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 helderberto/agent-skills --skill grill-megit clone --depth 1 https://github.com/helderberto/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/helderberto/agent-skills/grill-me)<a href="https://agentmods.dev/skills/helderberto/agent-skills/grill-me"><img src="https://agentmods.dev/badge/skills/helderberto/agent-skills/grill-me.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 28 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00063 | $0.00421 |
| Opus 5 | $0.00032 | $0.00211 |
| Sonnet 5 | $0.00013 | $0.00084 |
| Haiku 4.5 | $0.00006 | $0.00042 |
Grade A, and why
grill-me 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
Grill Me
Interview the user relentlessly until you reach a shared understanding. Map the plan 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. Ask the whole frontier in one round: number each question and give your recommended answer. Then wait for the user's answers before the next round.
Format a round like so:
❓ **Q1 — <question title>**: <question body, may be multiple paragraphs, including multiple choices>
➡️ <your recommended answer>
---
❓ **Q2 — <question title>**: <question body>
➡️ <your recommended answer>
Each answered round reshapes the tree: settled decisions push the frontier outward and unblock the questions that depended on them. Recompute the frontier and ask the next round. A question whose answer depends on another question still open in this round belongs to a later round, not this one.
Facts are your job; decisions are the user's. If a frontier question can be answered from the codebase or environment, dispatch a subagent to find it — never ask the user for anything you could look up yourself. Don't block the round on a running lookup: only the questions downstream of it wait; ask the rest of the frontier now.
Done when the frontier is empty: every branch visited, nothing left silently assumed. Do not act until the user explicitly confirms the shared understanding — "whatever you think is best" or "you decide" is delegation, not confirmation; put the specific decision back to them.
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 · 31 lines · 63 tokens per session scan A 58d98c2c3c0c
grill-me is a skill published in the GitHub repository helderberto/agent-skills (14 stars, last pushed 7d ago), licensed MIT. It adds 63 tokens to every session and 421 once invoked, about $0.0003 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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