Chalk Labs
Need help deploying grilling?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
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/maxatwork-grilling
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
Use cases: testing
Reviews
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What's inside
- Skill name
grilling- Description
- Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
- License
- MIT
- Instructions
- 25 lines in SKILL.md · view on GitHub
Files (3)
- LICENSE
- SKILL.md
- openai.yaml · agents/
SKILL.md (first lines)
Interview the user relentlessly until you reach a shared understanding. Map this as a **design tree**: every decision branches into the decisions that hang off it. Work the tree in **rounds**. The **frontier** is every decision whose prerequisites are already settled: the questions you can ask _now_ without guessing at answers you haven't heard yet. Ask the whole frontier in one round: number each question and give your recommended answer. Then wait for the user's answers before the next round. Format a round like so: ``` ❓ **Q1** - **<question title>**: <question body, might be multiple paragraphs, including multiple choices> ➡️ <your recommended answer> --- ❓ **Q2** - **<question title>**: <question body, might be multiple paragraphs, including multiple choices> ➡️ <your recommended answer> ``` Each round the user answers reshapes the tree: settled decisions push the frontier outward and unblock questions that depended on them. Recompute the frontier and ask the next round. A question whose answer depends on another question still open in this round belongs to a _later_ round, not this one. Finding _facts_ is your job, never the user's. When a frontier question needs a fact from the environment (filesystem, tools, etc.), dispatch a sub-agent to find it; don't ask the user for anything you could look up yourself. Don't block on it: a running exploration is an unsettled prerequisite, so only the questions downstream of it wait for the sub-agent to report; ask the rest of the frontier now. The _decisions_ are the user's: put each to them and wait. The session is done when the frontier is empty: every branch of the design tree visited, nothing left silently assumed. Do not act on it until the user confirms you have reached a shared understanding.
From maxatwork/skills, MIT.
More from maxatwork/skills
- 0.589score
exploring-repositories
maxatwork
Inspect or compare an external repository using a durable local clone.
SkillAFreshness: A★ 1Claude Code +9 - 0.589score
impeccable
maxatwork
Design or improve frontend UX and visual quality.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
model-selection
maxatwork
Choose the cheapest sufficient model and effort for coding, reasoning, taste, and throughput needs.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
penpot-canvas
maxatwork
Create, open, edit, inspect, and preview designs in a user-configured Penpot instance using Codex's built-in browser and the Penpot MCP server.
SkillAFreshness: A★ 1Claude Code +9 - 0.581score
forgejo-cli
maxatwork
Use when need to work with Forgejo repository tasks, including pull requests, issues, releases, and Actions.
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
find-skills
maxatwork
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express…
SkillAFreshness: A★ 1Claude Code +9 - 0.552score
create-verification-skill
maxatwork
Use ONLY when the user asks to create a repository verification skill.
SkillBFreshness: B★ 1Claude Code +9 - 0.549score
diagnosing-bugs
maxatwork
Diagnose bugs or performance regressions whose cause is unclear using reproduction, targeted evidence, and hypothesis testing.
SkillBFreshness: B★ 1Claude Code +9 - 0.549score
fallow
maxatwork
Analyze JavaScript and TypeScript with Fallow for unused code, duplication, complexity, architecture, styling, or changed-code risk.
SkillBFreshness: B★ 1Claude Code +9 - 0.547score
domain-modeling
maxatwork
Change or clarify domain concepts, terminology, ownership, and lifecycles.
SkillBFreshness: B★ 1Claude Code +9 - 0.547score
codebase-design
maxatwork
Design or review module interfaces, ownership, and test seams using deep-module principles.
SkillBFreshness: B★ 1Claude Code +9 - 0.547score
ponytail-audit
maxatwork
Audit a whole codebase for unnecessary complexity when the user asks for over-engineering or bloat analysis.
SkillBFreshness: B★ 1Claude Code +9
Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 29, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/maxatwork/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from maxatwork
- 0.589score
exploring-repositories
maxatwork
Inspect or compare an external repository using a durable local clone.
SkillAFreshness: A★ 1Claude Code +9 - 0.589score
impeccable
maxatwork
Design or improve frontend UX and visual quality.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
model-selection
maxatwork
Choose the cheapest sufficient model and effort for coding, reasoning, taste, and throughput needs.
SkillAFreshness: A★ 1Claude Code +9 - 0.584score
penpot-canvas
maxatwork
Create, open, edit, inspect, and preview designs in a user-configured Penpot instance using Codex's built-in browser and the Penpot MCP server.
SkillAFreshness: A★ 1Claude Code +9 - 0.581score
forgejo-cli
maxatwork
Use when need to work with Forgejo repository tasks, including pull requests, issues, releases, and Actions.
SkillAFreshness: A★ 1Claude Code +9 - 0.562score
find-skills
maxatwork
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express…
SkillAFreshness: A★ 1Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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Cite this page
grilling skill. Agent Mart. https://agentmart.dev/skills/maxatwork-grilling (last updated 2026-10-24)