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 AnkitClassicVision/ankit_shared_skills --skill grill-megit clone --depth 1 https://github.com/AnkitClassicVision/ankit_shared_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/ankitclassicvision/ankit_shared_skills/grill-me)<a href="https://agentmods.dev/skills/ankitclassicvision/ankit_shared_skills/grill-me"><img src="https://agentmods.dev/badge/skills/ankitclassicvision/ankit_shared_skills/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/ankitclassicvision/ankit_shared_skills/grill-me"><img src="https://agentmods.dev/badge/skills/ankitclassicvision/ankit_shared_skills/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 | $0.00071 | $0.00826 |
| Opus 5 | $0.00036 | $0.00413 |
| Sonnet 5 | $0.00014 | $0.00165 |
| Haiku 4.5 | $0.00007 | $0.00083 |
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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grill Me
Grill the user before building. Reach shared understanding, expose contradictions, and leave durable docs or code pointers that reduce future re-explanation.
Operating loop
- Start by finding available grounding:
- User-provided docs, PRDs, specs, tickets, diagrams, transcripts.
- Existing codebase files, tests, schema/migrations, README, and package scripts.
- Domain docs such as
CONTEXT.md,UBIQUITOUS_LANGUAGE.md,docs/,architecture/,adr/, ordecisions/.
- If a question can be answered from docs or code, inspect those artifacts instead of asking.
- Ask one question at a time.
- For each question:
- State the tension or unknown.
- Give the recommended answer first.
- Offer 2-4 concrete options only when the choice is real.
- Name what code or docs evidence supports or contradicts the recommendation.
- Walk dependency-first: resolve upstream concepts, relationships, ownership, lifecycle, state, permissions, failure modes, data contracts, and naming before implementation details.
- Keep grilling until the next build step is unambiguous or the remaining blockers require human product judgment.
Docs-aware grilling
Before or during the interview, look for a bounded-context document:
- Prefer
CONTEXT.mdif present. - If absent, use the smallest relevant existing doc set and propose creating or updating
CONTEXT.mdwhen shared language emerges. - In monorepos, identify the bounded context first. Do not force a single global glossary if contexts use different language.
During grilling:
- Challenge fuzzy terms against existing glossary/docs.
- Surface terminology collisions, such as one term being used for two concepts or two terms for one concept.
- Ground terms in code: types, schemas, route names, migrations, component names, test names, and folder boundaries.
- Convert verbose phrasing into precise domain language.
- Use concrete scenarios and edge cases to test each term.
- Capture unresolved terms as open questions, not fake definitions.
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.
- 11d ago First seen · 82 lines · 71 tokens per session scan A 2414d48770e2
grill-me is a skill published in the GitHub repository AnkitClassicVision/ankit_shared_skills (11 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 826 once invoked, about $0.0004 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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