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 ntaffzii/Skill-Agents --skill grill-with-docsgit clone --depth 1 https://github.com/ntaffzii/Skill-AgentsWrote 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/ntaffzii/skill-agents/grill-with-docs)<a href="https://agentmods.dev/skills/ntaffzii/skill-agents/grill-with-docs"><img src="https://agentmods.dev/badge/skills/ntaffzii/skill-agents/grill-with-docs.svg" alt="Measured on agentmods" 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 | $0.00057 | $0.00418 |
| Opus 5 | $0.00028 | $0.00209 |
| Sonnet 5 | $0.00011 | $0.00084 |
| Haiku 4.5 | $0.00006 | $0.00042 |
Grade A, and why
grill-with-docs 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.
What it actually says
Grill With Docs
Use this skill before implementation when alignment matters.
Workflow
-
Establish intent
- Ask what outcome the user wants, who it is for, and what must not change.
- Identify success criteria and failure modes.
-
Challenge scope
- Find the smallest useful version.
- Ask what can be deferred.
- Surface hidden dependencies, permissions, data needs, and integration points.
- Separate must-have, should-have, nice-to-have, and out-of-scope items when the request is large.
-
Build shared language
- Name the domain concepts in the user's words.
- Define ambiguous terms.
- Prefer one precise term over repeated explanatory phrases.
-
Convert decisions into docs
- Create or update lightweight docs only when they will help future sessions.
- Use PRD for product behavior.
- Use ADR for architectural decisions.
- Use glossary/context docs for domain language.
-
End with an execution-ready brief
- Goals
- Non-goals
- Decisions
- Open questions
- First implementation slice
- Validation plan
Question Rules
- Ask the fewest questions that unblock execution.
- Group related questions.
- Do not interview forever; once enough context exists, recommend a path.
- If the user is absent, make conservative assumptions and label them.
Verification
- The brief has a clear goal and non-goals.
- Decisions are separated from open questions.
- The first implementation slice is small enough to execute.
- Any assumptions are labeled.
Output Format
End with:
- Goals
- Non-goals
- Scope
- Decisions
- Open questions
- First implementation slice
- Validation plan
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 · 66 lines · 57 tokens per session scan A 104726b88e68
grill-with-docs is a skill published in the GitHub repository ntaffzii/Skill-Agents (4 stars, last pushed 5d ago), licensed MIT. It adds 57 tokens to every session and 418 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 2026-08-31.
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