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 aivrar/portable-hermes-agent --skill grill-megit clone --depth 1 https://github.com/aivrar/portable-hermes-agentWrote 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/aivrar/portable-hermes-agent/grill-me)<a href="https://agentmods.dev/skills/aivrar/portable-hermes-agent/grill-me"><img src="https://agentmods.dev/badge/skills/aivrar/portable-hermes-agent/grill-me/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/aivrar/portable-hermes-agent/grill-me"><img src="https://agentmods.dev/badge/skills/aivrar/portable-hermes-agent/grill-me.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 | $0.00012 | $0.01083 |
| Opus 5 | $0.00006 | $0.00541 |
| Sonnet 5 | $0.00002 | $0.00217 |
| Haiku 4.5 | $0.00001 | $0.00108 |
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 7d 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.
This is a copy
100% identical to grill-me — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grill Me
Stress-tests a plan through structured adversarial questioning before any code is written. Models the plan as a design tree — every decision branches into the decisions that hang off it — and interviews the user in rounds until every branch is resolved and nothing is silently assumed.
Combines the phase discipline of the original with the frontier-rounds
mechanic from mattpocock/skills' grilling.
When to Use
- User says "grill me", "interview my plan", "stress test this idea"
- Before complex work: auth flows, schema changes, migrations, payments
- A plan has unresolved decisions or seems vague
- Before
subagent-driven-developmentdecomposition
Do NOT use for existing code (use requesting-code-review) or simple one-off
tasks.
Prerequisites
None. The skill works on any plan or raw idea.
Core Mechanic: Frontier Rounds
Map the plan as a design tree. 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.
Work in rounds: ask the whole current frontier in one message, numbered, each question carrying your recommended answer. Then wait. A question whose answer depends on another question still open in this round belongs to a LATER round, not this one.
Format each round like so:
❓ Q1 — <question title>: <question body, options if relevant>
➡️ Recommendation: <your recommended answer + one-line why>
❓ Q2 — <question title>: <question body>
➡️ Recommendation: <...>
Each answer reshapes the tree: settled decisions push the frontier outward and unblock dependent questions. Recompute the frontier and ask the next round.
Facts are your job; decisions are the user's. When a frontier question
needs a fact from the environment (codebase, filesystem, config, docs), find
it yourself with search_files / read_file / terminal — or dispatch a
subagent via delegate_task for a heavy exploration. Never ask the user for
anything you could look up. Don't block on an exploration: only the questions
downstream of it wait; ask the rest of the frontier now.
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.
- 7d ago First seen · 118 lines · 12 tokens per session scan A 6e3b3b81c1ad
grill-me is a skill published in the GitHub repository aivrar/portable-hermes-agent (217 stars, last pushed 2d ago), licensed MIT. It adds 12 tokens to every session and 1,083 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to grill-me, differing in 0 lines, and is treated as a copy.
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