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 flanliulf/SpecLite --skill speclite-grillinggit clone --depth 1 https://github.com/flanliulf/SpecLiteWrote 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/flanliulf/speclite/speclite-grilling)<a href="https://agentmods.dev/skills/flanliulf/speclite/speclite-grilling"><img src="https://agentmods.dev/badge/skills/flanliulf/speclite/speclite-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/flanliulf/speclite/speclite-grilling"><img src="https://agentmods.dev/badge/skills/flanliulf/speclite/speclite-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 | $0.00041 | $0.00305 |
| Opus 5.5 | $0.00016 | $0.00122 |
| Sonnet 5.5 | $0.00008 | $0.00061 |
| Haiku 4.5 | $0.00004 | $0.00030 |
Grade A, and why
speclite-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 1mo 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
就此事的每个方面持续、深入地盘问我，直到我们达成共同理解。沿着决策树的每一条分支逐步推进，逐一解决各项决策之间的依赖关系。对于每个问题，提供你推荐的答案。
每次只问一个问题，并在继续之前等待我对该问题的反馈。一次问多个问题会令人困惑。
如果某个 事实 可以通过探索环境（filesystem、tools 等）找到，就自行查找，而不是询问我。不过，决策 由我来做——把每一个决策交给我，并等待我的回答。
在我确认我们已经达成共同理解之前，不要据此采取行动。
[Generation Metadata（生成信息）]
本 Skill 由 speclite-skill-creator 自动生成。如需修改，必须同步更新 SKILL.md 与 SKILL.en.md，并同步 assets/source/speclite/core-skills/speclite-grilling/ 与实际安装副本。
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.
- 1mo ago First seen · 21 lines · 41 tokens per session scan A e9404f2ecadc
speclite-grilling is a skill published in the GitHub repository flanliulf/SpecLite (4 stars, last pushed 15d ago), licensed MIT. It adds 41 tokens to every session and 305 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-16.
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