grill-me

grill-me is a skill for Claude Code, Codex, Cursor from jepegit/issue-flow. It costs 73 tokens per session (642 once invoked), scanned A, original, MIT.

A planning interview that asks detailed questions about a proposed plan or design until its major decisions are settled.

In plain words
What is it for?
Use it to stress-test a plan, resolve design choices one at a time, and prepare a clearer issue plan.
Why use it?
It uncovers hidden assumptions, alternatives, dependencies, and edge cases before they become code or a written plan.

Skill for Claude CodeCodexCursor

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/jepegit/issue-flow/grill-me
Any agent
npx skills add jepegit/issue-flow --skill grill-me
Clone the repo
git clone --depth 1 https://github.com/jepegit/issue-flow

Made for: Claude Code, Codex, Cursor.

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/jepegit/issue-flow/grill-me.svg)](https://agentmods.dev/skills/jepegit/issue-flow/grill-me)
Your own site
<a href="https://agentmods.dev/skills/jepegit/issue-flow/grill-me"><img src="https://agentmods.dev/badge/skills/jepegit/issue-flow/grill-me.svg" alt="Measured on agentmods" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 642 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 $0.00073 $0.00642
Opus 5 $0.00036 $0.00321
Sonnet 5 $0.00015 $0.00128
Haiku 4.5 $0.00007 $0.00064

Measured 3d ago against content hash eebf8df68f8a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 3d 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.

.cursor/skills/grill-me/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Grill me — relentless planning interview

Interview the user about every aspect of the plan until you reach a shared, unambiguous understanding. Walk down each branch of the design tree, resolving dependencies between decisions one at a time. The goal is to surface hidden assumptions and edge cases before they get encoded in code or written into .issueflows/01-current-issues/issue<N>_plan.md.

When to use

  • The user asks to be grilled / stress-tested ("grill me", "poke holes in this").
  • During /iflow-plan, when grilling is active (see Activation below), to pressure-test the approach before the plan file is drafted.

How to grill

  • One question at a time. Never batch questions. Wait for the answer before moving to the next branch.
  • Always recommend an answer. For each question, give your recommended option and a one-line rationale, so the user can accept quickly or push back.
  • Explore before asking. If a question can be answered by reading the code, the issue text, or .issueflows/04-designs-and-guides/, explore first and confirm what you found instead of asking the user to do your homework.
  • Follow the decision tree. Resolve upstream decisions before the ones that depend on them; let earlier answers prune later branches.
  • Stay on scope. Grill the issue at hand. Park genuinely separate concerns as follow-up notes rather than expanding the interview indefinitely.
  • Know when to stop. End when every open branch is resolved (or explicitly deferred) and you can restate the plan without ambiguity. Summarize the agreed decisions so they can flow straight into the plan.

Activation

This skill is dormant by default: it engages only when the user asks for it ("grill me") or when a project turns it on for planning.

Turn it off again for the rest of a session with "stop grilling" or "normal mode". (To make grilling on by default during planning for this project, set grill_me_default = true under [issueflow] in .issueflows/config.toml and re-run issue-flow update.)

Read the full file on GitHub · 58 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. 3d ago First seen · 58 lines · 73 tokens per session scan A eebf8df68f8a

Subscribe to this mod's changes

grill-me is a skill published in the GitHub repository jepegit/issue-flow (4 stars, last pushed 21d ago), licensed MIT. It adds 73 tokens to every session and 642 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 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

chat-perf

Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens