[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M737CSS0XNWEWFR2M4BM4DHR":3,"skill-same:01M737CSS0XNWEWFR2M4BM4DHR":57},{"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":27,"commitSha":28,"skillDirectory":29,"forksCount":30,"repositoryHtmlUrl":31,"repositoryHomepageUrl":32,"ownerHtmlUrl":33,"ownerBlogUrl":34,"ownerDescription":35,"updatedAt":36,"install":37,"resources":50},"01M737CSS0XNWEWFR2M4BM4DHR","sports--xctf-data",null,"|","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\u002F.claude\u002Fskills\u002Fsports--xctf-data\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: sports--xctf-data\ndescription: >-\n  |\norigin: \"github.com\u002Fmachina-sports\u002Fsports-skills (skill: xctf-data)\"\nlicense: MIT\nversion: \"1.0.0\"\ncompatibility: \"yana-ai >= 0.14.0\"\n---\n\n# XC\u002FTF Data (TFRRS — NCAA Cross Country & Track and Field)\n\nBefore writing queries, consult `references\u002Fapi-reference.md` for parameters, URL conventions, and return shapes.\n\n## Setup\n\nBefore first use, check if the CLI is available:\n```bash\nwhich sports-skills || pip install sports-skills\n```\nIf `pip install` fails, install from GitHub:\n```bash\npip install git+https:\u002F\u002Fgithub.com\u002Fmachina-sports\u002Fsports-skills.git\n```\nRequires Python 3.10+. No API keys required. All data comes from TFRRS public pages and The Stride Report RSS feed.\n\n## Quick Start\n\nCLI (preferred):\n```bash\nsports-skills xctf get_athlete_profile --athlete_id=9230145 --school=BYU --name=Jane_Hedengren\nsports-skills xctf get_news --limit=5\n```\n\nPython SDK:\n```python\nfrom sports_skills import xctf\n\nprofile = xctf.get_athlete_profile(\n    athlete_id=\"9230145\",\n    school=\"BYU\",\n    name=\"Jane_Hedengren\",\n)\n```\n\n## CRITICAL: Before Any Query\n\nAll three parameters are required and must match the athlete's TFRRS URL exactly:\n\n```\nhttps:\u002F\u002Fwww.tfrrs.org\u002Fathletes\u002F{athlete_id}\u002F{school}\u002F{name}.html\n```\n\n- `athlete_id` — numeric ID (e.g. `9230145`)\n- `school` — school slug with underscores, not spaces (e.g. `BYU`)\n- `name` — athlete name slug (e.g. `Jane_Hedengren`)\n\nDo NOT guess slugs. Find them by navigating to the athlete on tfrrs.org and copying the URL.\n\n## Commands\n\n| Command | Description |\n|---|---|\n| `search_athlete` | Search the current team roster by name; returns `athlete_id`, `school`, and `name` slugs for use with `get_athlete_profile`. Searches both genders automatically. Current athletes only — graduated athletes require a direct TFRRS URL |\n| `get_athlete_profile` | Athlete name, school, eligibility, all PRs, and full season-by-season meet results |\n| `get_team_roster` | Full XC and\u002For TF roster for a team |\n| `get_meet_results` | All event results and team scores from a TFRRS meet |\n| `get_news` | Recent XC\u002FTF articles from The Stride Report (thestridereport.com) |\n\nSee `references\u002Fapi-reference.md` for full parameter details and return shapes.\n\n## Examples\n\nExample 1: Look up a current athlete's PRs\nUser says: \"What are Jane Hedengren's PRs?\"\nActions:\n1. Call `search_athlete(name=\"Jane Hedengren\", school=\"UT_college_f_BYU\")`\n   Result: `data.matches` contains entries with `athlete_id`, `school`, `name` slugs\n2. Call `get_athlete_profile(athlete_id=\"9230145\", school=\"BYU\", name=\"Jane_Hedengren\")`\nResult: `data.prs` contains all personal records by event (e.g. `{\"1500\": \"4:10.24\", \"5000\": \"14:44.79\", \"6K (XC)\": \"18:29.6\", ...}`)\n\nExample 2: Get a runner's cross country season\nUser says: \"Show me Jane Hedengren's 2025 XC season results\"\nActions:\n1. Call `search_athlete(name=\"Jane Hedengren\", school=\"UT_college_f_BYU\")`\n2. Call `get_athlete_profile` with the matched athlete params\n3. Filter `data.meets` for entries whose `date` falls in the fall of 2025 (Sep–Nov 2025)\nResult: List of meets with dates, events, marks, and places\n\nExample 3: Graduated or transferred athlete\nUser says: \"What are Katelyn Vuong's PRs from UC Davis?\"\nActions:\n1. Call `search_athlete(name=\"Katelyn Vuong\", school=\"CA_college_f_UC_Davis\")`\n   Result: `data.matches` is empty — athlete has graduated\n2. Tell the user: \"Katelyn Vuong is not on UC Davis's current roster. Please find her profile URL on tfrrs.org (e.g. search 'Katelyn Vuong UC Davis tfrrs') and share it.\"\n3. User provides: `https:\u002F\u002Fwww.tfrrs.org\u002Fathletes\u002F7899206\u002FUC_Davis\u002FKatelyn_Vuong.html`\n4. Extract params from the URL and call `get_athlete_profile(athlete_id=\"7899206\", school=\"UC_Davis\", name=\"Katelyn_Vuong\")`\nNote: TFRRS creates separate profiles for XC and TF. If both exist, fetch both IDs for complete PRs.\n\nExample 4: Get a team's current roster\nUser says: \"Show me the UC Davis women's XC roster\"\nActions:\n1. Call `get_team_roster(school=\"CA_college_f_UC_Davis\", sport=\"xc\")`\nResult: List of athletes with name, year, and profile slugs\n\nExample 5: Get results from a meet\nUser says: \"Show me the results from the Stanford Invitational\"\nActions:\n1. Find the meet on tfrrs.org and copy the meet_id and slug from the URL (e.g. tfrrs.org\u002Fresults\u002F95890\u002FStanford_Invitational)\n2. Call `get_meet_results(meet_id=\"95890\", slug=\"Stanford_Invitational\")`\nResult: All event results and team scores from the meet\n\nExample 6: Get the latest XC\u002FTF news\nUser says: \"What's the latest college track news?\"\nActions:\n1. Call `get_news(limit=10)`\nResult: Recent articles from The Stride Report with title, date, summary, and link\n\n## Commands that DO NOT exist — never call these\n\n- ~~`get_team_rankings`~~ — does not exist. Use `get_athlete_profile` for individual data.\n- ~~`search_athletes`~~ — does not exist. The correct command is `search_athlete` (no trailing 's').\n- ~~`fetch_news`~~ — does not exist. The correct command is `get_news`.\n\nIf a command is not listed in the Commands table above, it does not exist.\n\n## Error Handling\n\nWhen a command fails, **do not surface raw errors to the user**. Instead:\n1. For `get_athlete_profile`: confirm `athlete_id`, `school`, and `name` match the TFRRS URL exactly (case-sensitive)\n2. For `search_athlete`: verify the team slug is correct by checking the team's TFRRS page URL\n3. For `get_meet_results`: verify the `meet_id` and `slug` match the meet's TFRRS URL exactly\n4. For `get_team_roster`: verify the school slug is correct\n5. For `get_news`: if the feed fails, inform the user that The Stride Report may be temporarily unavailable\n6. Report failure with a clean message only after exhausting alternatives\n\n## Troubleshooting\n\n**`sports-skills` command not found**\nRun `pip install sports-skills` or install from GitHub (see Setup above).\n\n**HTTP 404 on athlete profile**\nThe `school` or `name` slug does not match the TFRRS URL exactly. Slugs are case-sensitive and use underscores. Copy directly from tfrrs.org.\n\n**`prs` returns empty dict**\nThe athlete's profile page may be very new or structured differently. Check the URL directly on tfrrs.org.\n\n**`search_athlete` returns empty matches**\nThe athlete is likely graduated or transferred. See Example 3 above for how to handle this.\n\n**`get_meet_results` returns no events**\nThe `meet_id` or `slug` may be incorrect. Copy both directly from the meet's TFRRS URL.\n\n**`get_news` fails or returns no articles**\nThe Stride Report RSS feed may be temporarily unavailable. Try again later.\n\n**Connection errors or timeouts**\nTFRRS may be temporarily unavailable. Requests are throttled to 1 per second automatically — wait a moment and retry.\n","# XC\u002FTF Data (TFRRS — NCAA Cross Country & Track and Field)\n\nBefore writing queries, consult `references\u002Fapi-reference.md` for parameters, URL conventions, and return shapes.\n\n## Setup\n\nBefore first use, check if the CLI is available:\n```bash\nwhich sports-skills || pip install sports-skills\n```\nIf `pip install` fails, install from GitHub:\n```bash\npip install git+https:\u002F\u002Fgithub.com\u002Fmachina-sports\u002Fsports-skills.git\n```\nRequires Python 3.10+. No API keys required. All data comes from TFRRS public pages and The Stride Report RSS feed.\n\n## Quick Start\n\nCLI (preferred):\n```bash\nsports-skills xctf get_athlete_profile --athlete_id=9230145 --school=BYU --name=Jane_Hedengren\nsports-skills xctf get_news --limit=5\n```\n\nPython SDK:\n```python\nfrom sports_skills import xctf\n\nprofile = xctf.get_athlete_profile(\n    athlete_id=\"9230145\",\n    school=\"BYU\",\n    name=\"Jane_Hedengren\",\n)\n```\n\n## CRITICAL: Before Any Query\n\nAll three parameters are required and must match the athlete's TFRRS URL exactly:\n\n```\nhttps:\u002F\u002Fwww.tfrrs.org\u002Fathletes\u002F{athlete_id}\u002F{school}\u002F{name}.html\n```\n\n- `athlete_id` — numeric ID (e.g. `9230145`)\n- `school` — school slug with underscores, not spaces (e.g. `BYU`)\n- `name` — athlete name slug (e.g. `Jane_Hedengren`)\n\nDo NOT guess slugs. Find them by navigating to the athlete on tfrrs.org and copying the URL.\n\n## Commands\n\n| Command | Description |\n|---|---|\n| `search_athlete` | Search the current team roster by name; returns `athlete_id`, `school`, and `name` slugs for use with `get_athlete_profile`. Searches both genders automatically. Current athletes only — graduated athletes require a direct TFRRS URL |\n| `get_athlete_profile` | Athlete name, school, eligibility, all PRs, and full season-by-season meet results |\n| `get_team_roster` | Full XC and\u002For TF roster for a team |\n| `get_meet_results` | All event results and team scores from a TFRRS meet |\n| `get_news` | Recent XC\u002FTF articles from The Stride Report (thestridereport.com) |\n\nSee `references\u002Fapi-reference.md` for full parameter details and return shapes.\n\n## Examples\n\nExample 1: Look up a current athlete's PRs\nUser says: \"What are Jane Hedengren's PRs?\"\nActions:\n1. Call `search_athlete(name=\"Jane Hedengren\", school=\"UT_college_f_BYU\")`\n   Result: `data.matches` contains entries with `athlete_id`, `school`, `name` slugs\n2. Call `get_athlete_profile(athlete_id=\"9230145\", school=\"BYU\", name=\"Jane_Hedengren\")`\nResult: `data.prs` contains all personal records by event (e.g. `{\"1500\": \"4:10.24\", \"5000\": \"14:44.79\", \"6K (XC)\": \"18:29.6\", ...}`)\n\nExample 2: Get a runner's cross country season\nUser says: \"Show me Jane Hedengren's 2025 XC season results\"\nActions:\n1. Call `search_athlete(name=\"Jane Hedengren\", school=\"UT_college_f_BYU\")`\n2. Call `get_athlete_profile` with the matched athlete params\n3. Filter `data.meets` for entries whose `date` falls in the fall of 2025 (Sep–Nov 2025)\nResult: List of meets with dates, events, marks, and places\n\nExample 3: Graduated or transferred athlete\nUser says: \"What are Katelyn Vuong's PRs from UC Davis?\"\nActions:\n1. Call `search_athlete(name=\"Katelyn Vuong\", school=\"CA_college_f_UC_Davis\")`\n   Result: `data.matches` is empty — athlete has graduated\n2. Tell the user: \"Katelyn Vuong is not on UC Davis's current roster. Please find her profile URL on tfrrs.org (e.g. search 'Katelyn Vuong UC Davis tfrrs') and share it.\"\n3. User provides: `https:\u002F\u002Fwww.tfrrs.org\u002Fathletes\u002F7899206\u002FUC_Davis\u002FKatelyn_Vuong.html`\n4. Extract params from the URL and call `get_athlete_profile(athlete_id=\"7899206\", school=\"UC_Davis\", name=\"Katelyn_Vuong\")`\nNote: TFRRS creates separate profiles for XC and TF. If both exist, fetch both IDs for complete PRs.\n\nExample 4: Get a team's current roster\nUser says: \"Show me the UC Davis women's XC roster\"\nActions:\n1. Call `get_team_roster(school=\"CA_college_f_UC_Davis\", sport=\"xc\")`\nResult: List of athletes with name, year, and profile slugs\n\nExample 5: Get results from a meet\nUser says: \"Show me the results from the Stanford Invitational\"\nActions:\n1. Find the meet on tfrrs.org and copy the meet_id and slug from the URL (e.g. tfrrs.org\u002Fresults\u002F95890\u002FStanford_Invitational)\n2. Call `get_meet_results(meet_id=\"95890\", slug=\"Stanford_Invitational\")`\nResult: All event results and team scores from the meet\n\nExample 6: Get the latest XC\u002FTF news\nUser says: \"What's the latest college track news?\"\nActions:\n1. Call `get_news(limit=10)`\nResult: Recent articles from The Stride Report with title, date, summary, and link\n\n## Commands that DO NOT exist — never call these\n\n- ~~`get_team_rankings`~~ — does not exist. Use `get_athlete_profile` for individual data.\n- ~~`search_athletes`~~ — does not exist. The correct command is `search_athlete` (no trailing 's').\n- ~~`fetch_news`~~ — does not exist. The correct command is `get_news`.\n\nIf a command is not listed in the Commands table above, it does not exist.\n\n## Error Handling\n\nWhen a command fails, **do not surface raw errors to the user**. Instead:\n1. For `get_athlete_profile`: confirm `athlete_id`, `school`, and `name` match the TFRRS URL exactly (case-sensitive)\n2. For `search_athlete`: verify the team slug is correct by checking the team's TFRRS page URL\n3. For `get_meet_results`: verify the `meet_id` and `slug` match the meet's TFRRS URL exactly\n4. For `get_team_roster`: verify the school slug is correct\n5. For `get_news`: if the feed fails, inform the user that The Stride Report may be temporarily unavailable\n6. Report failure with a clean message only after exhausting alternatives\n\n## Troubleshooting\n\n**`sports-skills` command not found**\nRun `pip install sports-skills` or install from GitHub (see Setup above).\n\n**HTTP 404 on athlete profile**\nThe `school` or `name` slug does not match the TFRRS URL exactly. Slugs are case-sensitive and use underscores. Copy directly from tfrrs.org.\n\n**`prs` returns empty dict**\nThe athlete's profile page may be very new or structured differently. Check the URL directly on tfrrs.org.\n\n**`search_athlete` returns empty matches**\nThe athlete is likely graduated or transferred. See Example 3 above for how to handle this.\n\n**`get_meet_results` returns no events**\nThe `meet_id` or `slug` may be incorrect. Copy both directly from the meet's TFRRS URL.\n\n**`get_news` fails or returns no articles**\nThe Stride Report RSS feed may be temporarily unavailable. Try again later.\n\n**Connection errors or timeouts**\nTFRRS may be temporarily unavailable. Requests are throttled to 1 per second automatically — wait a moment and retry.\n",{"name":5,"origin":24,"license":15,"version":25,"description":7,"compatibility":26},"github.com\u002Fmachina-sports\u002Fsports-skills (skill: xctf-data)","1.0.0","yana-ai >= 0.14.0","main","481dcd7dd2e288b9d627a2bd017db70e64e6c6fa",".claude\u002Fskills\u002Fsports--xctf-data",2,"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.","2026-11-14 13:24:09",{"source":8,"skillName":5,"commands":38,"prompt":48,"zipAvailable":49},[39,42,45],{"tool":40,"command":41},"npx","npx skills add Horonomos-laps\u002FYana-AI --skill sports--xctf-data",{"tool":43,"command":44},"bunx","bunx skills add Horonomos-laps\u002FYana-AI --skill sports--xctf-data",{"tool":46,"command":47},"pnpm","pnpm dlx skills add Horonomos-laps\u002FYana-AI --skill sports--xctf-data","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fsports--xctf-data\u002FSKILL.md",true,[51],{"path":52,"resourceType":53,"resourceTypeDesc":54,"sizeBytes":55,"sourceHtmlUrl":56},"scripts\u002Fvalidate_params.sh","SCRIPT","脚本",1295,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fsports--xctf-data\u002Fscripts\u002Fvalidate_params.sh",[58,65,73,81,89,97],{"skillNo":59,"name":60,"nameZh":6,"description":61,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":62,"categories":63,"keywords":64,"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":66,"name":67,"nameZh":6,"description":68,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":69,"licenseFileUrl":6,"sourceHtmlUrl":70,"categories":71,"keywords":72,"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":74,"name":75,"nameZh":6,"description":76,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":69,"licenseFileUrl":77,"sourceHtmlUrl":78,"categories":79,"keywords":80,"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":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":69,"licenseFileUrl":85,"sourceHtmlUrl":86,"categories":87,"keywords":88,"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":90,"name":91,"nameZh":6,"description":92,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":69,"licenseFileUrl":93,"sourceHtmlUrl":94,"categories":95,"keywords":96,"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":98,"name":99,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":69,"licenseFileUrl":6,"sourceHtmlUrl":100,"categories":101,"keywords":102,"publishedAt":19},"01M736TK27QMCXK0DVCH25SJN5","ramdisk-tmpfs-patterns","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Framdisk-tmpfs-patterns\u002FSKILL.md",[],[]]