Agent skill

Grill Me

by open-octo in open-octo/octo-agent

Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree one at a time.

MITAuto-check passedAgent Workflows

Install Grill Me

skills CLI
$ npx skills add open-octo/octo-agent --skill grill-me -a claude-code

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

GitHub CLI
$ gh skill install open-octo/octo-agent grill-me --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/open-octo/octo-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/internal/skills/defaults/grill-me .claude/skills/grill-me && 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
grill-me
GitHub stars
125
Token cost
~1.2k tokens
SKILL.md length
624 words
Files
1
Skills in repo
40
Repo updated
First seen
Licence
MIT

At a glance

Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree one at a time.

  • Works in 4 steps: Context exploration → Grill → Coverage check → …
  • The user wants to stress-test a plan
  • SKILL.md covers ⚠️ Hard rule: ONE question per…, Phase 0 — Context exploration, Phase 1 — Grill and Phase 2 — Coverage check, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Grill Me is an agent skill from open-octo/octo-agent. Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree one at a time. Use when the user wants to stress-test a plan, pressure-test a design before building, or says "grill me", "拷问我", "帮我把方案想清楚", "挑战一下这个设计", "review my plan before I build". Pairs with the tech-design skill — grill first, then hand the resolved decisions to tech-design to write them up.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Requirements gathering and Load testing. The repository describes itself as: Open-source, single-binary, self-hosted AI agent — your models and data stay on your machine. A coding agent on par with Claude Code and a personal assistant lighter than… The licence is MIT.

When your agent uses it

  • The user wants to stress-test a plan
  • Pressure-test a design before building
  • Review my plan before I build

Example prompts

  • “grill me”
  • “帮我把方案想清楚”
  • “挑战一下这个设计”
  • “/grill-me”

Workflow steps

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

  1. Context exploration
  2. Grill
  3. Coverage check
  4. Wrapping up

What it can do on your machine

Read from SKILL.md and the folder at commit 81448b2. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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

Grill Me loads about 1.2k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 624 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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 passed

The automated check found no risky patterns in SKILL.md.

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 open-octo/octo-agent at commit 81448b2, republished under its MIT licence (© open-octo). 624 words, ~1,229 tokens.

Download SKILL.mdSave it as .claude/skills/grill-me/SKILL.md (or your agent's skills folder).
name
grill-me
description
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree one at a time. Use when the user wants to stress-test a plan, pressure-test a design before building, or says "grill me", "拷问我", "帮我把方案想清楚", "挑战一下这个设计", "review my plan before I build". Pairs with the tech-design skill — grill first, then hand the resolved decisions to tech-design to write them up.
license
MIT
metadata.origin
adapted for octo — generic stack, octo-native codebase exploration

Skill: grill-me

Interview the user relentlessly about every aspect of a plan until you reach a shared, resolved understanding. You are the skeptic who surfaces the decisions they haven't made yet — not a note-taker.

⚠️ Hard rule: ONE question per message

This is the single most important rule of this skill. Even when you spot five things worth grilling on, send the first question, wait for the answer, then ask the next.

Why this matters: a wall of five questions defeats the purpose. The user can't think hard about any single decision when faced with a multi-question pile — they'll skim and pick the easy ones, or push back asking "which first?". Both waste the session.

Anti-pattern:

❌ "Here are 5 things I want to grill on: 1. … 2. … 3. …"

Correct pattern:

✅ "[First question, with options + recommendation]" [wait for answer] "[Next question, informed by the previous answer]"

If a topic has sub-questions, ask the top-level one first and drill in based on the answer. Don't pre-emptively enumerate every branch — the answer to question 1 often kills questions 2-3.

Phase 0 — Context exploration

Before asking any questions, do your homework:

  1. Read the input — the user may provide anything from a one-line idea to a full PRD (local file, doc URL, or prose). Whatever the form, extract what you can: problem statement, core user flow, scope boundaries. The less the user gives, the more Phase 1 needs to cover.
  2. Explore the codebase — identify the existing services, data models, APIs, message-queue topics, cache keys, and prior art relevant to the plan. Report key findings to the user concisely before starting questions.

This phase is silent work — don't ask the user things you can learn from the code.

Phase 1 — Grill

Walk down each branch of the design tree, resolving dependencies between decisions one by one. If a question can be answered by exploring the codebase, explore instead of asking.

Question format

For each non-trivial decision, structure the message as:

  1. Set up the decision — 1-2 sentences of context (what's at stake, why this is a branch point)
  2. Present 2-3 options as A/B/C with a one-paragraph trade-off each (table if complex)
  3. State your recommendation and why, grounded in the codebase findings
  4. End with the question

Then stop and wait. Do not chain a second question after this one, even if it feels closely related — the answer to question 1 usually reshapes question 2.

Show full SKILL.md (223 more words)Show less
Prefer multiple choice over open-ended

A/B/C questions are easier to answer and give you concrete signal to continue from. Reserve open-ended for "what are you optimizing for?" / "what's the goal?" style questions where the option space is genuinely unknown to you.

Simple yes/no or factual questions don't need the full options-and-recommendation treatment — use judgment.

Phase 2 — Coverage check

Before wrapping up, verify no critical area was missed. Scan the decisions made so far against these domains:

DomainCheck
ArchitectureService boundaries, sync vs async, failure handling
Data modelTables/collections, columns, indexes, data volume, partitioning
API designContracts, pagination, idempotency, breaking changes
MessagingTopics, schemas, consumer groups, retry/DLQ
CachingKey format, TTL, eviction, invalidation
ConfigurationConfig / feature-flag keys, per-environment default differences, dynamic vs restart-to-apply, multi-key ordering
Rollout & safetyGrayscale, feature flags, rollback, monitoring

For each domain relevant to the plan: if it was never discussed, ask about it now (still one question at a time — the temptation to batch returns here, resist it). If it was covered, skip it. Domains not applicable to the plan (e.g. no MQ involved) can be skipped entirely.

Phase 3 — Wrapping up

When all major branches of the decision tree are resolved, stop and summarize:

All key branches resolved. Decision summary:

1. [question] → [conclusion] ([rationale])
2. …

Want me to turn these into a technical design doc? (tech-design skill)

If the user says yes, invoke the tech-design skill. The decisions above stay in conversation context — tech-design uses them directly, so it won't re-grill.

© open-octo, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in internal/skills/defaults/grill-me of open-octo/octo-agent.

Open the folder on GitHubat commit 81448b2

Compare with similar skills

Grill Me 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.

Grill Me compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Grill Me this skillopen-octo/octo-agent125—~1.2kAutomated safety check: PassMIT
Grillingpietheinstrengholt/rssmonster56431 repos~510Automated safety check: PassMIT
Grill Menateherkai/AIS-OS1.6k—~1.8kAutomated safety check: PassCustom licence
Grill MeEffect-TS/effect-smol7821 repos~504Automated safety check: PassMIT
Grill Mesanity-io/sanity6.4k39 repos~151Automated safety check: PassMIT
Deep Divebyungjunjang/jangpm-meta-skills120—~2.5kAutomated safety check: PassNone

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Categories

Questions about Grill Me

What does Grill Me do?

Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree one at a time. Grill Me is an agent skill from open-octo/octo-agent. Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree one at a time.

When should I use Grill Me?

Grill Me fits situations like: the user wants to stress-test a plan; pressure-test a design before building; review my plan before I build.

How do I install Grill Me in Claude Code?

Run `npx skills add open-octo/octo-agent --skill grill-me -a claude-code`. Or copy the skill folder (internal/skills/defaults/grill-me in open-octo/octo-agent) into .claude/skills/grill-me in your project. Claude Code loads it when a task matches its description.

How do I install Grill Me in Codex?

Run `npx skills add open-octo/octo-agent --skill grill-me -a codex`. Or copy the skill folder (internal/skills/defaults/grill-me in open-octo/octo-agent) into .agents/skills/grill-me in your project. Codex loads it when a task matches its description.

Can I use Grill Me 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 open-octo/octo-agent --skill grill-me -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/grill-me, .gemini/skills/grill-me, .github/skills/grill-me and .opencode/skills/grill-me in your project.

What does Grill Me need to run?

SKILL.md names no scripts, command-line tools or credentials: Grill Me is instructions for the agent only.

Does Grill Me access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Grill Me safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Grill Me use?

Grill Me is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Grill Me use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Grill Me?

Skills that share tags, products or a category with Grill Me: Grilling (pietheinstrengholt/rssmonster, 564 stars), Grill Me (nateherkai/AIS-OS, 1.6k stars), Grill Me (Effect-TS/effect-smol, 782 stars) and Grill Me (sanity-io/sanity, 6.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Grill Me?

open-octo (a GitHub organization) maintains it in open-octo/octo-agent, which has 125 GitHub stars. The repository holds 40 skills in this directory. The repository was last updated on October 9, 2026.

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