geekx-grilling

geekx-grilling is a skill for Claude Code, Codex from geekjourneyx/geekx-skills. It costs 95 tokens per session (2,186 once invoked), scanned A, original, MIT.

A questioning workflow for pressure-testing plans, decisions, requirements, and proposed solutions. It asks one important question at a time and uses the answers to clarify facts, choices, dependencies, scope, and exclusions.

In plain words
What is it for?
Use it when you want to be challenged about a plan, compare a small number of meaningful options, build a decision tree, or remove ambiguity from a project.
Why use it?
It exposes unclear assumptions and unresolved decisions before work begins. This helps prevent choosing an implementation path while important constraints or trade-offs are still unknown.

Skill for Claude CodeCodex

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

Good fit Use it when you want to be challenged about a plan, compare a small number of meaningful options, build a decision tree, or remove ambiguity from a project.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/geekjourneyx/geekx-skills/geekx-grilling
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.

Any agent
npx skills add geekjourneyx/geekx-skills --skill geekx-grilling
Clone the repo
git clone --depth 1 https://github.com/geekjourneyx/geekx-skills

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 geekx-grilling

README.md
[![agentmods](https://agentmods.dev/badge/skills/geekjourneyx/geekx-skills/geekx-grilling/github.svg)](https://agentmods.dev/skills/geekjourneyx/geekx-skills/geekx-grilling)
Your own site
<a href="https://agentmods.dev/skills/geekjourneyx/geekx-skills/geekx-grilling"><img src="https://agentmods.dev/badge/skills/geekjourneyx/geekx-skills/geekx-grilling/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for geekx-grilling

Your own site · 80×15
<a href="https://agentmods.dev/skills/geekjourneyx/geekx-skills/geekx-grilling"><img src="https://agentmods.dev/badge/skills/geekjourneyx/geekx-skills/geekx-grilling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 95 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,186 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 $0.00095 $0.02186
Opus 5 $0.00048 $0.01093
Sonnet 5 $0.00019 $0.00437
Haiku 4.5 $0.00010 $0.00219

Measured 12d ago against content hash ce8233be1f88, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

geekx-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 12d 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.

skills/geekx-grilling/SKILL.md · 171 lines

How it starts

The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GeekX 深度追问

使命

通过一次一个高价值问题,逐项解决重大决定及其依赖,直到双方对事实、选择、范围和非目标形成明确共识。

深入细致不等于问题多。完整覆盖所有重大未决事项,同时排除不影响结论的噪音。

硬规则

  1. 一次只问一个问题,等待用户回答后再继续。
  2. 每个问题提供 2 到 3 个互斥选项。
  3. 推荐项永远排第一,并在标签中标记“(推荐)”。
  4. 每个选项都说明适用理由、主要代价或最可能失败点。
  5. 推荐项必须同时符合当前事实、当前约束和当前最佳实践,不能只靠流行度、惯例或用户预设。
  6. 能从文件、工具、上下文或环境中查到的事实,先查再问。
  7. 达成共同理解前,不实施、不写代码、不创建方案资产。
  8. 推荐答案不是用户答案。只有用户明确选择后,才能把决定标记为已确认。

提问工具

如果运行时提供 request_user_inputAskUserQuestion 或等价的结构化提问工具,任何需要用户回答的问题——包括澄清、选择、确认和最终批准——都必须调用该工具。

不要先用普通文本发问,再补一次工具调用。

工具调用遵守这个结构:

  • 问题只包含一个决策。
  • 推荐项放在第一位,标签以“(推荐)”结尾。
  • 每个选项的说明同时包含“为什么适合”和“代价是什么”。
  • 选项必须互斥,不能用同义改写凑数量。

如果运行时没有结构化提问工具,才退化为普通文本;仍须保留单题、多个选项、推荐项优先和逐项理由。

决策闭环

在会话中维护一个简洁的内部决策清单,不要预先把整份问卷展示给用户。

每个重大决定只能处于一个状态:

  • 待决:现在可以回答,但用户尚未选择。
  • 阻塞:依赖某个上游决定,暂时不能可靠回答。
  • 已确认:用户已经明确选择。
  • 已排除:因上游选择、硬约束或证据而不再适用。

重大决定是会改变目标、用户、成功标准、范围、不可逆承诺、资源分配或执行路线的选择。低成本可逆细节和纯装饰偏好不进入清单。

每轮按以下顺序执行:

  1. 探索环境,收集可自行查证的事实。
  2. 扫描当前事项的重大方面,识别重大决定及其依赖关系。
  3. 将依赖未满足的决定标记为 阻塞
  4. 从未被阻塞的 待决 项中,选择最上游、影响最大的唯一问题。
  5. 为该问题设计 2 到 3 个真实选项,先形成推荐答案,再调用提问工具。
  6. 等待用户回答,不得把推荐、沉默或模糊回应视为确认。
  7. 根据回答更新清单:
    • 用户选择的决定改为 已确认
    • 与该选择冲突且不再适用的分支改为 已排除
    • 仍然独立有效的并行分支保留为 待决
    • 依赖已经满足的分支从 阻塞 改为 待决
  8. 重新扫描回答是否引入新的重大决定,然后进入下一轮。

沿着决策树逐项推进,不等于穷举所有假想未来。关闭已经失效的分支,但不能遗漏仍会改变结果的独立分支。

推荐项推导

推荐项必须能用以下五项公开说明:

  1. 目标:当前真正要改善什么结果。
  2. 事实:已有证据和现状是什么。
  3. 约束:时间、资源、兼容性和不可违反条件是什么。
  4. 代价:复杂度税、机会成本和回滚成本是什么。
  5. 可逆性:哪个选择能用最小承诺获得最多信息。

如果“当前最佳实践”可能随时间、价格、产品能力或规则变化,先用可用工具查阅官方或一手资料。无法验证时,明确标记为基于现状的推断,不要把记忆写成已确认事实。

第一性原理不是把思考写得很长,而是让结论能从目标、事实和约束直接推出。

对推荐项做一次逆向检查:

  • 如果推荐项错了,最可能错在哪里?
  • 什么新证据会让推荐发生变化?
  • 不选推荐项,最可能付出什么额外成本?

把关键结论压缩进推荐理由,不展示冗长思维过程。

选项质量

每个备选项都必须是经过思考的真实路线,不得把明显荒谬的选项当陪衬。

选项说明至少回答:

  • 它在什么条件下更合理?
  • 它比推荐项多承担什么代价或风险?

如果只有一个合理答案,不要伪造多个方案。把决策改写为“现在执行 / 先验证 / 暂不执行”等真实分支。

反噪音与反过度设计

  • 优先问高信息增益问题,不按主题清单机械盘问。
  • 优先确认目标和成功标准,再讨论实现。
  • 优先小而可逆的选择,再讨论长期架构。
  • 不因用户要求“全面”就设定问题数量。
  • 不把未来可能性当成当前需求。
  • 不重复询问已经明确或可以推导的内容。
  • 不因已提问数量、会话轮次或“感觉差不多”而提前停止。

失败分支

情况 必须这样处理
结构化提问工具可用 必须调用工具;禁止只发普通文本问题。
结构化提问工具不可用 用普通文本给出一个问题、2 到 3 个选项和逐项理由。
用户要求一次列出全部问题 拒绝批量轰炸,只问最上游的一个问题。
用户要求推荐指定答案 仍按事实和约束推导;若不成立,明确推荐别的选项。
用户回答“都可以”或“不确定” 保持状态为 待决,重述推荐项及其代价,再请求确认,不扩展新问题。
用户要求把推荐项视为已确认 STOP:推荐不等于决定;继续等待用户明确选择。
用户选择非推荐项 接受选择并更新分支;只有违反硬约束时才指出冲突。
用户回答使一个分支失效 标记为 已排除,不要继续追问该分支。
一个决定完成但仍有独立重大决定 保留为 待决,下一轮继续处理,不能宣布完成。
所有重大决定已关闭 进入共同理解确认,不制造边缘问题。
用户要求立即行动但共识未确认 STOP:先完成共同理解确认。

Read the full file on GitHub · 171 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. 12d ago First seen · 171 lines · 95 tokens per session scan A ce8233be1f88

Subscribe to this mod's changes

geekx-grilling is a skill published in the GitHub repository geekjourneyx/geekx-skills (24 stars, last pushed 5d ago), licensed MIT. It adds 95 tokens to every session and 2,186 once invoked, about $0.0005 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 2026-08-30.

Related

Other skills, from other repositories

agent-wiki

Incremental LLM-friendly wiki generator for Obsidian note vaults. Use when: (1) Building wiki from notes, (2) Ingesting notes to wiki, (3) Obsidian LLM wiki, (4) Incremental knowledge base management. Triggers: 'build wiki from notes', 'ingest notes to wiki', 'Obsidian LLM wiki', 'incremental knowledge base'.

Dianel555/DSkills · 89 tokens

ace-tool

Semantic codebase search, code indexing, and prompt enhancement via standalone CLI. Use when: (1) Semantic code search with natural language queries, (2) Code indexing for remote codebase retrieval, (3) Prompt enhancement with codebase context, (4) Before grep/find/glob operations for better accuracy, (5) Complex…

Dianel555/DSkills · 124 tokens

github-trending-analyzer

Crawl GitHub trending repositories, analyze with LLM for Chinese insights, categorize by themes, compute diffs against history, and generate Markdown reports. Default brief mode stops at trend analysis; optional detailed mode appends per-project analysis. Supports incremental gap-filling and selective re-analysis with…

Dianel555/DSkills · 65 tokens

capability-evolver

Self-evolution workflow for the agent. Before substantive work, recall past outcomes from evolution memory; while editing, detect improvement signals; at task end, record the outcome; when reusable, distill or search the EvoMap network for proven genes/capsules. Use when the user starts non-trivial work (a feature, a…

Dianel555/DSkills · 98 tokens

cc-agy

Delegates coding/research tasks to the Google Antigravity CLI (agy) for external-model execution (Gemini 3.x, Claude Sonnet/Opus 4.6, GPT-OSS). Replaces the broken collaborating-with-gemini skill. Use when: (1) External-model delegation via Antigravity, (2) Multi-model prototyping (switch model per call), (3)…

Dianel555/DSkills · 187 tokens

context7

Fetch up-to-date library/framework/API documentation from Context7, bypassing training-cutoff limits. Use when: (1) User asks how to use/configure/install a library, framework, or SDK, (2) Code examples or API reference needed for a specific package, (3) Version-specific behavior questions (e.g., "React 19", "Next.js…

Dianel555/DSkills · 193 tokens