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 Rijul1204/rashedul-agentic-engineering --skill grill-me-codexgit clone --depth 1 https://github.com/Rijul1204/rashedul-agentic-engineeringWrote 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/rijul1204/rashedul-agentic-engineering/grill-me-codex)<a href="https://agentmods.dev/skills/rijul1204/rashedul-agentic-engineering/grill-me-codex"><img src="https://agentmods.dev/badge/skills/rijul1204/rashedul-agentic-engineering/grill-me-codex/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/rijul1204/rashedul-agentic-engineering/grill-me-codex"><img src="https://agentmods.dev/badge/skills/rijul1204/rashedul-agentic-engineering/grill-me-codex.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 | $0.00047 | $0.00394 |
| Opus 5 | $0.00023 | $0.00197 |
| Sonnet 5 | $0.00009 | $0.00079 |
| Haiku 4.5 | $0.00005 | $0.00039 |
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 9d 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
Use this skill to pressure-test a plan, architecture, or delivery approach until the key decisions, constraints, and risks are explicit.
Workflow
- Restate the target briefly so both sides are aligned.
- Explore the repo, docs, and current implementation for anything discoverable before asking questions.
- Ask one high-signal question at a time. Every question must expose a real decision, dependency, ambiguity, or risk.
- For each question, provide:
- why it matters
- your recommended answer
- what changes if the opposite answer is chosen
- Keep drilling until the following are explicit:
- goal and success criteria
- users or stakeholders
- inputs, outputs, and interfaces
- constraints and non-goals
- edge cases and failure modes
- testing and rollout expectations
- End with either:
- a concise decision-complete summary, or
- a short list of unresolved decisions that still block implementation
Rules
- Prefer repo exploration over questioning when the answer is discoverable.
- Challenge weak assumptions directly and concretely.
- Avoid filler, repetition, and generic brainstorming.
- If the user jumps to implementation before defining the problem, recover the problem statement first.
- If the plan already looks solid, focus on hidden coupling, omitted failure cases, vague acceptance criteria, and operational risk.
Output Shape
Use a compact structure:
- Current understanding
- Questions and recommended answers
- Decision summary or remaining blockers
Keep the conversation moving. The goal is not to admire the plan. The goal is to make it hard to ship something underspecified.
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.
- 9d ago First seen · 47 lines · 47 tokens per session scan A f2cb2ba1f887
grill-me is a skill published in the GitHub repository Rijul1204/rashedul-agentic-engineering (2 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 394 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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