agentsclimarketplace

Grill me

Skill alirezarezvani/claude-skills/engineering/grill-me/skills/grill-me

Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".From its SKILL.md

Install
npx -y skills add alirezarezvani/claude-skills --skill grill-me

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.5 KB, 484 tokens by cl100k_base, as published. Nobody here has run it

Grill Me

Derived from Matt Pocock's grill-me (MIT). Matt's interview discipline preserved verbatim. Additions: extraction + question + session tools + references + cs-* wrapper (see references/companion_tooling.md).

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.

If a question can be answered by exploring the codebase, explore the codebase instead.

Rules (preserved + amplified)

  1. One question per turn. Never bundle.
  2. Provide a recommended answer with each question. Defaulting to "what do you think?" is lazy.
  3. Explore the codebase before asking. If grep / Read resolves it, do that first. Saves a turn.
  4. Walk the tree depth-first. Finish a branch before opening another.
  5. Track dependencies. If decision B depends on decision A, ask A first.

Workflow

  1. User provides a plan or design (or path to one).
  2. Run scripts/decision_tree_extractor.py to extract branches.
  3. Run scripts/question_generator.py to produce the question list with recommendations.
  4. Start a session: scripts/grill_session_tracker.py --action start.
  5. Walk the tree, one question at a time, recording answers in the session.
  6. When all branches resolved: report "shared understanding reached" + the locked-in decisions.

Output Pattern

Per question turn:

Q[i]/[total]: [question]
Recommended answer: [your call + 1-sentence rationale]

(Or: I explored the codebase and found [evidence]. Confirm?)

Tooling

See references/companion_tooling.md. Tools: extractor + generator + tracker. Agent: cs-grill-master. Command: /cs:grill-me.


Version: 1.0.0 Derived: Matt Pocock (MIT) + this repo's wrapper

What ships with it: 6 files

34.6 KB alongside SKILL.md, 3 of them executable

Gives 3 of the 12 instructions most review quality skills give in 484 tokens

Counted across 1,273 of the 2,403 authors here whose files we hold, read 2026-09-06

  • Ask one question at a timehere, and in 63 of 1273, across 62 files
  • Provide a recommended answer for each questionhere, and in 47 of 1273, across 45 files
  • Rank findings by severityin 44 of 1273
  • Use parameterized queries for database accessin 38 of 1273, across 20 files
  • Validate all user input with schemasin 33 of 1273, across 15 files
  • Store secrets in environment variablesin 32 of 1273, across 14 files
  • Explore the codebase to answer questionshere, and in 31 of 1273, across 29 files
  • Store tokens in httpOnly cookiesin 30 of 1273, across 12 files
  • Implement rate limiting on API endpointsin 30 of 1273, across 12 files
  • Sanitize user-provided HTMLin 29 of 1273, across 11 files
  • Return generic error messages to usersin 28 of 1273, across 10 files
  • Cite file and line for every findingin 28 of 1273, across 25 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.