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 markoblogo/abvx-agent-skills --skill doc-grounded-grillinggit clone --depth 1 https://github.com/markoblogo/abvx-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/markoblogo/abvx-agent-skills/doc-grounded-grilling)<a href="https://agentmods.dev/skills/markoblogo/abvx-agent-skills/doc-grounded-grilling"><img src="https://agentmods.dev/badge/skills/markoblogo/abvx-agent-skills/doc-grounded-grilling/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/markoblogo/abvx-agent-skills/doc-grounded-grilling"><img src="https://agentmods.dev/badge/skills/markoblogo/abvx-agent-skills/doc-grounded-grilling.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 | $0.00083 | $0.00558 |
| Opus 5 | $0.00042 | $0.00279 |
| Sonnet 5 | $0.00017 | $0.00112 |
| Haiku 4.5 | $0.00008 | $0.00056 |
Grade A, and why
doc-grounded-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 10d 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Doc Grounded Grilling
Use structured questioning to align a plan with the repo's actual language, constraints, and existing decisions.
Workflow
- Read the nearest relevant context first:
AGENTS.mddocs/ai/*- ADRs
- repo docs
designmd-brand-kitartifacts when frontend or brand work is involved
- Ask one question at a time.
- If the answer is already in the code or docs, verify there before asking.
- For each question:
- identify the ambiguity;
- give a recommended answer or framing;
- wait for user feedback before continuing.
- Walk down the branches of the design tree until:
- terms are precise;
- boundaries are understood;
- key trade-offs are named;
- critical scenarios are covered.
- When a term or decision settles, classify the durable artifact:
- glossary/context update for canonical domain language;
- ADR candidate for hard-to-reverse or surprising trade-offs;
- PRD/spec note for scope and acceptance criteria;
- no artifact when the answer is temporary or already documented.
What To Challenge
- terminology that conflicts with existing domain language;
- assumptions contradicted by code or ADRs;
- vague nouns like "account", "session", "client", "job", "draft", "campaign";
- plans that skip the test seam, integration seam, or rollout seam;
- frontend ideas that ignore the current design system or brand shape.
Output
The session should leave behind:
- sharper language;
- clarified decisions;
- explicit open questions;
- identified docs that should be updated through
durable-context-maintenancewhen the decision settles; - proposed glossary/context or ADR updates when the task changed the repo's shared language or a consequential decision.
Guardrails
- Do not interrogate for its own sake; stop when the plan is clear enough to execute.
- Do not invent domain language when the repo already has one.
- Do not batch ten questions at once.
Final Report
Summarize resolved terms, decisive trade-offs, remaining open questions, and which docs should be refreshed next.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 66 lines · 83 tokens per session scan A 8cd43ca8e84d
doc-grounded-grilling is a skill published in the GitHub repository markoblogo/abvx-agent-skills (16 stars, last pushed yesterday), licensed MIT. It adds 83 tokens to every session and 558 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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