Agent skill

Roast

by notque in notque/vexjoy-agent

Constructive critique via 5 HackerNews personas with claim validation.

MITAuto-check: notesDevelopment

Install Roast

skills CLI
$ npx skills add notque/vexjoy-agent --skill roast -a claude-code

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

GitHub CLI
$ gh skill install notque/vexjoy-agent roast --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/notque/vexjoy-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research/roast .claude/skills/roast && 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
roast
GitHub stars
435
Token cost
~3.2k tokens
SKILL.md length
1,516 words
Files
2 (incl. references)
Skills in repo
61
Repo updated
First seen
Licence
MIT

At a glance

Constructive critique via 5 HackerNews personas with claim validation.

  • Works in 5 steps: ACTIVATE READ-ONLY MODE → GATHER CONTEXT → SPAWN ROASTER AGENTS (Parallel) → …
  • Development work in your project
  • SKILL.md covers Overview, Deep References, Instructions and Examples, plus 2 more sections
  • Calls git

What it does

Roast is an agent skill from notque/vexjoy-agent. Constructive critique via 5 HackerNews personas with claim validation.

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/report-template.md`).

It sits in Development. It works with Git and Bash. The repository describes itself as: VexJoy AI Agent with Jev Intelligent Routing - /do routes plain-English requests to the right specialist agent and gates the work with reviews, tests, and a learning loop. The licence is MIT.

When your agent uses it

  • Development work in your project

Example prompts

  • “/roast”

Requirements

  • Pre-approved tools (allowed-tools): Read, Glob, Grep, Bash, Task, Skill

Workflow steps

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

  1. ACTIVATE READ-ONLY MODE
  2. GATHER CONTEXT
  3. SPAWN ROASTER AGENTS (Parallel)
  4. COORDINATE (Validate Claims)
  5. SYNTHESIZE (Generate Report)

What it can do on your machine

Read from SKILL.md and the folder at commit 5218674. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • Bash
    • Task
    • Skill

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

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

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Roast loads about 3.2k tokens when it runs, and up to ~4.4k if it reads all its reference files. Until then it costs about 19 tokens; SKILL.md has 1,516 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~19
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.4k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Glob, Grep, Bash, Task, Skill

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 notque/vexjoy-agent at commit 5218674, republished under its MIT licence (© notque). 1,516 words, ~3,164 tokens.

Download SKILL.mdSave it as .claude/skills/roast/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
roast
description
Constructive critique via 5 HackerNews personas with claim validation.
allowed-tools
Read, Glob, Grep, Bash, Task, Skill
promoted_to
research
user-invocable
false
argument-hint
<target to critique>
context
fork
routing.triggers
roast code, devil's advocate, stress test idea, roast this, stress test this idea, poke holes in this
routing.category
analysis
routing.pairs_with
assessment, review

Roast: Devil's Advocate Analysis

Overview

This skill produces evidence-based constructive critique through 5 specialized HackerNews commenter personas: Skeptical Senior, Well-Actually Pedant, Enthusiastic Newcomer, Contrarian Provocateur, and Pragmatic Builder. The workflow spawns these personas in parallel, validates all claims against actual files and lines, and synthesizes findings into an improvement-focused report.

Key constraints baked into the workflow:

  • CLAUDE.md must be read and followed before analysis begins
  • Read-only mode (no Write, Edit, destructive Bash) is mandatory — enforced via read-only-ops skill invocation
  • Every claim must reference specific file:line locations and be validated against actual evidence before appearing in the final report
  • All 5 personas must complete before validation begins — no partial analysis
  • Final report must include both validated strengths and problems, prioritized by impact
  • Unvalidated claims are dismissed; unfounded critiques are shown with evidence explaining why
  • Analysis must be direct and focused — no elaborate frameworks beyond the 5-persona + validation pattern
  • Sarcasm and mockery are stripped during synthesis; technical accuracy and file references are preserved

Deep References

WhenLoadContent
Phase 5: writing the synthesized reportreferences/report-template.mdFull report template with tone transformation rules

Instructions

Phase 1: ACTIVATE READ-ONLY MODE

Goal: Establish guardrails before any analysis begins.

Call the Skill tool with read-only-ops.

skill: read-only-ops

This ensures no modifications can occur during the analysis workflow.

Allowed operations:

  • Read tool for file contents
  • Glob tool for file patterns
  • Grep tool for content search
  • Bash: ls, wc, du, git status, git log, git diff

Forbidden operations:

  • Write tool -- no file creation
  • Edit tool -- no file modification
  • Bash: rm, mv, cp, mkdir, touch, git add, git commit, git push

If read-only mode cannot be activated, stop immediately. Never proceed with unguarded analysis.

Gate: Read-only mode active. Proceed only when gate passes.

Phase 2: GATHER CONTEXT

Goal: Understand the target thoroughly before spawning critical perspectives.

Step 1: Identify target type

InputTargetAction
No argumentREADME.md + repo structureRead README, survey project layout
@file.mdSpecific fileRead that file, identify related files
DescriptionDescribed conceptSearch repo for related implementation

Step 2: Read key files

Use Read tool to examine: README.md, main documentation, key implementation files relevant to the target.

Step 3: Survey structure

Use Glob to map the landscape:

  • **/*.md for documentation coverage
  • Source code organization and entry points
  • Configuration files and dependency declarations

Step 4: Search for patterns

Use Grep to find: specific claims to verify, usage patterns, dependency references, related test files.

Step 5: Ground verbal descriptions

If user describes a concept rather than pointing to a file, search the repo for existing implementation. Critique grounded in actual code beats critique of a strawman every time. Never analyze a verbal description without confirming the code exists.

Gate: Target identified and sufficient context gathered. Proceed only when gate passes.

Phase 3: SPAWN ROASTER AGENTS (Parallel)

Goal: Launch 5 agents in parallel, each embodying a roaster persona, analyzing the target with full evidence-gathering discipline.

Launch 5 general-purpose agents in parallel via Task tool. Load the full persona specification from the corresponding agent file into each prompt.

The 5 parallel tasks:

  1. Skeptical Senior (agents/reviewer-code.md, senior lens) Focus: Sustainability, maintenance burden, long-term viability

  2. Well-Actually Pedant (agents/reviewer-code.md, pedant lens) Focus: Precision, intellectual honesty, terminological accuracy

  3. Enthusiastic Newcomer (agents/reviewer-perspectives.md, newcomer lens) Focus: Onboarding experience, documentation clarity, accessibility

  4. Contrarian Provocateur (agents/reviewer-perspectives.md, contrarian lens) Focus: Fundamental assumptions, alternative approaches

  5. Pragmatic Builder (agents/reviewer-domain.md, pragmatic-builder lens) Focus: Production readiness, operational concerns

Each agent must:

  • Call the Skill tool with read-only-ops. Do this first to enforce no-modification guardrails.
  • Follow their systematic 5-step review process
  • Tag ALL claims as [CLAIM-N] with specific file:line references
  • Provide concrete evidence for every claim — vague critiques are worthless and must be rejected during validation
  • Search for actual implementation details rather than analyzing verbal descriptions

Agent prompt template: Tell each agent its persona name, role, target, and these requirements: (1) call read-only-ops first, (2) follow their systematic 5-step review process, (3) tag ALL claims as [CLAIM-N] with file:line references, (4) provide specific evidence for every claim. Load the appropriate reviewer agent file for each persona's lens.

CRITICAL: Wait for all 5 agents to complete before proceeding to Phase 4. Do not begin validation on partial results. Every persona must contribute before synthesis can happen.

Gate: All 5 agents complete with tagged claims. Proceed only when gate passes.

Phase 4: COORDINATE (Validate Claims)

Goal: Verify every [CLAIM-N] against actual evidence before including in the report.

Collect and validate every [CLAIM-N] from all 5 agents.

Step 1: Collect all claims

Extract every [CLAIM-N] tag from all 5 agent outputs. For each, track:

  • Claim ID and text
  • Source persona (Senior, Pedant, Newcomer, Contrarian, Builder)
  • Referenced file:line location

Step 2: Validate each claim

For each [CLAIM-N], read the referenced file/line using Read tool and assign a verdict:

VerdictMeaningCriteria
VALIDClaim is accurateEvidence directly supports it
PARTIALOverstated but has meritSome truth, some exaggeration
UNFOUNDEDNot supportedEvidence contradicts or doesn't exist
SUBJECTIVEOpinion, can't verifyMatter of preference/style

Critical: You must read the file and check the line. Visual inspection misses nuance. "Obviously valid" is a rationalization word. Do not accept a claim because it sounds right or all personas agree on it — consensus is not the same as correctness.

Step 3: Cross-reference

Note claims found independently by multiple agents. If 3+ personas independently identify the same issue, escalate to HIGH priority regardless of individual severity.

Step 4: Prioritize

Sort VALID and PARTIAL findings by impact:

  • HIGH: Core functionality, security, or maintainability
  • MEDIUM: Important improvements with moderate impact
  • LOW: Minor issues or polish

Gate: All claims validated with evidence. Proceed only when gate passes.

Show full SKILL.md (591 more words)Show less
Phase 5: SYNTHESIZE (Generate Report)

Goal: Transform aggressive persona outputs into constructive, actionable report.

Follow the full template in references/report-template.md. Key synthesis rules:

  1. Filter by verdict: Only VALID and PARTIAL claims appear in improvement opportunities
  2. Dismissed section: UNFOUNDED claims go in dismissed section with evidence showing why. Transparency matters — users need to understand why certain critiques don't hold up.
  3. Subjective section: SUBJECTIVE claims noted as opinion-based. User decides.
  4. Strengths required: Coordinator validates what works well. Not just problems. Include "Validated Strengths" section.
  5. Constructive tone: Strip sarcasm, mockery, dismissive language from agent outputs. Preserve technical accuracy and file references.
  6. Implementation roadmap: Group actions by immediacy (immediate / short-term / long-term)

Validation Summary Table (include in report):

markdown
## Claim Validation Summary

| Claim | Agent | Verdict | Evidence |
|-------|-------|---------|----------|
| [CLAIM-1] | Senior | VALID | [file:line shows X] |
| [CLAIM-2] | Pedant | PARTIAL | [true that X, but Y mitigates] |
| [CLAIM-3] | Newcomer | UNFOUNDED | [code shows otherwise] |

Gate: Report complete with all sections populated. Analysis done.


Examples

Example 1: Roast a README

User says: "Roast this repo"

skill: roast

Actions:

  1. Activate read-only mode (Phase 1)
  2. Read README.md, survey repo structure, identify key files (Phase 2)
  3. Spawn 5 persona agents in parallel, each analyzing README + structure (Phase 3)
  4. Collect all [CLAIM-N] tags, validate each against actual files (Phase 4)
  5. Synthesize constructive report with prioritized improvement opportunities (Phase 5) Result: Evidence-based critique with actionable improvements and validated strengths
Example 2: Roast a Design Doc

User says: "Poke holes in the architecture doc"

skill: roast @README.md

Actions:

  1. Activate read-only mode, read the target document (Phases 1-2)
  2. Survey related implementation files referenced by the doc (Phase 2)
  3. Spawn 5 agents focused on that document and its claims (Phase 3)
  4. Validate claims against both doc content and referenced code (Phase 4)
  5. Report with architecture-specific improvements and alternatives (Phase 5) Result: Multi-perspective architecture review grounded in implementation
Example 3: Roast an Approach

User says: "Devil's advocate on using SQLite for the error learning database"

skill: roast the idea of using SQLite for the error learning database

Actions:

  1. Search repo for existing SQLite implementation and related code (Phase 2)
  2. Spawn agents to critique both the concept AND actual code found (Phase 3)
  3. Validate claims against implementation evidence (Phase 4)
  4. Report grounded in real code, not just theoretical critique (Phase 5) Result: Critique anchored in actual implementation, not a strawman

Error Handling

Error: "Agent Returns Claims Without File References"

Cause: Persona agent skipped evidence-gathering or analyzed verbally Solution:

  1. Dismiss ungrounded claims as UNFOUNDED — they cannot be validated
  2. If majority of claims lack references, re-run that specific agent with explicit instruction to cite file:line
  3. Never promote ungrounded claims to the validated findings section
Error: "Read-Only Mode Not Activated"

Cause: Phase 1 skipped or read-only-ops skill invocation failed Solution:

  1. Stop all analysis immediately
  2. Call the Skill tool with read-only-ops. Do this before proceeding.
  3. If skill unavailable, manually enforce: no Write, Edit, or destructive Bash
Error: "Agent Attempts to Fix Issues"

Cause: Persona agent crossed from analysis into implementation Solution:

  1. Discard any modifications attempted
  2. Extract only the analytical findings from that agent's output
  3. Remind: this is read-only analysis, fixes are the user's decision
Error: "No Target Found or Empty Repository"

Cause: User invoked roast without specifying target and no README.md exists Solution:

  1. Check for alternative entry points: CONTRIBUTING.md, docs/, main source files
  2. If repo has code but no docs, analyze the code structure and entry points
  3. If truly empty, inform user and ask for a specific file or concept to analyze

References

Reference Files
  • ${CLAUDE_SKILL_DIR}/references/report-template.md: Full report output template with tone transformation rules
  • agents/reviewer-code.md: Code quality reviewer (senior and pedant lenses)
  • agents/reviewer-perspectives.md: Perspectives reviewer (newcomer and contrarian lenses)
  • agents/reviewer-domain.md: Domain reviewer (pragmatic-builder lens)
Dependencies
  • read-only-ops skill: Enforces no-modification guardrails during analysis

© notque, 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 skills/research/roast of notque/vexjoy-agent.

  • SKILL.md
  • references/report-template.md

Open the folder on GitHubat commit 5218674

Compare with similar skills

Roast 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.

Roast compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Roast this skillnotque/vexjoy-agent435—~3.2kAutomated safety check: NotesMIT
Dirextalk DeployerYingSuiAI/dirextalk-deployer457—~7.2kAutomated safety check: PassMIT
Cursor Composer Task DelegateChachamaru127/claude-code-harness3.2k—~4.4kAutomated safety check: NotesMIT
Gridbash Panesjasonsuhari/gridbash134—~1.5kAutomated safety check: PassMIT
Niubashunixwin/niubash146—~2.1kAutomated safety check: PassMIT
Brain Bootstrapmindmuxai/brain.md564—~1.8kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Roast

What does Roast do?

Constructive critique via 5 HackerNews personas with claim validation. Roast is an agent skill from notque/vexjoy-agent. Constructive critique via 5 HackerNews personas with claim validation.

When should I use Roast?

Roast fits situations like: development work in your project.

How do I install Roast in Claude Code?

Run `npx skills add notque/vexjoy-agent --skill roast -a claude-code`. Or copy the skill folder (skills/research/roast in notque/vexjoy-agent) into .claude/skills/roast in your project. Claude Code loads it when a task matches its description.

How do I install Roast in Codex?

Run `npx skills add notque/vexjoy-agent --skill roast -a codex`. Or copy the skill folder (skills/research/roast in notque/vexjoy-agent) into .agents/skills/roast in your project. Codex loads it when a task matches its description.

Can I use Roast 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 notque/vexjoy-agent --skill roast -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/roast, .gemini/skills/roast, .github/skills/roast and .opencode/skills/roast in your project.

What does Roast need to run?

Going by SKILL.md and its folder, Roast needs the command-line tools its instructions call (git). Its frontmatter pre-approves these tools: Read, Glob, Grep, Bash, Task, Skill.

Does Roast access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Roast safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Roast use?

Roast 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 Roast use?

About 3.2k tokens (SKILL.md is roughly 13k 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 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Roast?

Skills that share tags, products or a category with Roast: Dirextalk Deployer (YingSuiAI/dirextalk-deployer, 457 stars), Cursor Composer Task Delegate (Chachamaru127/claude-code-harness, 3.2k stars), Gridbash Panes (jasonsuhari/gridbash, 134 stars) and Niubash (unixwin/niubash, 146 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Roast?

notque (a GitHub user) maintains it in notque/vexjoy-agent, which has 435 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on October 3, 2026.

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