Agent skill

Reviewer Architect Adversarial

by ntorga in ntorga/agent-starter-kit

Adversarial plan review — structural validation and assumption attack on grill artifacts before implementation begins.

MITAuto-check passedProduct & Project Management

Install Reviewer Architect Adversarial

skills CLI
$ npx skills add ntorga/agent-starter-kit --skill reviewer-architect-adversarial -a claude-code

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

GitHub CLI
$ gh skill install ntorga/agent-starter-kit reviewer-architect-adversarial --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/ntorga/agent-starter-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/reviewer-architect-adversarial .claude/skills/reviewer-architect-adversarial && 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
reviewer-architect-adversarial
GitHub stars
146
Token cost
~2.6k tokens
SKILL.md length
1,430 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

Adversarial plan review — structural validation and assumption attack on grill artifacts before implementation begins.

  • Works in 9 steps: Read the artifacts end-to-end. Read… → Initialize the progress file. Create… → Completeness. Answer each question with… → …
  • Product & Project Management work in your project
  • SKILL.md covers Purpose, Procedure and Guardrails
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Reviewer Architect Adversarial is an agent skill from ntorga/agent-starter-kit. Adversarial plan review — structural validation and assumption attack on grill artifacts before implementation begins.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Product & Project Management. The repository describes itself as: The scaffold for your multi-model, personalized Natural Language AI Harness (NLAH) . The licence is MIT.

When your agent uses it

  • Product & Project Management work in your project

Example prompts

  • “/reviewer-architect-adversarial”

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. Read the artifacts end-to-end. Read tree.md, plan.md, arch.md, and impl.md in .memory/plan//. Understand the design tree, acceptance…
  2. Initialize the progress file. Create .memory/reviews/review-architecture-.md and save it before proceeding
  3. Completeness. Answer each question with yes or no. A "no" is a Blocker. Write findings to the progress file under ## Findings with heading…
  4. Structural validation. Build lists from the plan, then verify each item. Write findings to the progress file under ### Structural…
  5. Coverage. Build columns and cross-reference. Write findings to the progress file under ### Coverage. Mark phase 3 as [x]. Save the file…
  6. Assumptions. Scan the plan for each pattern below. For each match, verify or flag. Write findings to the progress file under ###…
  7. Standards. Read every rule loaded in the block. For each plan section that specifies an implementation approach (library choice, pattern…
  8. Scope. Compare the original request against the plan, line by line. Write findings to the progress file under ### Scope. Mark phase 6 as…
  9. Assemble findings. Read the progress file. For each finding, verify the severity

What it can do on your machine

Read from SKILL.md and the folder at commit 851e942. 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 (its code samples are markdown).

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

  • Network

    No URLs in SKILL.md.

    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

Reviewer Architect Adversarial loads about 2.6k tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 1,430 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~37
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

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 ntorga/agent-starter-kit at commit 851e942, republished under its MIT licence (© ntorga). 1,430 words, ~2,614 tokens.

Download SKILL.mdSave it as .claude/skills/reviewer-architect-adversarial/SKILL.md (or your agent's skills folder).
name
reviewer-architect-adversarial
description
Adversarial plan review — structural validation and assumption attack on grill artifacts before implementation begins.
usedBy
reviewer
version
0.7.0
lastUpdated
2026-09-12

Purpose

A plan that survives adversarial scrutiny saves hours of rework. Code review catches bugs in what was built. This skill catches flaws in what will be built. It validates structural soundness of the grill artifacts (do referenced files and APIs exist? do the epics cover all acceptance criteria? are the epics coherent?) and attacks assumptions (where will this break? what does the plan take for granted?). Surface problems now, when the fix costs a plan revision, not a code rewrite.

Procedure

  1. Read the artifacts end-to-end. Read tree.md, plan.md, arch.md, and impl.md in .memory/plan/<feature-slug>/. Understand the design tree, acceptance criteria, directory structure, epics, information flows, methods, and tests.

  2. Initialize the progress file. Create .memory/reviews/review-architecture-<timestamp>.md and save it before proceeding:

    markdown
    # Architecture Review Progress
    
    ## Status
    - Last updated: <timestamp>
    - Overall: In Progress
    
    ## Phases
    - [ ] 1. Completeness
    - [ ] 2. Structural validation
    - [ ] 3. Coverage
    - [ ] 4. Assumptions
    - [ ] 5. Standards
    - [ ] 6. Scope
    
    ## Findings

    Do not proceed until the file exists on disk.

  3. Completeness. Answer each question with yes or no. A "no" is a Blocker. Write findings to the progress file under ## Findings with heading ### Completeness. Mark phase 1 as [x]. Save the file before proceeding.

    tree.md:

    • Does tree.md exist with a Path: line naming the selected path?
    • Is every node in tree.md marked [settled]? Any [open] node is a Blocker — the grill terminated early.
    • Does every fact in ## Facts carry a found answer? An open fact with no node depending on it is a Warning.

    plan.md:

    • Does plan.md contain a context section (2-3 sentences)?
    • Does plan.md contain an acceptance criteria section with at least one numbered criterion?
    • Is plan.md free of implementation mechanism (no file paths, function names, class names)? Technical terms that describe the product's domain are product language, not mechanism. Flag only terms that prescribe how to build, not terms that describe what the product is.
    • Clean rewrite check. Does plan.md contain zero strikethrough markup, "Revised:" annotations, "no longer" phrasing, or diff-style markers? If any are present: Blocker.

    arch.md:

    • Does arch.md contain a directory structure section?
    • Does arch.md describe layer separation?
    • Does arch.md list reference projects when applicable?

    impl.md:

    • Does impl.md contain at least one epic with a name and description?
    • Does each epic identify which acceptance criteria it delivers?
    • Does each epic list file paths to create or modify?
    • Does each epic contain method signatures for the methods it introduces?
    • Does each epic contain test specifications (Good, Bad, Ugly) for each method?
    • Does each epic contain an information flow section tracing the request path?
    • Does each epic contain an estimated LOC?
    • Does impl.md note parallelizable groups?
  4. Structural validation. Build lists from the plan, then verify each item. Write findings to the progress file under ### Structural validation. Mark phase 2 as [x]. Save the file before proceeding.

    • Information flow. Does each epic's information flow trace a complete path from user entry point through each layer to infrastructure and back? Missing layers or handoffs: Warning. Completely absent or incoherent: Blocker.
    • Method signatures. List every method signature across all epics. For each, verify the name follows the project's naming rules (responsibility-first, no tool names in signatures, compound names). Names that violate rules: Warning.
    • Reference files. Does each epic list at least one reference file? Missing: Warning.
    • Files to modify. List every existing file path the plan says to change. For each, run: test -f "path/to/file" && echo "EXISTS" || echo "MISSING". A "MISSING" is a Blocker.
    • Files to create. List every new file path the plan says to add. For each, run: test -d "$(dirname "path/to/file")" && echo "EXISTS" || echo "MISSING". A "MISSING" parent directory is a Blocker.
    • Named entities. List every function name, type name, endpoint path, or interface name the plan mentions. For each, search the codebase: grep -r "entity_name" -l (adapt file extensions to the project's languages). Zero results for an entity claimed as existing is a Blocker. Entities marked "to create" are expected to be new. Skip those.
    • Layer boundaries. If the project documents its architecture (in .context.md files, an architecture skill, or a dedicated architecture file), read it. For each file the plan touches, write which layer it belongs to. For each pair of files in different layers, write the dependency direction. If any dependency points from an inner layer to an outer layer, that is a Blocker.
    • Epic sizing. Verify each epic's estimated LOC is at or below 600 (soft cap). If it exceeds 600 but not 900: Warning. If it exceeds 900: Blocker. An epic over the cap may need splitting.
  5. Coverage. Build columns and cross-reference. Write findings to the progress file under ### Coverage. Mark phase 3 as [x]. Save the file before proceeding.

    • Column A: List each acceptance criterion from plan.md (numbered, with name).
    • Column B: List each epic in impl.md.
    • Column C: List the epic assignments (which acceptance criteria belong to which epic).
    • For each acceptance criterion in Column A, write which epic in Column B delivers it. If a criterion has no matching epic, that is a Warning (not yet delivered — expected if the feature is in progress). If a criterion is marked ✓ or ~, confirm the corresponding epic has been implemented.
    • For each epic in Column B, write which acceptance criterion it delivers. If an epic delivers no acceptance criterion, that is a Blocker (orphan work).
    • Epic assignment consistency. Cross-reference Column C against Columns A and B. Every acceptance criterion must be assigned to exactly one epic and delivered by exactly one epic. A criterion assigned to multiple epics, or assigned to an epic but delivered by a different epic, is a Warning.
    • Test cap check. For each method, count the test specs per lens (Good, Bad, Ugly). If any method has more than 1 test per lens, that is a Warning.
    • For each test specification, write which acceptance criterion it verifies. If a test verifies no criterion, that is a Warning (wasted test).
  6. Assumptions. Scan the plan for each pattern below. For each match, verify or flag. Write findings to the progress file under ### Assumptions. Mark phase 4 as [x]. Save the file before proceeding.

    • Library capability. Does the plan say a library or framework can do something? Confirm by checking the library's README, its official documentation, then its source code. Stop at the first source that answers the question. Unverified: Warning.
    • Schema existence. Does the plan reference a database table, column, index, or migration by name? Search migration files or schema definitions to confirm it exists. Zero results: Warning.
    • API contract. Does the plan reference a response field, status code, or endpoint behavior from an external or internal API? Read the handler or client code to confirm the contract matches. Unverified: Warning.
    • Environment. Does the plan reference an environment variable, config key, or infrastructure resource by name? Search config files and deployment manifests to confirm. Unverified: Warning.
  7. Standards. Read every rule loaded in the <rules> block. For each plan section that specifies an implementation approach (library choice, pattern, query style, error handling strategy, naming convention), verify the approach does not contradict any loaded rule. A contradiction is a Blocker. Write findings to the progress file under ### Standards. Mark phase 5 as [x]. Save the file before proceeding.

  8. Scope. Compare the original request against the plan, line by line. Write findings to the progress file under ### Scope. Mark phase 6 as [x]. Save the file before proceeding.

    • List each distinct thing the original request asks for. For each, find the acceptance criterion or epic that satisfies it. If no matching section exists, that is a Blocker (under-delivery).
    • List each file or abstraction the plan creates. For each, find the request sentence that motivated it. If no matching sentence exists and the plan does not explain why it is necessary, that is a Warning (scope creep).
    • Epic shippability check. Does each epic deliver user-visible value or a verifiable contract? An epic that requires a future epic to be functional at all is a Warning.
  9. Assemble findings. Read the progress file. For each finding, verify the severity:

    • Blocker — logic incoherence, missing required section, file/entity not found, architectural violation, unmet acceptance criterion. Must be fixed.
    • Warning — minor structural concern, edge case, over-specification, orphan work, epic sizing issue. Should be addressed.
    • Note — observation or question. No action required.

    Format each finding as:

    - [<section>: <check name>] Expected: <what the plan claims or requires>. Found: <what verification revealed>. Fix: <concrete action for the Architect>.

    Group findings under ### Blockers, ### Warnings, and ### Notes headings. Set Overall status to Complete. Deliver using the handoff format (follows: skills/reviewer-handoff/SKILL.md).

Show full SKILL.md (68 more words)Show less

Guardrails

  • Never approve a plan you have not verified against the codebase. Reading the plan is not enough. Check that what it references exists on disk.
  • Never flag simplicity concerns as Blockers. A plan that over-engineers is suboptimal, not broken. Simplicity issues are Warnings.
  • Never critique the plan's writing style, formatting, or structure. Only its substance. If the plan is clear enough to implement, its prose is fine.

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

Files

Just SKILL.md in skills/reviewer-architect-adversarial of ntorga/agent-starter-kit.

Open the folder on GitHubat commit 851e942

Compare with similar skills

Reviewer Architect Adversarial 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.

Reviewer Architect Adversarial compared with similar skills
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Game Changing FeaturesopenstatusHQ/data-table-filters2.3k3 repos~2.1kAutomated safety check: PassMIT
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT
Convex Create Componentspokvulcan/poker-planning1148 repos~2.6kAutomated safety check: PassMIT
Self Improving Agentfarm-fe/farm5.6k2 repos~3.3kAutomated safety check: NotesMIT

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Questions about Reviewer Architect Adversarial

What does Reviewer Architect Adversarial do?

Adversarial plan review — structural validation and assumption attack on grill artifacts before implementation begins. Reviewer Architect Adversarial is an agent skill from ntorga/agent-starter-kit. Adversarial plan review — structural validation and assumption attack on grill artifacts before implementation begins.

When should I use Reviewer Architect Adversarial?

Reviewer Architect Adversarial fits situations like: product & Project Management work in your project.

How do I install Reviewer Architect Adversarial in Claude Code?

Run `npx skills add ntorga/agent-starter-kit --skill reviewer-architect-adversarial -a claude-code`. Or copy the skill folder (skills/reviewer-architect-adversarial in ntorga/agent-starter-kit) into .claude/skills/reviewer-architect-adversarial in your project. Claude Code loads it when a task matches its description.

How do I install Reviewer Architect Adversarial in Codex?

Run `npx skills add ntorga/agent-starter-kit --skill reviewer-architect-adversarial -a codex`. Or copy the skill folder (skills/reviewer-architect-adversarial in ntorga/agent-starter-kit) into .agents/skills/reviewer-architect-adversarial in your project. Codex loads it when a task matches its description.

Can I use Reviewer Architect Adversarial 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 ntorga/agent-starter-kit --skill reviewer-architect-adversarial -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reviewer-architect-adversarial, .gemini/skills/reviewer-architect-adversarial, .github/skills/reviewer-architect-adversarial and .opencode/skills/reviewer-architect-adversarial in your project.

What does Reviewer Architect Adversarial need to run?

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

Does Reviewer Architect Adversarial access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Reviewer Architect Adversarial 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 Reviewer Architect Adversarial use?

Reviewer Architect Adversarial 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 Reviewer Architect Adversarial use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Reviewer Architect Adversarial?

Skills that share tags, products or a category with Reviewer Architect Adversarial: User Story Writer (deanpeters/Product-Manager-Skills, 7.2k stars), Game Changing Features (openstatusHQ/data-table-filters, 2.3k stars), CCPM Project Management (automazeio/ccpm, 8.4k stars) and Convex Create Component (spokvulcan/poker-planning, 114 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Reviewer Architect Adversarial?

ntorga (a GitHub user) maintains it in ntorga/agent-starter-kit, which has 146 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on September 12, 2026.

Source: ntorga/agent-starter-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.