super-plumber: Skill for Codex

.pi/skills/sp-grilling/SKILL.md

sp-grilling is a skill for Codex from LUKAWI/super-plumber. It costs 84 tokens per session (1,413 once invoked), scanned A, original, MIT.

A guided questioning skill for aligning requirements, reviewing task maps, examining decisions, changing earlier decisions, and checking finished work. It asks one question at a time and gives a recommended answer.

In plain words
What is it for?
Use it to review a plan or result, pressure-test a decision, clarify requirements, or decide how tasks and architecture decision records should change.
Why use it?
It helps uncover unclear requirements and weak assumptions before changes are made. It keeps decisions with the user while checking facts in the project itself.

Skill for Codex

Written for Codex: agents/openai.yaml present.

This is LUKAWI/super-plumber's own configuration. It tells Codex how to work on super-plumber itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything super-plumber configures →

Reuse

Borrowing it

Nothing to install: this file belongs to LUKAWI/super-plumber. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/LUKAWI/super-plumber/master/.pi/skills/sp-grilling/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/LUKAWI/super-plumber

Made for: 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 sp-grilling

README.md
[![agentmods](https://agentmods.dev/badge/skills/lukawi/super-plumber/sp-grilling.svg)](https://agentmods.dev/skills/lukawi/super-plumber/sp-grilling)
Your own site
<a href="https://agentmods.dev/skills/lukawi/super-plumber/sp-grilling"><img src="https://agentmods.dev/badge/skills/lukawi/super-plumber/sp-grilling.svg" alt="Measured on agentmods" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,413 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00084 $0.01413
Opus 5 $0.00042 $0.00707
Sonnet 5 $0.00017 $0.00283
Haiku 4.5 $0.00008 $0.00141

Measured yesterday against content hash 68c06caf6977, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

sp-grilling 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 yesterday.

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.

.pi/skills/sp-grilling/SKILL.md · 47 lines

How it starts

The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SP Grilling — 纪律技能:一次一问的意图对齐与决策拷问

Overview

  • 定位:SP 自带纪律技能族成员(DEC-6 ③,adr_0014 的 skill 面)——MP grilling 本体的忠实移植 + SP 落点附录。工作流全周期的统一对话核心:需求与方向对齐、serve 人审对图质检、开发中决策、改决定、成品审核。
  • 仅用户主动调用:不由 agent 或其它 skill 自动接入。普通需求澄清、设计审核不等于开启 grilling;本技能不是审核前置门禁。仍不单独分发 command。
  • 本页结构:本体协议(忠实移植,勿改)→ 强度分档 → SP 落点附录(共识后的结论如何落图)。

本体协议(一次一问,直到共识)

  1. 无情访谈到共识:就当前的计划/决策/想法的每一个方面对我无情追问,直到我们达成共识的理解。沿决策树的每个分支走下去,把决策之间的依赖逐一解开。每个问题都附上你的推荐答案
  2. 一次一问:一次只问一个问题,等我给出反馈后再继续。一次抛出多个问题令人不知所措。
  3. 事实自查,决策归人:凡是能通过探查环境查到的事实(文件系统、graph CLI/MCP 工具、代码、图内状态),自己查,不要问我;决策是我的——把每一个决策摆到我面前,等我的答复。
    • SP 语境对照——事实:某节点当前状态、某 ADR 是否已 superseded、validate 是否 0 error、某文件是否存在;决策:节点该拆还是该合、ADR 够不够三判据、任务定 quick 还是 standard、方案选哪条。
  4. 共识前不动手:在我确认我们已达成共识之前,不要动手执行任何落图/改图/施工动作。

强度分档

档位 何时用 深挖强度
quick 轻量档 经 plumber-design Phase 0 路由定档为 quick 的任务 少轮次:只对齐目标验收各一问(附推荐答案),不逐分支深挖;两问得到答复即共识
standard / program 其余全部(含路由不明的任务) 全量深挖:本体协议逐条走满——决策树逐支、依赖逐一、每问附推荐答案,直到共识闭合

档位不明确时按高档执行:宁可多问,不可漏问。

雾区豁免(IL-026;依据 adr_0007:雾区只提示不阻止):对图上登记了雾区(fog)的点位,只拷问一问——「毕业条件(graduation)是否可验证/可观测」,不按 standard 档粒度逐支深挖:认知未到处不假装精确,雾区内部的问题留待 research 解雾后再拷。话术互指:雾区在 web-ui serve 的 chart 模式可见,毕业走 graph graduate-fog(手册 §2.2)。

SP 落点附录:访谈结论四路落图

本体协议跑完、共识达成之后,把结论按性质路由到 SP 资产落位。路由只在共识后追加落图动作,不改变本体协议本身:

  1. 工作类定档(这个活是什么量级)→ 回 plumber-design Phase 0 路由表顺序定档:关键未知阻止形成可信交付计划则 program;否则按一个会话能否完成并验收选 quick / standard,跨会话或跨图不单独触发 program(DEC-2):.pi/skills/plumber-design/SKILL.md
  2. 设计决策(难逆转 + 脱离上下文令人费解 + 真实权衡,ADR 三判据全满足)→ graph adr create 落 ADR 顶点(状态 proposed,accept/supersede 裁决归 Super Mario/人类),再以 decides 边挂到管辖的节点/context。
  3. 改决定(图已画好要改)→ 按 DEC-7 改图协议分流:
    • 小修(不动结构:节点 plan/DoD 文案、checkpoint 增删)→ 归 plumber-execute 上报出口(WF16):worker 提议、执行报告注明"计划已修订";
    • 结构修订(增删节点/边、拆分节点、取消子树、ADR supersede 连锁失效)→ 归 designer amend 模式(增量 validate + 影响评估 + 增量人审);执行者不自己改结构。
  4. 审批对话(serve 人审中或审核结论)→ DEC-1 凭据话术:用户批准后由 designer 调一次 graph approve --by <审核者> 落审批凭据(quick 档 init 后自签);对话本身仍按本体协议走,凭据是落点不是替代。

Read the full file on GitHub · 47 lines

Files

What ships with it

1 file 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. yesterday Changed · -107 tokens per session 68c06caf6977
  2. 4d ago Changed · +2 lines 42ed27e4f2d0
  3. 8d ago First seen · 45 lines · 191 tokens per session scan A dec39e0c6a5d

Subscribe to this mod's changes

sp-grilling is a skill published in the GitHub repository LUKAWI/super-plumber (3 stars, last pushed yesterday), licensed MIT. It adds 84 tokens to every session and 1,413 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

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens