Run an explicitly requested decision interview and record each settled decision in durable project documentation.

MITAuto-check passed

Install Grill

skills CLI
$ npx skills add asgeirtj/system_prompts_leaks --skill grill -a claude-code

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

GitHub CLI
$ gh skill install asgeirtj/system_prompts_leaks grill --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/asgeirtj/system_prompts_leaks.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Meta/muse-code/skills/grill .claude/skills/grill && 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
GitHub stars
69k
Token cost
~1.7k tokens
SKILL.md length
952 words
Files
1
Skills in repo
128
Repo updated
First seen
Licence
MIT

At a glance

Run an explicitly requested decision interview and record each settled decision in durable project documentation.

  • Works in 6 steps: Research discoverable facts in the… → Ask one decision-forcing question at a… → Ask every interview question in plain… → …
  • SKILL.md covers Interview Contract, Background formal evidence, Scope Contract and Documentation Contract, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Grill is an agent skill from asgeirtj/system_prompts_leaks. Run an explicitly requested decision interview and record each settled decision in durable project documentation.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Documented system prompts from Anthropic - Claude Fable 5.1, Opus 5.5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Google - Gemini 3.8 Flash, 3.1 Pro… The licence is MIT.

Example prompts

  • “/grill”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Research discoverable facts in the repository, issue, docs, and code before asking the user. Ask only for judgments or facts that cannot…
  2. Ask one decision-forcing question at a time. State the recommended answer and the reason briefly, then wait for the answer.
  3. Ask every interview question in plain text as an ordinary assistant response. Do not use a question tool.
  4. Use comparison tables only when the user explicitly requested one or the question concerns agent-product behavior, such as Claude Code…
  5. Follow dependent decisions until the skill decides the decision tree is exhausted. Never ask a final "are we done?" meta-question.
  6. Summarize the settled contract: goals, non-goals, decisions, constraints, risks, validation, and unresolved items.

What it can do on your machine

Read from SKILL.md and the folder at commit 60d44cc. 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

    Links to these hosts (documentation or services it may open):

    • github.com

    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 loads about 1.7k tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 952 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~30
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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 asgeirtj/system_prompts_leaks at commit 60d44cc, republished under its MIT licence (© asgeirtj). 952 words, ~1,662 tokens.

Download SKILL.mdSave it as .claude/skills/grill/SKILL.md (or your agent's skills folder).
name
grill
description
Run an explicitly requested decision interview and record each settled decision in durable project documentation.
source
https://github.com/mattpocock/skills
license
MIT

Grill

Use this skill only when the user explicitly asks for grilling plus durable documentation or directly invokes this skill; the agents coordinator handing it an unclear goal, or one decision needing the user's confirmation, before its plan is a direct invocation (its question is the user's judgement — target, measure, scope — that repository facts shape but never answer), and there the durable record is the project's own PROJECT.md or library/ file, never a repository doc. Complexity, ambiguity, or a possible need for docs alone never activates it. This skill carries its own interview and documentation contract. Do not load or invoke domain-modeling at runtime.

Interview Contract

  1. Research discoverable facts in the repository, issue, docs, and code before asking the user. Ask only for judgments or facts that cannot be discovered.
  2. Ask one decision-forcing question at a time. State the recommended answer and the reason briefly, then wait for the answer.
  3. Ask every interview question in plain text as an ordinary assistant response. Do not use a question tool.
    • When a bounded decision benefits from 2-3 short, mutually exclusive choices, list them in plain text with the recommended answer first.
    • Invite the user to choose, modify, or discuss the choices instead of forcing a structured selection.
  4. Use comparison tables only when the user explicitly requested one or the question concerns agent-product behavior, such as Claude Code versus Codex.
  5. Follow dependent decisions until the skill decides the decision tree is exhausted. Never ask a final "are we done?" meta-question.
  6. Summarize the settled contract: goals, non-goals, decisions, constraints, risks, validation, and unresolved items.

Background formal evidence

When the target project provides an applicable formal checker, follow its local documentation to prepare the declared interview input and run the check before choosing the outline and after relevant answers or source changes. Read the completed invocation's results and source/input binding, then use unresolved obligations and counterexamples to revise the next question. Recheck changed inputs. Reuse answers only within their supported scope and conditions, preserving independent choices. After each answer, write its source and applicable scope into the declared input and the journal or Draft decision; rerun and record the revised remaining obligations before the next outline. A possible model assignment is not human acceptance; bounded coverage does not cover unlisted questions. Missing or stale evidence limits dependent conclusions while independent permitted work continues. Ask one practical question in the user's language, with ordinary choices and consequences; explain formal techniques when asked.

Scope Contract

The interview is not finished until the settled contract fixes the scope in writing and the user accepts that text explicitly:

  1. Artifact-level boundary. Name what the deliverable is (the documents, directories, PRs, or code paths in scope) and the artifact classes that are out of scope, such as follow-on specs, tests, runtime code, or task plans.
  2. Done means. A short checklist of the observable conditions that finish the work: landed commits, closed issues, verified evidence. Nothing outside the checklist is a completion dependency.
  3. Staged designs are approved one stage at a time. If a decision record describes later stages (an ADR that stages Constitution, spec, or runtime changes), record them as deferred proposals; accepting the record never approves the later stages. Each stage returns for its own interview.
  4. Execution words never widen scope. "Go", "do it all", or "land 1-5" authorize only the accepted boundary. When later work would add an artifact class, a new PR, or a task program outside the boundary, stop before producing it and take one of exactly two paths: obtain the owner's explicit approval of the wider boundary, recorded on the owning issue, or move the extra work into a follow-up issue that starts its own interview. Never build first and ask afterwards.

Post the accepted scope contract where the executing lane and its supervisors can read it (for repository work, the owning issue), quoting the acceptance. This comment is lane-coordination evidence, not a decision record: it quotes the user's exact words with channel and time; the durable decision lives in the record this skill writes, never in the comment.

Ending the interview never authorizes implementation. Implement only after a separate explicit user request.

Show full SKILL.md (255 more words)Show less

Documentation Contract

  1. Before the first question, resolve the target document from the user's named target and the repository's existing documentation conventions. Inspect local instructions, indexes, specs, ADRs, glossaries, and nearby docs. If the target is undeterminable, ask one question. Never invent a universal docs/grilling/<date>.md location.
  2. Create or update the target as Draft. Write each settled decision immediately as Draft instead of waiting for the interview to end. Keep unresolved questions visibly marked.
  3. If interrupted or cancelled, preserve the Draft and all file edits, mark unresolved questions, and never auto-revert documentation changes.
  4. Read detailed CONTEXT.md, ADR, glossary, or other format references only when that document type is actually being written.
  5. Normal Write/Edit tool events are the live proof of documentation work. Do not emit duplicate Updated <path> status lines.
  6. An explicit docs request is a hard completion condition: the session cannot finish successfully without a useful documentation creation or update. "No docs needed" with zero file changes never satisfies it.
  7. Only explicit user acceptance may change a document from Draft to Final. Exhausting the decision tree does not imply acceptance.
  8. In the final response, list every changed documentation path and whether it stayed Draft or became Final.

Credit

This skill's name and interview approach — one recommended answer per question, repository facts researched instead of asked, decisions written down as they settle — come from the grilling skill (and the former grill-with-docs skill) by Matt Pocock (@mattpocockuk), https://github.com/mattpocock/skills. The skill text shipped here is our own. See the package's CREDITS.md.

© asgeirtj, 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 Meta/muse-code/skills/grill of asgeirtj/system_prompts_leaks.

Open the folder on GitHubat commit 60d44cc

Compare with similar skills

Grill 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 compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Grill this skillasgeirtj/system_prompts_leaks69k—~1.7kAutomated safety check: PassMIT
Grill Menrwl/nx29k—~1.2kAutomated safety check: PassMIT
Interviewalirezarezvani/claude-skills28k—~1.1kAutomated safety check: PassMIT
Screen Recordinggithub/awesome-copilot40k—~2kAutomated safety check: PassMIT
Recordingcodewhale-hq/Codewhale41k—~540Automated safety check: PassMIT
Medical Records Requestmohitagw15856/pm-claude-skills1.4k—~1.6kAutomated safety check: PassMIT

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Questions about Grill

What does Grill do?

Run an explicitly requested decision interview and record each settled decision in durable project documentation. Grill is an agent skill from asgeirtj/system_prompts_leaks. Run an explicitly requested decision interview and record each settled decision in durable project documentation.

How do I install Grill in Claude Code?

Run `npx skills add asgeirtj/system_prompts_leaks --skill grill -a claude-code`. Or copy the skill folder (Meta/muse-code/skills/grill in asgeirtj/system_prompts_leaks) into .claude/skills/grill in your project. Claude Code loads it when a task matches its description.

How do I install Grill in Codex?

Run `npx skills add asgeirtj/system_prompts_leaks --skill grill -a codex`. Or copy the skill folder (Meta/muse-code/skills/grill in asgeirtj/system_prompts_leaks) into .agents/skills/grill in your project. Codex loads it when a task matches its description.

Can I use Grill 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 asgeirtj/system_prompts_leaks --skill grill -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, .gemini/skills/grill, .github/skills/grill and .opencode/skills/grill in your project.

What does Grill need to run?

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

Does Grill access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Grill 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 use?

Grill 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 use?

About 1.7k tokens (SKILL.md is roughly 6.6k 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?

Skills that share tags, products or a category with Grill: Grill Me (nrwl/nx, 29k stars), Interview (alirezarezvani/claude-skills, 28k stars), Screen Recording (github/awesome-copilot, 40k stars) and Recording (codewhale-hq/Codewhale, 41k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Grill?

asgeirtj (a GitHub user) maintains it in asgeirtj/system_prompts_leaks, which has 69,280 GitHub stars. The repository holds 128 skills in this directory. The repository was last updated on October 10, 2026.

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