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.
npx skills add devcxl/mattpocock-skills-zh --skill grillinggit clone --depth 1 https://github.com/devcxl/mattpocock-skills-zhWrote 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.
[](https://agentmods.dev/skills/devcxl/mattpocock-skills-zh/grilling)<a href="https://agentmods.dev/skills/devcxl/mattpocock-skills-zh/grilling"><img src="https://agentmods.dev/badge/skills/devcxl/mattpocock-skills-zh/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.
<a href="https://agentmods.dev/skills/devcxl/mattpocock-skills-zh/grilling"><img src="https://agentmods.dev/badge/skills/devcxl/mattpocock-skills-zh/grilling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.00483 |
| Opus 5 | $0.00022 | $0.00242 |
| Sonnet 5 | $0.00009 | $0.00097 |
| Haiku 4.5 | $0.00004 | $0.00048 |
Grade A, and why
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 10d 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.
What it actually says
持续盘问用户，直到你们达成共识。将讨论映射为一棵设计树（design tree）：每个决策都会分支出一系列依赖它的子决策。
以**轮次（rounds）**推进这棵树。**前沿（frontier）**是所有前提已确定的决策：即你现在可以问的问题，无需猜测尚未听到的答案。每一轮问完整个前沿：为每个问题编号，并给出你的推荐答案。然后等待用户的回答，再进行下一轮。
每个问题格式如下：
❓ **Q1** - **<问题标题>**：<问题正文，可以是多段，包括多个选项>
➡️ <你的推荐答案>
---
❓ **Q2** - **<问题标题>**：<问题正文，可以是多段，包括多个选项>
➡️ <你的推荐答案>
每一轮用户的回答都会重塑这棵树：已确定的决策把前沿向外推，解锁依赖它们的问题。重新计算前沿，进入下一轮。某个问题的答案依赖本轮中另一个仍未回答的问题时，它属于更晚的轮次，而不是本轮。
寻找事实是你的工作，永远不是用户的。当前沿问题需要来自环境的事实（文件系统、工具等）时，派一个子代理去查；不要问用户任何你自己能查到的东西。不要阻塞等待：正在进行的探查是一个未解决的前提，只有它下游的问题需要等子代理回报；现在就把前沿其余部分问完。决策是用户的：把每个决策摆给他们，然后等待。
当前沿为空时，会话结束：设计树的每条分支都已遍历，没有任何东西被默默假设。在用户确认你们达成共识之前，不要付诸行动。
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.
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.
- 10d ago First seen · 29 lines · 43 tokens per session scan A 99004d0d6747
grilling is a skill published in the GitHub repository devcxl/mattpocock-skills-zh (331 stars, last pushed 5d ago), licensed MIT. It adds 43 tokens to every session and 483 once invoked, about $0.0002 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.
Other skills, from other repositories
chinese-documentation
A Chinese technical-documentation style guide covering spacing, punctuation, numbers, terminology, and links when Chinese and English appear together.
chinese-code-review
A Chinese-language code-review communication guide with templates and severity levels for review comments.
chinese-commit-conventions
A Chinese-language guide to Conventional Commits, a format for writing consistent Git commit messages, plus related changelog, commit-checking, and commit-helper configuration.
systematic-debugging
A step-by-step method for finding the underlying cause of technical problems before changing code. It covers reading errors, reproducing failures, checking recent changes, and tracing data across system components.
dispatching-parallel-agents
A workflow for assigning separate coding agents to independent tasks that do not share state or depend on one another. Each agent receives a focused scope, constraints, and an expected result.
executing-plans
A procedure for carrying out a written software implementation plan in a separate session, including reviewing the plan, completing its tasks, and checking the results at defined review points.