[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M73FS8GE2NRB3TGF5MG61YFD":3,"skill-same:01M73FS8GE2NRB3TGF5MG61YFD":52},{"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":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":28,"commitSha":29,"skillDirectory":30,"forksCount":31,"repositoryHtmlUrl":32,"repositoryHomepageUrl":33,"ownerHtmlUrl":34,"ownerBlogUrl":35,"ownerDescription":36,"updatedAt":37,"install":38,"resources":51},"01M73FS8GE2NRB3TGF5MG61YFD","session-to-skill",null,"Auto-extract a reusable skill from the current session conversation. Use when the user says \"save this as a skill\", \"turn this into a skill\", \"I want to reuse this workflow\", \"make this repeatable\", \"skillify this\", \"we just did something I want to automate\", or after completing a useful multi-step task that could be repeated. Do NOT use for one-off fixes or tasks with no repeatable value.","Horonomos-laps\u002FYana-AI","Horonomos-laps","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F355299122?v=4","01M76B3QPXE88ET2SQPDPVATZT"," Horonomos-laps","01M72ZQRJPCYPSSWT4D00VJR2A",13,"MIT","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fsession-to-skill\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: session-to-skill\ndescription: >\n  Auto-extract a reusable skill from the current session conversation.\n  Use when the user says \"save this as a skill\", \"turn this into a skill\",\n  \"I want to reuse this workflow\", \"make this repeatable\", \"skillify this\",\n  \"we just did something I want to automate\", or after completing a useful\n  multi-step task that could be repeated.\n  Do NOT use for one-off fixes or tasks with no repeatable value.\norigin: adapted:NanmiCoder\u002Fcc-haha (skillify.ts)\nlicense: MIT\nversion: 1.0.0\ncompatibility: \"yana-ai >= 0.14.0\"\n---\n\n\u003C!-- Adapted from cc-haha\u002Fsrc\u002Fskills\u002Fbundled\u002Fskillify.ts (MIT). Logic: session analysis → user interview → SKILL.md generation. Changes: adapted to yamtam SKILL.md format, added Anti-Fake-Pass gates, removed ANT-only constraints. -->\n\n## When to Use\n\n- Use when: user just completed a multi-step workflow they want repeatable\n- Use when: user explicitly says \"make this a skill\" or \"I want to automate this\"\n- Use when: the task has ≥3 distinct steps that follow a clear order\n- Do NOT use: for one-off tasks, bug fixes, or exploratory investigations\n- Do NOT use: if an equivalent skill already exists — check first\n\n## Pre-check\n\nBefore starting, run:\n```bash\nls core\u002Fskills\u002F | grep -i \"\u003Cproposed-name>\"\n```\nIf a similar skill exists, suggest updating it instead.\n\n## 4-Step Process\n\n### Step 1 — Analyze the session\n\nRead the conversation and identify:\n- What repeatable workflow was just performed?\n- What were the distinct, ordered steps?\n- What inputs did it require (files, URLs, flags)?\n- What was the success criteria?\n\nWrite a 1-sentence summary before proceeding.\n\n### Step 2 — Interview the user (use AskUserQuestion)\n\n**Round 1 — Name and scope:**\n- Proposed skill name (kebab-case)\n- One-line description: \"Use when...\"\n- What should it NOT be used for?\n\n**Round 2 — Steps and inputs:**\n- Confirm the step sequence\n- What arguments\u002Finputs are required vs optional?\n- Any environment requirements (env vars, tools)?\n\n**Round 3 — Trigger phrases:**\n- What would the user type to invoke this? (3–5 trigger phrases)\n- What signal words make it obvious this skill applies?\n\n### Step 3 — Draft the SKILL.md\n\nFollow the yamtam SKILL.md format:\n```markdown\n---\nname: \u003Cskill-name>\ndescription: >\n  \u003Cone-paragraph description with trigger phrases and Do NOT cases>\norigin: session-extracted\nversion: 1.0.0\n---\n\n## When to Use\n## Pre-conditions\n## Steps\n## Anti-Fake-Pass\n```\n\nKeep it under 200 lines. One clear thing per step. No padding.\n\n### Step 4 — Show and confirm\n\nShow the complete draft to the user.\nAsk: \"Does this capture it correctly? Any adjustments before I save?\"\n\nOnly write the file after explicit approval.\n\nWrite to: `core\u002Fskills\u002F\u003Cname>\u002FSKILL.md`\n\n## Anti-Fake-Pass\n\n```\n❌ Creating a skill for a one-off task with no repeatable value\n❌ Writing the skill without confirming the step order with the user\n❌ Saving without showing the draft first\n❌ Skipping the duplicate-check\n✅ User explicitly confirmed the draft before saving\n✅ Skill has ≥3 distinct steps\n✅ Trigger phrases are specific enough to avoid false positives\n```\n","\u003C!-- Adapted from cc-haha\u002Fsrc\u002Fskills\u002Fbundled\u002Fskillify.ts (MIT). Logic: session analysis → user interview → SKILL.md generation. Changes: adapted to yamtam SKILL.md format, added Anti-Fake-Pass gates, removed ANT-only constraints. -->\n\n## When to Use\n\n- Use when: user just completed a multi-step workflow they want repeatable\n- Use when: user explicitly says \"make this a skill\" or \"I want to automate this\"\n- Use when: the task has ≥3 distinct steps that follow a clear order\n- Do NOT use: for one-off tasks, bug fixes, or exploratory investigations\n- Do NOT use: if an equivalent skill already exists — check first\n\n## Pre-check\n\nBefore starting, run:\n```bash\nls core\u002Fskills\u002F | grep -i \"\u003Cproposed-name>\"\n```\nIf a similar skill exists, suggest updating it instead.\n\n## 4-Step Process\n\n### Step 1 — Analyze the session\n\nRead the conversation and identify:\n- What repeatable workflow was just performed?\n- What were the distinct, ordered steps?\n- What inputs did it require (files, URLs, flags)?\n- What was the success criteria?\n\nWrite a 1-sentence summary before proceeding.\n\n### Step 2 — Interview the user (use AskUserQuestion)\n\n**Round 1 — Name and scope:**\n- Proposed skill name (kebab-case)\n- One-line description: \"Use when...\"\n- What should it NOT be used for?\n\n**Round 2 — Steps and inputs:**\n- Confirm the step sequence\n- What arguments\u002Finputs are required vs optional?\n- Any environment requirements (env vars, tools)?\n\n**Round 3 — Trigger phrases:**\n- What would the user type to invoke this? (3–5 trigger phrases)\n- What signal words make it obvious this skill applies?\n\n### Step 3 — Draft the SKILL.md\n\nFollow the yamtam SKILL.md format:\n```markdown\n---\nname: \u003Cskill-name>\ndescription: >\n  \u003Cone-paragraph description with trigger phrases and Do NOT cases>\norigin: session-extracted\nversion: 1.0.0\n---\n\n## When to Use\n## Pre-conditions\n## Steps\n## Anti-Fake-Pass\n```\n\nKeep it under 200 lines. One clear thing per step. No padding.\n\n### Step 4 — Show and confirm\n\nShow the complete draft to the user.\nAsk: \"Does this capture it correctly? Any adjustments before I save?\"\n\nOnly write the file after explicit approval.\n\nWrite to: `core\u002Fskills\u002F\u003Cname>\u002FSKILL.md`\n\n## Anti-Fake-Pass\n\n```\n❌ Creating a skill for a one-off task with no repeatable value\n❌ Writing the skill without confirming the step order with the user\n❌ Saving without showing the draft first\n❌ Skipping the duplicate-check\n✅ User explicitly confirmed the draft before saving\n✅ Skill has ≥3 distinct steps\n✅ Trigger phrases are specific enough to avoid false positives\n```\n",{"name":5,"origin":24,"license":15,"version":25,"description":26,"compatibility":27},"adapted:NanmiCoder\u002Fcc-haha (skillify.ts)","1.0.0","Auto-extract a reusable skill from the current session conversation. Use when the user says \"save this as a skill\", \"turn this into a skill\", \"I want to reuse this workflow\", \"make this repeatable\", \"skillify this\", \"we just did something I want to automate\", or after completing a useful multi-step task that could be repeated. Do NOT use for one-off fixes or tasks with no repeatable value.\n","yana-ai >= 0.14.0","main","481dcd7dd2e288b9d627a2bd017db70e64e6c6fa","core\u002Fskills\u002Fsession-to-skill",1,"https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI","https:\u002F\u002Fyana.vutam.link\u002F","https:\u002F\u002Fgithub.com\u002FHoronomos-laps","https:\u002F\u002Fyana.vutam.link","An open-source governed runtime & execution environment for multi-agent AI systems.","2026-11-11 23:56:26",{"source":8,"skillName":5,"commands":39,"prompt":49,"zipAvailable":50},[40,43,46],{"tool":41,"command":42},"npx","npx skills add Horonomos-laps\u002FYana-AI --skill session-to-skill",{"tool":44,"command":45},"bunx","bunx skills add Horonomos-laps\u002FYana-AI --skill session-to-skill",{"tool":47,"command":48},"pnpm","pnpm dlx skills add Horonomos-laps\u002FYana-AI --skill session-to-skill","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fsession-to-skill\u002FSKILL.md",true,[],[53,60,68,76,84,92],{"skillNo":54,"name":55,"nameZh":6,"description":56,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":57,"categories":58,"keywords":59,"publishedAt":19},"01M735GKET5YVYKAY62W2P5YXB","openai--sentry--sentry","Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fopenai--sentry--sentry\u002FSKILL.md",[],[],{"skillNo":61,"name":62,"nameZh":6,"description":63,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":64,"licenseFileUrl":6,"sourceHtmlUrl":65,"categories":66,"keywords":67,"publishedAt":19},"01M73DCAP83T17HY7SMGK7MGFE","ito-basket-compare","Compare Itô prediction-market baskets against a user's knowledge base, portfolio notes, financial context, watchlist, or research thesis. Use for read-only basket comparison and gap analysis without investment advice or live trading.","Apache-2.0","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fito-basket-compare\u002FSKILL.md",[],[],{"skillNo":69,"name":70,"nameZh":6,"description":71,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":64,"licenseFileUrl":72,"sourceHtmlUrl":73,"categories":74,"keywords":75,"publishedAt":19},"01M734CYEMZFDR3KH6SW0JP8TD","implementing-network-traffic-baselining","Build network traffic baselines from NetFlow\u002FIPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly\u002Fdaily traffic pattern profiling","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FSKILL.md",[],[],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":64,"licenseFileUrl":80,"sourceHtmlUrl":81,"categories":82,"keywords":83,"publishedAt":19},"01M73ASZ6NJRJM44Z2P84NGQ3Q","detecting-evasion-techniques-in-endpoint-logs","Detects defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FSKILL.md",[],[],{"skillNo":85,"name":86,"nameZh":6,"description":87,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":64,"licenseFileUrl":88,"sourceHtmlUrl":89,"categories":90,"keywords":91,"publishedAt":19},"01M734AFNXD06Z78QRK0VKGT7Q","implementing-microsegmentation-with-guardicore","Implementing microsegmentation using Akamai Guardicore Segmentation to map application dependencies, create granular network policies, visualize east-west traffic flows, and enforce least-privilege communication between workloads across data centers and cloud.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FSKILL.md",[],[],{"skillNo":93,"name":94,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":64,"licenseFileUrl":6,"sourceHtmlUrl":95,"categories":96,"keywords":97,"publishedAt":19},"01M736TK27QMCXK0DVCH25SJN5","ramdisk-tmpfs-patterns","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Framdisk-tmpfs-patterns\u002FSKILL.md",[],[]]