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 dgilford/ai-science-toolkit --skill grillinggit clone --depth 1 https://github.com/dgilford/ai-science-toolkitWrote 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/dgilford/ai-science-toolkit/grilling)<a href="https://agentmods.dev/skills/dgilford/ai-science-toolkit/grilling"><img src="https://agentmods.dev/badge/skills/dgilford/ai-science-toolkit/grilling.svg" alt="Measured on agentmods" 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 | $0.00092 | $0.00468 |
| Opus 5 | $0.00046 | $0.00234 |
| Sonnet 5 | $0.00018 | $0.00094 |
| Haiku 4.5 | $0.00009 | $0.00047 |
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 8d 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 me relentlessly about every aspect of this plan until we reach a shared understanding. Walk down each branch of the design tree, resolving dependencies between decisions one-by-one. For each question, provide your recommended answer.
Ask the questions one at a time, waiting for feedback on each question before continuing. Asking multiple questions at once is bewildering.
If a fact can be found by exploring the codebase, look it up rather than asking me. The decisions, though, are mine — put each one to me and wait for my answer.
Do not enact the plan until I confirm we have reached a shared understanding.
When to grill proactively
"If in doubt" is too weak a trigger — an agent handed a concrete task rarely feels in doubt, even when it hides consequential decisions. Grill before acting, not only when asked, whenever a step would:
- change or restart a running service or process (a training run, a server, a scheduled job);
- allocate a shared resource — GPUs, ports, memory, disk, a rate-limited API quota;
- edit an interdependent config whose blast radius you cannot fully see;
- invalidate or contradict a decision already made this session.
In these cases, surface the conflict explicitly and grill on how to resolve it before proceeding.
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.
- 8d ago First seen · 32 lines · 92 tokens per session scan A ca6d159a9eb3
grilling is a skill published in the GitHub repository dgilford/ai-science-toolkit (62 stars, last pushed 19d ago), licensed MIT. It adds 92 tokens to every session and 468 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.
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