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 Dong90/oh-my-taiyiforge --skill taiyi-intel-scangit clone --depth 1 https://github.com/Dong90/oh-my-taiyiforgeWrote 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/dong90/oh-my-taiyiforge/taiyi-intel-scan)<a href="https://agentmods.dev/skills/dong90/oh-my-taiyiforge/taiyi-intel-scan"><img src="https://agentmods.dev/badge/skills/dong90/oh-my-taiyiforge/taiyi-intel-scan/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/dong90/oh-my-taiyiforge/taiyi-intel-scan"><img src="https://agentmods.dev/badge/skills/dong90/oh-my-taiyiforge/taiyi-intel-scan.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00045 | $0.01160 |
| Opus 5.5 | $0.00018 | $0.00464 |
| Sonnet 5.5 | $0.00009 | $0.00232 |
| Haiku 4.5 | $0.00005 | $0.00116 |
Grade A, and why
taiyi-intel-scan 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.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
taiyi-intel-scan
目的
在写 CHANGE / REQUIREMENT 之前,把与本次变更相关的代码现实整理成一份可读情报,避免设计阶段凭空假设、重复造轮子或踩遗留坑。
何时使用
| 信号 | 建议 |
|---|---|
新 slug 刚 taiyi init |
默认跑一次 |
taiyi_assess 为 medium / high |
必跑 |
| 不熟悉模块 / 跨多目录 | 必跑 |
| 单文件 typo 修复 | 可跳过 |
何时不用
- 变更范围已在当前会话完全掌握
- 纯文档 / 配置一字节代码不动(仍建议扫依赖与 CI)
输入
- 用户意图或 Issue 摘要
- (可选)
CHANGE.md草稿中的 Scope - 项目根目录只读访问
输出
- 首选:
.taiyi/changes/<slug>/CONTEXT.md(可从templates/CONTEXT.md种子起步) - 多变更共享基线:
.taiyi/CONTEXT.md(在文件头注明shared: true与适用 slug)
执行步骤
1. 划定扫描边界
- 从用户描述提取 3–7 个关键词(模块名、路由、表名、API 前缀)
- 用
grep/ 语义搜索定位入口文件(路由注册、CLI、main、index) - 列出直接相关目录(不超过 15 个),注明「必读 / 参考 / 勿动」
2. 提取模式(Pattern Inventory)
记录项目既有惯例,后续阶段必须对齐:
| 类别 | 记录什么 | 示例 |
|---|---|---|
| 目录结构 | 功能放哪 | src/core/ vs lib/ |
| 命名 | 文件、导出、测试后缀 | *.test.ts / test_*.py |
| 测试 | 框架、运行命令、覆盖率习惯 | vitest run |
| API / 数据 | REST 风格、ORM、错误形状 | { ok, error } |
| 配置 | 环境变量、feature flag 位置 | .env.example |
3. 风险区标注
标 RISK(无测试、TODO 堆积、循环依赖、上帝文件)并给证据路径:
- 文件路径 + 行号或符号名
- 为何影响本变更(一句话)
- 建议:绕行 / 补测试 / 单独 slice
4. 阅读清单(Read First)
给出 3–5 个文件,按顺序,每文件一句话说明「读完知道什么」。
5. 与下游衔接
在文末写 Handoff:
- 对
taiyi-change:Scope 建议、Out of scope 提醒 - 对
taiyi-design:可复用组件、禁止重写的子系统 - 若发现架构级未知:建议
taiyi-architect
CONTEXT.md 模板
# CONTEXT: <slug>
> 生成:taiyi-intel-scan · 只读扫描,非设计结论
## Scope 摘要
<!-- 一句话 -->
## 相关目录
| 路径 | 关系 | 备注 |
|------|------|------|
| | 必读 / 参考 / 勿动 | |
## 模式清单
- 测试:`...`
- API:`...`
- 命名:`...`
## 风险区
| 级别 | 位置 | 说明 | 建议 |
|------|------|------|------|
| RISK | `path:line` | | |
## Read First
1. `path` — …
2. `path` — …
## Handoff
- change:…
- design:…
质量自检
- 每条结论有路径证据,无「据说」「可能」式空话
- 未在本 Skill 内改业务代码(只读)
- 篇幅可控:CONTEXT 建议 80–200 行,过长则拆「附录:文件索引」
- 与
CHANGE.mdScope 无矛盾;有矛盾则在 Handoff 标明
与工具链
- OpenCode:
taiyi_assess推荐本 Skill 时自动出现在 guide - 复杂仓库可叠加其他 codebase 类 Skill,摘要写入 CONTEXT,不替代本工件
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 · 134 lines · 45 tokens per session scan A 07e5cdb9cc09
taiyi-intel-scan is a skill published in the GitHub repository Dong90/oh-my-taiyiforge (859 stars, last pushed 16d ago), licensed MIT. It adds 45 tokens to every session and 1,160 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 2026-08-30.
Other skills, from other repositories
business-requirements
Read and hand-edit the app's business requirements — the checklist the harness verifies the built app against. MUST be loaded whenever the user asks to add, change, remove, reword, re-prioritise, or reclassify a business requirement (e.g. "add a requirement that…", "that rule is wrong, fix it", "drop the requirement…
first-run-open
Owns the opening move of first-run when the user has NOT handed you a substantive prompt (cold start), and sets the voice-vs-text opening posture for any open. Shows a provisional dream and a guess about who the user is, then learns from their correction (show-to-learn) and re-aims. Hands back to the first-run spine…
disqualification
The honest exit. Loads when qualification signals sustained-low or a realism failure (the ask is genuinely outside QB's wheelhouse). Acknowledges the mismatch plainly, suggests a realistic alternative, preserves dignity, and does not chase. A legitimate designed outcome, not a framework failure.
qualification
Reads qualification signals from the user's input and passive context, sets the archetype and effort mode, and decides whether to proceed up the convince ladder or route to the disqualification skill. Runs alongside the first-run spine from the first substantive message onward. Falls back to "proceed at normal effort"…
build-recovery
Owns the build wait and build failure. Narrates the generation honestly while it runs, and when it errors, names the failure plainly with a real recovery path instead of a generic "oops". Loads when generation is long or returns an error. The single highest-risk moment for the "it's actually building" belief.
chat-formatting-widgets
Governs the custom markdown widgets rendered in the QuantumByte chat interface. This includes the inline highlight-mark span (use on every question the user must answer). You must check this skill on every reply to format highlights.