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 agentmods add skills/tx1207/hello-scholar/grillingnpx skills add Tx1207/hello-scholar --skill grillinggit clone --depth 1 https://github.com/Tx1207/hello-scholarWrote 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/tx1207/hello-scholar/grilling)<a href="https://agentmods.dev/skills/tx1207/hello-scholar/grilling"><img src="https://agentmods.dev/badge/skills/tx1207/hello-scholar/grilling.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.00440 |
| Opus 5 | $0.00019 | $0.00220 |
| Sonnet 5 | $0.00008 | $0.00088 |
| Haiku 4.5 | $0.00004 | $0.00044 |
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 4d 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
Interview the user relentlessly until you reach a shared understanding. Map this as a design tree: every decision branches into the decisions that hang off it.
Work the tree in rounds. The frontier is every decision whose prerequisites are already settled — the questions you can ask now without guessing at answers you haven't heard yet. Each round, choose the one frontier decision with the greatest impact on the downstream design. Ask only that question, give your recommended answer, then wait for the user's response.
Format each question as a section card. Include only the option rows the decision needs:
#### Q1｜<question title>
<question body; use multiple paragraphs when needed>
- A｜<option title>: <option description and tradeoff>
- B｜<option title>: <option description and tradeoff>
- C｜<option title>: <option description and tradeoff>
Recommendation: **A**:
<reason for the recommendation>
Each answer reshapes the tree — settled decisions push the frontier outward and unblock questions that depended on them. Recompute the frontier, then choose exactly one question. A question whose answer depends on an unsettled decision belongs to a later round, not this one.
Finding facts is your job, never the user's. When a frontier question needs a fact from the environment (filesystem, tools, etc.), dispatch a sub-agent to find it — don't ask the user for anything you could look up yourself. If the selected question is still waiting on research, choose another frontier question that does not depend on that research; if none exists, wait for the research before asking. Ask only one question in every round. The decisions are the user's — put each to them and wait.
The session is done when the frontier is empty: every branch of the design tree visited, nothing left silently assumed. Do not act on it until the user confirms you have reached a shared understanding.
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.
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.
- 4d ago First seen · 30 lines · 38 tokens per session scan A 1dcb0d460d27
grilling is a skill published in the GitHub repository Tx1207/hello-scholar (5 stars, last pushed 23d ago), licensed MIT. It adds 38 tokens to every session and 440 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 2026-08-31.
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