[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M717KSGP2JQPJFQZFX97W09Q":3,"skill-same:01M717KSGP2JQPJFQZFX97W09Q":63},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":36,"linkOnly":37,"markdownContent":38,"markdownBody":39,"frontMatter":40,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":14,"repositoryHtmlUrl":46,"repositoryHomepageUrl":6,"ownerHtmlUrl":47,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":48,"install":49,"resources":62},"01M717KSGP2JQPJFQZFX97W09Q","aegisops-ai",null,"Autonomous DevSecOps & FinOps Guardrails. Orchestrates Gemini 3 Flash to audit Linux Kernel patches, Terraform cost drifts, and K8s compliance.","sapsapshen\u002Fai-memory-router","sapsapshen","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F20347959?v=4","01M6XDQEF1DP50DKF37H81J3J5","shenmian","01M6XDQEJPE41Y3DT2763X8ZJN",0,"MIT","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fglobal\u002Faegisops-ai\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35],"aegisops ai","compliance","2026","k8s","community","cost","autonomous","flash","Guardrails","safe","audit","terraform","finops","devsecops","linux","kernel","gemini","2026-11-10 10:12:30",false,"---\nname: aegisops-ai\ndescription: \"Autonomous DevSecOps & FinOps Guardrails. Orchestrates Gemini 3 Flash to audit Linux Kernel patches, Terraform cost drifts, and K8s compliance.\"\nrisk: safe\nsource: community\nauthor: Champbreed\ndate_added: \"2026-03-24\"\n---\n\n# \u002Faegisops-ai — Autonomous Governance Orchestrator\n\nAegisOps-AI is a professional-grade \"Living Pipeline\" \nthat integrates advanced AI reasoning directly into \nthe SDLC. It acts as an intelligent gatekeeper for \nsystems-level security, cloud infrastructure costs, \nand Kubernetes compliance.\n\n## Goal\n\nTo automate high-stakes security and financial audits by:\n1. Identifying logic-based vulnerabilities (UAF, Stale \nState) in Linux Kernel patches.\n2. Detecting massive \"Silent Disaster\" cost drifts in \nTerraform plans.\n3. Translating natural language security intent into \nhardened K8s manifests.\n\n## When to Use\n\n- **Kernel Patch Review:** Auditing raw C-based Git diffs for memory safety.\n- **Pre-Apply IaC Audit:** Analyzing `terraform plan` outputs to prevent bill spikes.\n- **Cluster Hardening:** Generating \"Least Privilege\" securityContexts for deployments.\n- **CI\u002FCD Quality Gating:** Blocking non-compliant merges via GitHub Actions.\n\n## When Not to Use\n\n- **Web App Logic:** Do not use for standard web vulnerabilities (XSS, SQLi); use dedicated SAST scanners.\n- **Non-C Memory Analysis:** The patch analyzer is optimized for C-logic; avoid using it for high-level languages like Python or JS.\n- **Direct Resource Mutation:** This is an *auditor*, not a deployment tool. It does not execute `terraform apply` or `kubectl apply`.\n- **Post-Mortem Analysis:** For analyzing *why* a previous AI session failed, use `\u002Fanalyze-project` instead.\n\n---\n## 🤖 Generative AI Integration\n\nAegisOps-AI leverages the **Google GenAI SDK** to implement a \"Reasoning Path\" for autonomous security and financial audits:\n\n* **Neural Patch Analysis:** Performs semantic code reviews of Linux Kernel patches, moving beyond simple pattern matching to understand complex memory state logic.\n* **Intelligent Cost Synthesis:** Processes raw Terraform plan diffs through a financial reasoning model to detect high-risk resource escalations and \"silent\" fiscal drifts.\n* **Natural Language Policy Mapping:** Translates human security intent into syntactically correct, hardened Kubernetes `securityContext` configurations.\n\n## 🧭 Core Modules\n\n### 1. 🐧 Kernel Patch Reviewer (`patch_analyzer.py`)\n\n* **Problem:** Manual review of Linux Kernel memory safety is time-consuming and prone to human error.\n* **Solution:** Gemini 3 performs a \"Deep Reasoning\" audit on raw Git diffs to detect critical memory corruption vulnerabilities (UAF, Stale State) in seconds.\n* **Key Output:** `analysis_results.json`\n\n### 2. 💰 FinOps & Cloud Auditor (`cost_auditor.py`)\n\n* **Problem:** Infrastructure-as-Code (IaC) changes can lead to accidental \"Silent Disasters\" and massive cloud bill spikes.\n* **Solution:** Analyzes `terraform plan` output to identify cost anomalies—such as accidental upgrades from `t3.micro` to high-performance GPU instances.\n* **Key Output:** `infrastructure_audit_report.json`\n\n### 3. ☸️ K8s Policy Hardener (`k8s_policy_generator.py`)\n\n* **Problem:** Implementing \"Least Privilege\" security contexts in Kubernetes is complex and often neglected.\n* **Solution:** Translates natural language security requirements into production-ready, hardened YAML manifests (Read-only root FS, Non-root enforcement, etc.).\n* **Key Output:** `hardened_deployment.yaml`\n\n## 🛠️ Setup & Environment\n\n### 1. Clone the Repository\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002FChampbreed\u002FAegisOps-AI.git\ncd AegisOps-AI\n```\n## 2. Setup\n\n```bash\npython3 -m venv venv\nsource venv\u002Fbin\u002Factivate\npip install google-genai python-dotenv\n```\n### 3. API Configuration\n\nCreate a `.env` file in the root directory to securely \nstore your credentials:\n\n```bash\necho \"GEMINI_API_KEY='your_api_key_here'\" > .env\n```\n## 🏁 Operational Dashboard\n\nTo execute the full suite of agents in sequence and generate all security reports:\n\n```bash\npython3 main.py\n```\n### Pattern: Over-Privileged Container\n\n* **Indicators:** `allowPrivilegeEscalation: true` or root user execution.\n* **Investigation:** Pass security intent (e.g., \"non-root only\") to the K8s Hardener module.\n\n---\n\n## 💡 Best Practices\n\n* **Context is King:** Provide at least 5 lines of context around Git diffs for more accurate neural reasoning.\n* **Continuous Gating:** Run the FinOps auditor before every infrastructure change, not after.\n* **Manual Sign-off:** Use AI findings as a high-fidelity signal, but maintain human-in-the-loop for kernel-level merges.\n\n---\n\n## 🔒 Security & Safety Notes\n\n* **Key Management:** Use CI\u002FCD secrets for `GEMINI_API_KEY` in production.\n* **Least Privilege:** Test \"Hardened\" manifests in staging first to ensure no functional regressions.\n\n## Links\n\n+ - **Repository**: https:\u002F\u002Fgithub.com\u002FChampbreed\u002FAegisOps-AI\n+ - **Documentation**: https:\u002F\u002Fgithub.com\u002FChampbreed\u002FAegisOps-AI#readme\n","# \u002Faegisops-ai — Autonomous Governance Orchestrator\n\nAegisOps-AI is a professional-grade \"Living Pipeline\" \nthat integrates advanced AI reasoning directly into \nthe SDLC. It acts as an intelligent gatekeeper for \nsystems-level security, cloud infrastructure costs, \nand Kubernetes compliance.\n\n## Goal\n\nTo automate high-stakes security and financial audits by:\n1. Identifying logic-based vulnerabilities (UAF, Stale \nState) in Linux Kernel patches.\n2. Detecting massive \"Silent Disaster\" cost drifts in \nTerraform plans.\n3. Translating natural language security intent into \nhardened K8s manifests.\n\n## When to Use\n\n- **Kernel Patch Review:** Auditing raw C-based Git diffs for memory safety.\n- **Pre-Apply IaC Audit:** Analyzing `terraform plan` outputs to prevent bill spikes.\n- **Cluster Hardening:** Generating \"Least Privilege\" securityContexts for deployments.\n- **CI\u002FCD Quality Gating:** Blocking non-compliant merges via GitHub Actions.\n\n## When Not to Use\n\n- **Web App Logic:** Do not use for standard web vulnerabilities (XSS, SQLi); use dedicated SAST scanners.\n- **Non-C Memory Analysis:** The patch analyzer is optimized for C-logic; avoid using it for high-level languages like Python or JS.\n- **Direct Resource Mutation:** This is an *auditor*, not a deployment tool. It does not execute `terraform apply` or `kubectl apply`.\n- **Post-Mortem Analysis:** For analyzing *why* a previous AI session failed, use `\u002Fanalyze-project` instead.\n\n---\n## 🤖 Generative AI Integration\n\nAegisOps-AI leverages the **Google GenAI SDK** to implement a \"Reasoning Path\" for autonomous security and financial audits:\n\n* **Neural Patch Analysis:** Performs semantic code reviews of Linux Kernel patches, moving beyond simple pattern matching to understand complex memory state logic.\n* **Intelligent Cost Synthesis:** Processes raw Terraform plan diffs through a financial reasoning model to detect high-risk resource escalations and \"silent\" fiscal drifts.\n* **Natural Language Policy Mapping:** Translates human security intent into syntactically correct, hardened Kubernetes `securityContext` configurations.\n\n## 🧭 Core Modules\n\n### 1. 🐧 Kernel Patch Reviewer (`patch_analyzer.py`)\n\n* **Problem:** Manual review of Linux Kernel memory safety is time-consuming and prone to human error.\n* **Solution:** Gemini 3 performs a \"Deep Reasoning\" audit on raw Git diffs to detect critical memory corruption vulnerabilities (UAF, Stale State) in seconds.\n* **Key Output:** `analysis_results.json`\n\n### 2. 💰 FinOps & Cloud Auditor (`cost_auditor.py`)\n\n* **Problem:** Infrastructure-as-Code (IaC) changes can lead to accidental \"Silent Disasters\" and massive cloud bill spikes.\n* **Solution:** Analyzes `terraform plan` output to identify cost anomalies—such as accidental upgrades from `t3.micro` to high-performance GPU instances.\n* **Key Output:** `infrastructure_audit_report.json`\n\n### 3. ☸️ K8s Policy Hardener (`k8s_policy_generator.py`)\n\n* **Problem:** Implementing \"Least Privilege\" security contexts in Kubernetes is complex and often neglected.\n* **Solution:** Translates natural language security requirements into production-ready, hardened YAML manifests (Read-only root FS, Non-root enforcement, etc.).\n* **Key Output:** `hardened_deployment.yaml`\n\n## 🛠️ Setup & Environment\n\n### 1. Clone the Repository\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002FChampbreed\u002FAegisOps-AI.git\ncd AegisOps-AI\n```\n## 2. Setup\n\n```bash\npython3 -m venv venv\nsource venv\u002Fbin\u002Factivate\npip install google-genai python-dotenv\n```\n### 3. API Configuration\n\nCreate a `.env` file in the root directory to securely \nstore your credentials:\n\n```bash\necho \"GEMINI_API_KEY='your_api_key_here'\" > .env\n```\n## 🏁 Operational Dashboard\n\nTo execute the full suite of agents in sequence and generate all security reports:\n\n```bash\npython3 main.py\n```\n### Pattern: Over-Privileged Container\n\n* **Indicators:** `allowPrivilegeEscalation: true` or root user execution.\n* **Investigation:** Pass security intent (e.g., \"non-root only\") to the K8s Hardener module.\n\n---\n\n## 💡 Best Practices\n\n* **Context is King:** Provide at least 5 lines of context around Git diffs for more accurate neural reasoning.\n* **Continuous Gating:** Run the FinOps auditor before every infrastructure change, not after.\n* **Manual Sign-off:** Use AI findings as a high-fidelity signal, but maintain human-in-the-loop for kernel-level merges.\n\n---\n\n## 🔒 Security & Safety Notes\n\n* **Key Management:** Use CI\u002FCD secrets for `GEMINI_API_KEY` in production.\n* **Least Privilege:** Test \"Hardened\" manifests in staging first to ensure no functional regressions.\n\n## Links\n\n+ - **Repository**: https:\u002F\u002Fgithub.com\u002FChampbreed\u002FAegisOps-AI\n+ - **Documentation**: https:\u002F\u002Fgithub.com\u002FChampbreed\u002FAegisOps-AI#readme\n",{"name":5,"risk":28,"author":41,"source":23,"date_added":42,"description":7},"Champbreed","2026-03-24","main","7a38d8e7073e61c16eda85681cb32fb68a8657a5","skills-store\u002Fglobal\u002Faegisops-ai","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router","https:\u002F\u002Fgithub.com\u002Fsapsapshen","2026-04-14 21:12:12",{"source":8,"skillName":5,"commands":50,"prompt":60,"zipAvailable":61},[51,54,57],{"tool":52,"command":53},"npx","npx skills add sapsapshen\u002Fai-memory-router --skill aegisops-ai",{"tool":55,"command":56},"bunx","bunx skills add sapsapshen\u002Fai-memory-router --skill aegisops-ai",{"tool":58,"command":59},"pnpm","pnpm dlx skills add sapsapshen\u002Fai-memory-router --skill aegisops-ai","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fglobal\u002Faegisops-ai\u002FSKILL.md",true,[],[64,87,113,123,136,155],{"skillNo":65,"name":66,"nameZh":6,"description":67,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":68,"categories":69,"keywords":75,"publishedAt":36},"01M71ATQRKG48SH06FQ697T5G9","wechat-search","Search WeChat Official Account articles using OpenClaw's web search and fetch capabilities with compliance-focused design.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fwechat-search-release\u002FSKILL.md",[70],{"categoryNo":71,"categoryName":72,"taxonomyType":73,"taxonomyTypeDesc":74},"01JBSEEDCAT000000000000037","律师与法务","PROFESSION","适用职业",[76,77,78,79,80,81,82,20,83,84,85,86],"wechat search","wechat","search","capabilities","openclaw","design","web search","web","official","fetch","with",{"skillNo":88,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":91,"categories":92,"keywords":93,"publishedAt":36},"01M71ATNAVGZB35PFYM2GC5N00","trend-tap","Real-time trending topics aggregator across 7 platforms (X\u002FTwitter, Reddit, Google Trends, Hacker News, Zhihu, Bilibili, Weibo). Trigger: when user says 'trend', 'trends', 'trend tap', '热点', '热搜', or asks what is trending\u002Fhot. Do NOT use web_search — this skill already fetches live data from all platforms with zero API keys.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Ftrend-tap\u002FSKILL.md",[],[94,95,96,97,98,99,78,100,101,102,103,104,105,106,107,108,109,110,111,112],"trend","trend tap","tap","api keys","Bash","time","trending","hacker","aggregator","do","when","brew","live","data","google","install","read","across","api",{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":119,"publishedAt":36},"01M71ATJ9AM5KM15AA8PS302EB","trend-radar","Real-time trending topics aggregator across 7 platforms (X\u002FTwitter, Reddit, Google Trends, Hacker News, Zhihu, Bilibili, Weibo). Trigger: when user says 'trend', 'trends', 'trend pulse', '热点', '热搜', or asks what is trending\u002Fhot. Do NOT use web_search — this skill already fetches live data from all platforms with zero API keys.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Ftrend-radar\u002FSKILL.md",[],[120,121,94,105,106,107,108,98,78,110,122,111,112,104,102,101,100,109,99,97],"trend radar","radar","pulse",{"skillNo":124,"name":125,"nameZh":6,"description":126,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":127,"categories":128,"keywords":129,"publishedAt":36},"01M71ATGF095N3EJM9G8SD0BB5","tech-news-daily","每日科技新闻汇——从全球多个 RSS 源抓取最新科技新闻，翻译（英→中）、去重、排版成每日简报。当用户询问科技新闻、科技新鲜事、每日科技、技术动态、Daily Tech News 或类似表达时触发此技能。","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Ftech-news-daily\u002FSKILL.md",[],[130,131,132,133,134,135],"news","tech","tech news daily","daily","rss","翻译",{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":147,"publishedAt":36},"01M71ATFAEAMQ17M70NQNY7SR8","summarize","Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube).","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fsummarize\u002FSKILL.md",[142],{"categoryNo":143,"categoryName":144,"taxonomyType":145,"taxonomyTypeDesc":146},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[138,83,148,149,150,86,105,151,152,153,96,154,109],"Audio","cli","youtube","images","https","files","pdfs",{"skillNo":156,"name":157,"nameZh":6,"description":158,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":159,"categories":160,"keywords":161,"publishedAt":36},"01M71ATDNS3R0M4H936PACQAWZ","sonoscli","Control Sonos speakers (discover\u002Fstatus\u002Fplay\u002Fvolume\u002Fgroup).","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fsonoscli\u002FSKILL.md",[],[157,162,163,164,109,165,152,166,167,168,169,170],"status","play","go","latest","github","discover","control","cmd","volume"]