grill-me

grill-me is a skill for Claude Code, Codex from OutlineDriven/odin-codex-plugin. It costs 83 tokens per session (1,972 once invoked), scanned A, original, Apache-2.0.

An adversarial interview workflow for examining a software plan or design through a sequence of decisions and questions.

In plain words
What is it for?
Use it to stress-test a proposed design and reach shared understanding by resolving one decision at a time.
Why use it?
It exposes unclear assumptions, missing dependencies, and unresolved choices before implementation begins.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/outlinedriven/odin-codex-plugin/grill-me
Any agent
npx skills add OutlineDriven/odin-codex-plugin --skill grill-me
Clone the repo
git clone --depth 1 https://github.com/OutlineDriven/odin-codex-plugin

Made for: Claude Code, Codex.

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 grill-me

README.md
[![agentmods](https://agentmods.dev/badge/skills/outlinedriven/odin-codex-plugin/grill-me.svg)](https://agentmods.dev/skills/outlinedriven/odin-codex-plugin/grill-me)
Your own site
<a href="https://agentmods.dev/skills/outlinedriven/odin-codex-plugin/grill-me"><img src="https://agentmods.dev/badge/skills/outlinedriven/odin-codex-plugin/grill-me.svg" alt="Measured on agentmods" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,972 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00083 $0.01972
Opus 5 $0.00042 $0.00986
Sonnet 5 $0.00017 $0.00394
Haiku 4.5 $0.00008 $0.00197

Measured 5d ago against content hash f9dd03f91837, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

grill-me 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 5d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • grill-me — 100% identical, 0 lines differ
skills/grill-me/SKILL.md · 145 lines

How it starts

The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Adversarial interview. Walk every branch of the design tree; resolve dependencies one decision at a time; recommend an answer per question.

Modality disambiguation [LOAD-BEARING]

Three adjacent skills — pick the right one before invoking.

Skill Shape Anchor Output Use when
clarifying-question protocol VS-shaped — sample N intent hypotheses, rank, challenge each, then batch clarifying questions None — pre-planning ambiguity Survivor set + clarified scope User intent is itself unclear
this skill Linear adversarial interview, recommendation per question None — design under test is the only anchor Shared understanding, decision tree resolved User has a plan/design and wants it stress-tested
domain-model grilling Adversarial interview gated on documented domain language CONTEXT.md + docs/adr/ Updated CONTEXT.md and/or new ADR Project has documented domain language to honour

Rule of thumb: intent unclear → clarifying-question protocol. Plan exists, no domain rubric → this skill. Plan exists, domain rubric required → domain-model grilling.

Process

1. Anchor on the design under test

Confirm what the plan is in one sentence. If the user's pitch is too thin to interrogate, pivot to a clarifying-question protocol instead.

2. Walk the decision tree

For every fork in the design — scope, boundary, ordering, error surface, contract, naming, public-API shape, irreversibility — ask one question. Order by dependency: parents before children.

For each question:

  • State the question precisely (one fact at a time).
  • Recommend an answer with a one-sentence rationale.
  • Wait for the user; never proceed on assumed answers.

3. Explore the codebase before asking when possible

If a question can be resolved by reading the code, read it instead of asking.

  • Discovery: fd -e <ext> <path>.
  • Structural search: ast-grep run -p '<pattern>' -l <lang> -C 3.
  • Lexical search: git --no-pager grep -n -C 3 '<pattern>'.
  • Targeted read: bat -P -p -n -r START:END <path>.
  • Dispatch an Explore agent when the question spans >5 files or >2 directories.

Read the full file on GitHub · 145 lines

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. 5d ago First seen · 145 lines · 83 tokens per session scan A f9dd03f91837

Subscribe to this mod's changes

grill-me is a skill published in the GitHub repository OutlineDriven/odin-codex-plugin (15 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 83 tokens to every session and 1,972 once invoked, about $0.0004 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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