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 chaunsin/agent-skills --skill grillgit clone --depth 1 https://github.com/chaunsin/agent-skillsWrote 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/chaunsin/agent-skills/grill)<a href="https://agentmods.dev/skills/chaunsin/agent-skills/grill"><img src="https://agentmods.dev/badge/skills/chaunsin/agent-skills/grill/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/chaunsin/agent-skills/grill"><img src="https://agentmods.dev/badge/skills/chaunsin/agent-skills/grill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00051 | $0.00543 |
| Opus 5.5 | $0.00020 | $0.00217 |
| Sonnet 5.5 | $0.00010 | $0.00109 |
| Haiku 4.5 | $0.00005 | $0.00054 |
Grade A, and why
grill 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 24d 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
grill
反复与用户访谈，直到达成共识。将此过程绘制成 设计树：每个决策都会衍生出后续的决策。
流程
分轮处理决策树。边界 是指所有前提条件已经确定的决策：即你 现在 可以提出的问题，而无需猜测你尚未听到的答案。在一轮中询问整个边界：给每个问题编号并给出你的建议答案。然后等待用户的回复，之后再进行下一轮。
格式如下：
❓ **Q1** - **<问题标题>**: <question body, might be multiple paragraphs, including multiple choices>
➡️ <你推荐的答案>
用户每回答一轮问题，问题树就会重塑：已确定的答案会将边界向外推移，并解锁依赖于这些答案的问题。重新计算边界，然后进行下一轮提问。如果某个问题的答案依赖于本轮中尚未解决的问题，则该问题属于 后续 轮次，而非本轮。
寻找 事实 是你的工作，而不是用户的。当一个前沿问题需要从环境（文件系统、工具等）中获取事实时，派出一个子代理去查找；不要向用户询问任何你可以自己查找的信息。不要因此而阻塞：正在进行的探索是一个尚未确定的前提条件，因此只有其下游的问题才需要等待子代理的报告；现在就可以向前沿问题的其他部分提出请求。决策权 在用户手中：把每个问题都交给他们，然后等待。
注意: 每次只提问一个问题，避免提问所有问题。
保存
引导用户保存文档，当设计树的每个分支都已遍历完毕，没有任何未加假设的内容时，会议即告结束。在用户确认已达成共识之前，请勿采取任何行动。
**是否保存文档**
A. docs/grill/grill-<subject>.md (推荐)
B. 不保存留在原地
C. 自定义目录或其他说明
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.
- 24d ago Changed · +2 lines 9096ef92c38e
- 1mo ago First seen · 37 lines · 51 tokens per session scan A 19d057f001a4
grill is a skill published in the GitHub repository chaunsin/agent-skills (2 stars, last pushed 25d ago), licensed Apache-2.0. It adds 51 tokens to every session and 543 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-11.
Other skills, from other repositories
make_plan
For external plan request scenarios, guides the Agent to request a clear, actionable, step-by-step plan from a stronger Agent via listagents and chatwithagent, emphasizing that the plan is executed by the requester, not by the consulted Agent.
gpt-image-2
A skill for generating or editing images with GPT Image 2 across local, host-provided, or advisory setups.
motion-showreel
A code-based workflow for making short videos built from animated graphics, text, logos, or interface elements. It produces MP4 video and editable source code rather than filming or editing existing footage.
new
Create a new project to start development quickly.
officecli-word-form
Use this skill to create fillable Word forms (.docx) with real Content Controls (SDT) + legacy FormField checkboxes + MERGEFIELD mail-merge placeholders + document protection. Trigger on: 'fillable form', 'form fields', 'content controls', 'SDT', 'word form', 'fill in', 'only editable fields', 'protect document'…
officecli-data-dashboard
Use this skill to build a multi-element Excel dashboard — Dashboard sheet on open, multiple formula-driven KPI cards, multiple charts, sparklines, and conditional formatting — from CSV or tabular input. Trigger on: 'dashboard', 'KPI dashboard', 'analytics dashboard', 'executive dashboard', 'metrics dashboard', 'CSV to…