grilling

grilling is a skill for Claude Code from dgilford/ai-science-toolkit. It costs 92 tokens per session (468 once invoked), scanned A, original, MIT.

A guided questioning process for examining a plan or design one decision at a time. It continues until the important choices and dependencies are understood together.

In plain words
What is it for?
Stress-testing designs, resolving implementation choices, and reviewing plans before changing services, allocating shared resources, or editing risky configuration.
Why use it?
It reveals hidden assumptions and risky branches before implementation. The process pauses for the user’s decisions instead of making consequential choices automatically.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ai-science-toolkit plugin — 21 skills, 4 agents shipped together

Good fit Stress-testing designs, resolving implementation choices, and reviewing plans before changing services, allocating shared resources, or editing risky configuration.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dgilford/ai-science-toolkit/grilling
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 dgilford/ai-science-toolkit --skill grilling
Clone the repo
git clone --depth 1 https://github.com/dgilford/ai-science-toolkit

Made for: Claude Code.

Or install ai-science-toolkit, the plugin that ships this one along with the rest of its 21 skills, 4 agents.

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 grilling

README.md
[![agentmods](https://agentmods.dev/badge/skills/dgilford/ai-science-toolkit/grilling.svg)](https://agentmods.dev/skills/dgilford/ai-science-toolkit/grilling)
Your own site
<a href="https://agentmods.dev/skills/dgilford/ai-science-toolkit/grilling"><img src="https://agentmods.dev/badge/skills/dgilford/ai-science-toolkit/grilling.svg" alt="Measured on agentmods" height="20"></a>
Per session 92 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 468 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00092 $0.00468
Opus 5 $0.00046 $0.00234
Sonnet 5 $0.00018 $0.00094
Haiku 4.5 $0.00009 $0.00047

Measured 8d ago against content hash ca6d159a9eb3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

grilling 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/grilling/SKILL.md · 32 lines

What it actually says

Interview me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.

Ask the questions one at a time, waiting for feedback on each question before continuing. Asking multiple questions at once is bewildering.

If a fact can be found by exploring the codebase, look it up rather than asking me. The decisions, though, are mine — put each one to me and wait for my answer.

Do not enact the plan until I confirm we have reached a shared understanding.

When to grill proactively

"If in doubt" is too weak a trigger — an agent handed a concrete task rarely feels in doubt, even when it hides consequential decisions. Grill before acting, not only when asked, whenever a step would:

  • change or restart a running service or process (a training run, a server, a scheduled job);
  • allocate a shared resource — GPUs, ports, memory, disk, a rate-limited API quota;
  • edit an interdependent config whose blast radius you cannot fully see;
  • invalidate or contradict a decision already made this session.

In these cases, surface the conflict explicitly and grill on how to resolve it before proceeding.

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 · 32 lines · 92 tokens per session scan A ca6d159a9eb3

Subscribe to this mod's changes

grilling is a skill published in the GitHub repository dgilford/ai-science-toolkit (62 stars, last pushed 19d ago), licensed MIT. It adds 92 tokens to every session and 468 once invoked, about $0.0005 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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