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.
git clone --depth 1 https://github.com/majiayu000/spellbookWrote 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/commands/majiayu000/spellbook/idea)<a href="https://agentmods.dev/commands/majiayu000/spellbook/idea"><img src="https://agentmods.dev/badge/commands/majiayu000/spellbook/idea/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/commands/majiayu000/spellbook/idea"><img src="https://agentmods.dev/badge/commands/majiayu000/spellbook/idea.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 | $0.00035 | $0.00163 |
| Opus 5.5 | $0.00014 | $0.00065 |
| Sonnet 5.5 | $0.00007 | $0.00033 |
| Haiku 4.5 | $0.00003 | $0.00016 |
Grade A, and why
idea scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
按本插件的 idea-to-product skill 执行想法到产品的完整流程。
- 用户输入：$ARGUMENTS
- 参数为空时，先问用户要一句话想法，不要自己编
resume/list/export分支按该 skill 的「命令变体」一节处理- 严格遵守该 skill 的 7 阶段顺序、Pre-下一阶段 checklist 和 Red Flags 表
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 · 12 lines · 35 tokens per session scan A 9d4642dc0f71
idea is a command published in the GitHub repository majiayu000/spellbook (288 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 163 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
todo
The quality-gated task list: tasks with real descriptions, testable acceptance criteria, and evidence — a task only closes when the controller agrees it is done.
sota-close
End-of-session closure pass — retract what proved wrong and correct it everywhere it reached, hand off open items where the next session will trip over them, update the docs this session made false, re-derive every number from its source, and commit the evidence. Run it at the END of a working session.
sota-report
Write a SOTA-skills field report for this session — where the guidance failed, was absent, was wrong, or was right and did not fire. Run it at the END of a working session, while the history is still in context.
thoughts
Quick honest take — share thoughts, concerns, or better ideas about the current discussion without a heavy audit.
aic-skills
Show all available AIContext skills grouped by workflow stage.
recap
Write an end-of-session recap — request / investigated / learned / completed / next-steps — with propose-confirm-commit flow and optional promotion of Learned items.