grill-with-docs

grill-with-docs is a skill for Claude Code, Codex from twaldin/flt. It costs 57 tokens per session (1,281 once invoked), scanned A, original, MIT.

A question-led planning review that checks a proposed change against the project's existing terms, data model, and documented decisions. It also records settled decisions in files such as CONTEXT.md and architecture decision records.

In plain words
What is it for?
Use it to work through a plan one question at a time, clarify terminology and design dependencies, and update project decision documents as answers are agreed.
Why use it?
It exposes mismatches and unresolved choices before implementation, while keeping the project's documentation aligned with the plan.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: names the AskUserQuestion tool.

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/twaldin/flt/grill-with-docs
Any agent
npx skills add twaldin/flt --skill grill-with-docs
Clone the repo
git clone --depth 1 https://github.com/twaldin/flt

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-with-docs

README.md
[![agentmods](https://agentmods.dev/badge/skills/twaldin/flt/grill-with-docs.svg)](https://agentmods.dev/skills/twaldin/flt/grill-with-docs)
Your own site
<a href="https://agentmods.dev/skills/twaldin/flt/grill-with-docs"><img src="https://agentmods.dev/badge/skills/twaldin/flt/grill-with-docs.svg" alt="Measured on agentmods" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,281 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 $0.00057 $0.01281
Opus 5 $0.00028 $0.00641
Sonnet 5 $0.00011 $0.00256
Haiku 4.5 $0.00006 $0.00128

Measured 5d ago against content hash c31fc2adb520, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

grill-with-docs 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.

templates/skills/grill-with-docs/SKILL.md · 125 lines

How it starts

The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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, waiting for feedback on each question before continuing.

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

How to ask questions

Dispatch rule (check at runtime):

  1. If flt is on PATH AND ~/.flt/ exists, use flt ask human '<json>' via the Bash tool. This persists the Q/A under ~/.flt/qna/ so the mutator/GEPA loop can train on it. The JSON shape is identical to AskUserQuestion's (1 question per call here — see batch sizing below — with 2-4 options, multiSelect, optional preview for single-select). Block on the bash call until the human answers; the command prints the answer JSON to stdout.
  2. Otherwise fall back to the native AskUserQuestion tool. Same JSON shape.

Either way, never dump prose with "Q1/Q2/Q3" sections — that's less readable than the interactive picker.

flt ask human payload shape:

{"questions":[
  {"id":"q-3a4f","header":"Auth","question":"Which approach?","multiSelect":false,
   "options":[
     {"label":"OAuth+JWT","description":"Standard but heavier"},
     {"label":"Sessions","description":"Simpler, same-origin only"}
   ]}
]}

The id field is required for flt ask human (random short slug, agent-provided). For native AskUserQuestion the runtime supplies the id implicitly — you don't need to write one.

Batch sizing for this skill: one question per call. The <what-to-do> block above mandates serial questioning so the user's answer can shape the next branch of the design tree. Don't batch multiple questions even when the underlying primitive supports it.

For each question:

  • Be specific. Reference actual code, types, and functions you found during exploration — not "how should errors be handled?" but "if cancelOrder is called on an Order with no remaining items, should it throw or no-op?"
  • Pre-populate options — faster for the user to pick than to invent from scratch
  • If you have a recommendation, make it the first option and label it "(Recommended)"
  • Use the preview field on options when mockups/code/configs help visual comparison (single-select only)

Only fall back to prose if the decision genuinely can't be reduced to discrete options.

Read the full file on GitHub · 125 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 125 lines · 57 tokens per session scan A c31fc2adb520

Subscribe to this mod's changes

grill-with-docs is a skill published in the GitHub repository twaldin/flt (5 stars, last pushed 1mo ago), licensed MIT. It adds 57 tokens to every session and 1,281 once invoked, about $0.0003 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.

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