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 znlgis/my-opencode-deepseek-config --skill grill-with-docsgit clone --depth 1 https://github.com/znlgis/my-opencode-deepseek-configWrote 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/znlgis/my-opencode-deepseek-config/grill-with-docs)<a href="https://agentmods.dev/skills/znlgis/my-opencode-deepseek-config/grill-with-docs"><img src="https://agentmods.dev/badge/skills/znlgis/my-opencode-deepseek-config/grill-with-docs.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.00291 |
| Opus 5 | $0.00016 | $0.00146 |
| Sonnet 5 | $0.00007 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
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 4d 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
Compose the grilling and domain-modeling skills when a request is ambiguous
and the project's domain terms are themselves fuzzy. Converge on intent one
question at a time while pinning down the vocabulary.
When to use
- Requirements are ambiguous (multiple interpretations with different effort).
- The domain language is inconsistent — the same concept is called different things, or a term's meaning shifts between uses.
How
- Load the
grillingskill for the question discipline: ask ONE question at a time, prefer multiple choice, until intent is clear. - Load the
domain-modelingskill for the glossary discipline: as each answer sharpens a term, record it inCONTEXT.mdinline. - Alternate: a grilling question that exposes a fuzzy term becomes a domain-modeling clarification before you continue grilling.
Rules
- Never batch questions — one at a time, per grilling.
- Never let a fuzzy term pass unexamined — if a word could mean two things, the answer is ambiguous until you pin it down.
- Stop as soon as intent is clear enough to proceed; do not over-grill.
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.
- 4d ago First seen · 33 lines · 33 tokens per session scan A d5b060982278
grill-with-docs is a skill published in the GitHub repository znlgis/my-opencode-deepseek-config (57 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 291 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 2026-09-03.
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