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 liuxinye23/CyberStrikeAI --skill tls-configuration-reviewgit clone --depth 1 https://github.com/liuxinye23/CyberStrikeAIWrote 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/liuxinye23/cyberstrikeai/tls-configuration-review)<a href="https://agentmods.dev/skills/liuxinye23/cyberstrikeai/tls-configuration-review"><img src="https://agentmods.dev/badge/skills/liuxinye23/cyberstrikeai/tls-configuration-review/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/liuxinye23/cyberstrikeai/tls-configuration-review"><img src="https://agentmods.dev/badge/skills/liuxinye23/cyberstrikeai/tls-configuration-review.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 | $0.00028 | $0.00686 |
| Opus 5 | $0.00014 | $0.00343 |
| Sonnet 5 | $0.00006 | $0.00137 |
| Haiku 4.5 | $0.00003 | $0.00069 |
Grade A, and why
tls-configuration-review 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 11d 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
TLS 与 HTTPS 配置审计
何时使用
当系统暴露 HTTPS、反向代理、多域名、多子域、下载站点、管理后台或移动端 API 时使用本技能。
快速流程
- 梳理所有域名、子域、证书边界和跳转链。
- 检查 HTTP→HTTPS 跳转、证书链、主机名匹配、HSTS、缓存代理行为。
- 对首页、登录页、API、下载链接和静态资源分别核对是否一致。
- 记录仅在某个子域、某个入口或某个 CDN 节点出现的偏差。
重点检查
入口与重定向
- 是否所有敏感入口都会稳定落到 HTTPS。
- 多跳重定向、跨域跳转、端口切换后是否丢失安全头或会话状态。
证书与域名
- 证书链是否完整,SAN 是否覆盖真实访问域。
- 过期、错配、临时证书、测试域证书误上生产要单独标注。
HSTS 与浏览器策略
- 是否只在首页设置 HSTS,而登录页、后台或子域缺失。
- 是否在混合部署下错误地把未准备好的子域一起纳入严格策略。
内容与资源一致性
- 页面、下载、图片、脚本、API 是否仍引用明文资源。
- 代理/CDN/边缘节点是否对不同路径应用不同 TLS 与缓存策略。
建议工具
http-framework-test
- 重点抓跳转链、首包时间、TLS 握手指标、关键响应头和最终资源落点。
- 对同一资源分别用
http://与https://验证实际行为。
nuclei
- 用于补充常见 TLS/证书/HSTS 暴露和基础配置错误检测。
证据要求
- 保存问题域名、目标路径、最终落点、证书摘要和关键响应头。
- 若问题仅出现在某类资源或某个节点,写清分布范围。
修复建议方向
- 统一敏感入口的 HTTPS 与跳转策略。
- 修复证书覆盖与链路不一致问题。
- 对 HSTS、混合内容和 CDN 边界做分层治理。
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.
- 11d ago First seen · 90 lines · 28 tokens per session scan A aa64198ee442
tls-configuration-review is a skill published in the GitHub repository liuxinye23/CyberStrikeAI (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 28 tokens to every session and 686 once invoked, about $0.0001 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…