings — the model imagines what a reviewer might say. This skill grounds each lens in a real, sourced engineering philosophy documented in references/persona_principles.md: what Ken Thompson actually argued about trust, what Linus actually demonstrated about good taste — not what an AI imagines.

How it differs from adversarial-reviewer: abstract roles → surface-level findings; named, sourced personas → findings anchored to a documented principle you can cite and defend.

Cost: 1 round ≈ 8-12 min. Comparable to waiting for CI.

Attribution discipline (read this first — it is the load-bearing rule)

This skill puts named, real people's principles to work. That power is also its failure mode: language models hallucinate quotes. To stay honest:

  1. Cite the principle, not a fabricated verbatim quote. Prefer paraphrasing a documented position ("Thompson's Reflections on Trusting Trust argues you can't trust code you didn't fully create") over inventing quotation marks around words the person may never have said.
  2. Attach a confidence level to every attribution — high (documented, in references/persona_principles.md with a source), moderate (widely attributed, source not pinned), low/unknown (you're inferring). Mirrors productivity/andreessen's citation discipline.
  3. If you cannot ground a persona's lens in a real source, drop that persona. A confidently-wrong quote attributed to a living engineer is worse than one fewer reviewer. Never fabricate a citation to hit the "≥1 finding" bar.
  4. The finding must stand on its own technical merit. The persona is a lens that directs attention, not the authority that makes the finding true. A real bug found "through Carmack's lens" is real because it's a bug, not because Carmack said so.

Rules

  • Ground before role-play. Anchor each persona in references/persona_principles.md (or a verifiable search) first. Ungrounded = invalid.
  • Findings stand on technical merit, with the persona's principle as the lens — see the discipline above.
  • Product persona mandatory every round. Engineers miss UX. Always include one.
  • Honesty over quantity. Don't fabricate findings or citations. Clean dimensions get reported clean (with the zero-finding burden below).
  • Zero-finding burden. "Looks fine" is only valid if you name 3+ principles the code demonstrably satisfies, and how. Non-findings are as expensive as findings.

Persona Pools

Each persona's documented principles + sources + confidence live in references/persona_principles.md.

Product (pick 1 per round — mandatory):

PersonaDocumented principleBest for
Steve JobsStart from the customer experience, work back to the techUX, onboarding
Marty CaganFall in love with the problem, not the solutionPRDs, feature specs, scope creep
Des Traynor (Intercom)The first 30 seconds decide adoptionDocs, READMEs, quick starts

Engineers (pick 2 per round):

PersonaDocumented principleBest forBlind spot
Ken ThompsonTrust boundaries; do one thing wellArchitecture, supply chain, APIUX, docs
Linus TorvaldsEliminate the special case ("good taste"); never break userspaceLogic, data structures, compatUser empathy, DX
John CarmackMeasure before you optimize; performance as craftAlgorithms, hot pathsMinimalism
Kent BeckSimple design; make it work → right → fastProcess, testabilityPerformance, security
Fred BrooksEssential vs. accidental complexitySystem design, estimationLow-level perf

Routing (which personas when):

  • Code correctness → Torvalds + Carmack + Jobs
  • Architecture / design → Thompson + Brooks + Cagan
  • Documentation / API → Thompson + Beck + Traynor
  • Performance → Carmack + Torvalds + Jobs
  • Security / supply chain → Thompson + Torvalds + Cagan
  • 1st round on any PR → Torvalds + Thompson + Jobs (broadest coverage)

Severity Levels

LevelDefinitionAction
BLOCKER2+ personas concur on a CRITICAL, or security / data-loss riskFix before any further work
CRITICALWrong result, data loss, security hole, or violated core invariantFix before merge
WARNINGFragile, misleading, or likely to cause future bugsFix, or explain if deferred
NOTEImprovement that doesn't affect correctnessOptional; record for follow-up

Promotion: NOTE → WARNING → CRITICAL → BLOCKER. Two personas independently finding the same issue promotes it one level (concurrence is signal). BLOCKER is the ceiling.

The Process

Step 0: Read twice
  1. Top-down (comprehension): what changed, and why.
  2. Bottom-up (adversarial): read function by function, last to first. Ask what each function actually guarantees vs. what its name implies, where it can fail, and what it assumes about callers. Reading bottom-up breaks the author's mental model. Multi-file → trace one end-to-end path.
Show full SKILL.md (500 more words)Show less
Step 1: Ground the principles first

For each persona, pull their documented principles from references/persona_principles.md (or search "[Name] engineering philosophy principles" and extract only sourced positions) before looking at the code, so you apply the principle rather than retrofitting one to an opinion you already formed.

Step 2: Review (3 independent — 2 engineers + 1 product)

Each persona gets: Mindset (one sentence from their principles), Priorities (3-5 criteria), Findings (each mapped to a documented principle + confidence level), or the zero-finding burden (3+ principles the code satisfies, with how).

Step 3: Synthesize & post

Merge duplicates; count concurrences; promote per the rule; flag single-lens findings (often the most interesting). Post the report as a PR comment (default) or save to .claude/review-[timestamp].md.

Integrity Check (Feynman)

"The first principle is that you must not fool yourself — and you are the easiest person to fool." — Richard Feynman, Cargo Cult Science (Caltech commencement, 1974)

After each round, ask:

  1. Would this person's documented philosophy actually direct attention here — or am I projecting?
  2. Did I cite a real, sourced principle (confidence marked), or dress generic advice in a famous name?
  3. Are my findings true on technical merit independent of the name attached?
  4. All NOTE-level? Then I'm narrating one perspective in different voices. Switch ≥2 personas and re-review.

Exit Condition

  • 1 round minimum for any PR.
  • BLOCKER/CRITICAL found → fix, then 1 re-review round.
  • CONCERNS (WARNING) → fix or accept risk, then 1 more round.
  • CLEAN on 2 consecutive rounds → done.
  • CLEAN on round 1 for a low-impact PR → done (1 round is enough).

When to Use

  • You want deeper coverage than standard automated checks alone.
  • A self-authored PR needs pre-submit hardening.
  • adversarial-reviewer findings feel generic and you want sourced specificity.
  • Reviewing methodologies or docs (product personas excel here).
  • Auth, data, architecture, or public-API changes.

When NOT to Use

  • Low-impact PR (cosmetic only, no logic change) → use adversarial-reviewer.
  • No web access AND the persona isn't covered in references/persona_principles.md → you can't ground it; don't fabricate.
  • Throwaway / prototype code.

Anti-Patterns

Inherits all from adversarial-reviewer. Plus:

Anti-PatternWhy wrong
Inventing a verbatim quote to sound authoritativeFabricated attribution to a real person. Cite the sourced principle + confidence, or drop it.
"As a senior engineer" without groundingNot a named, sourced lens. Ground first.
Same 3 personas every timeRotate per problem type — see Routing.
Product person skippedProduct catches what engineers miss.
Fabricating a finding to hit "≥1 issue"The bar is honesty, not quota. Use the zero-finding burden instead.
Skipping the integrity checkVerification without verification = rubber-stamp.
3 rounds for a trivial changeLow-impact PRs: 1 round is enough.

Cross-References


Attribution: Concept contributed by @YuhaoLin2005 (PR #866). Hardened for this repo: consolidated to one location, anti-fabrication/confidence discipline added, principles sourced in references/.

© alirezarezvani, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in engineering-team/skills/named-persona-adversarial-review of alirezarezvani/claude-skills.

  • SKILL.md
  • references/persona_principles.md

Open the folder on GitHubat commit 19392f7

Compare with similar skills

Named Persona Adversarial Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Named Persona Adversarial Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
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Code Review ChecklistshareAI-lab/learn-claude-code78k4 repos~1.1kAutomated safety check: PassMIT
Backend Code Reviewlangflow-ai/langflow155k—~3.5kAutomated safety check: NotesMIT
Mole Bug Patternstw93/Mole70k—~2kAutomated safety check: PassGPL-3.0
Backend Code Reviewlanggenius/dify158k—~676Automated safety check: PassCustom licence

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Categories

Questions about Named Persona Adversarial Review

What does Named Persona Adversarial Review do?

Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan). Named Persona Adversarial Review is an agent skill from alirezarezvani/claude-skills. Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan).

When should I use Named Persona Adversarial Review?

Named Persona Adversarial Review fits situations like: automated review findings feel generic; A PR has architectural; the author wants pre-submit hardening beyond standard checks.

How do I install Named Persona Adversarial Review in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill named-persona-adversarial-review -a claude-code`. Or copy the skill folder (engineering-team/skills/named-persona-adversarial-review in alirezarezvani/claude-skills) into .claude/skills/named-persona-adversarial-review in your project. Claude Code loads it when a task matches its description.

How do I install Named Persona Adversarial Review in Codex?

Run `npx skills add alirezarezvani/claude-skills --skill named-persona-adversarial-review -a codex`. Or copy the skill folder (engineering-team/skills/named-persona-adversarial-review in alirezarezvani/claude-skills) into .agents/skills/named-persona-adversarial-review in your project. Codex loads it when a task matches its description.

Can I use Named Persona Adversarial Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alirezarezvani/claude-skills --skill named-persona-adversarial-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/named-persona-adversarial-review, .gemini/skills/named-persona-adversarial-review, .github/skills/named-persona-adversarial-review and .opencode/skills/named-persona-adversarial-review in your project.

What does Named Persona Adversarial Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Named Persona Adversarial Review is instructions for the agent only.

Does Named Persona Adversarial Review access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Named Persona Adversarial Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Named Persona Adversarial Review use?

Named Persona Adversarial Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Named Persona Adversarial Review use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.4k tokens, read only when the agent opens those files.

What are the alternatives to Named Persona Adversarial Review?

Skills that share tags, products or a category with Named Persona Adversarial Review: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Backend Code Review (langflow-ai/langflow, 155k stars) and Mole Bug Patterns (tw93/Mole, 70k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Named Persona Adversarial Review?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,938 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

Source: alirezarezvani/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.