[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M73FWBD41598EDXG20WD26CA":3,"skill-same:01M73FWBD41598EDXG20WD26CA":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},"01M73FWBD41598EDXG20WD26CA","sports--cbb-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\u002Fcore\u002Fskills\u002Fsports--cbb-data\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: sports--cbb-data\ndescription: >-\n  |\norigin: \"github.com\u002Fmachina-sports\u002Fsports-skills (skill: cbb-data)\"\nlicense: MIT\nversion: \"1.0.0\"\ncompatibility: \"yana-ai >= 0.14.0\"\n---\n\n# College Basketball Data (CBB)\n\nBefore writing queries, consult `references\u002Fapi-reference.md` for endpoints, conference IDs, team IDs, and data 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 with a Python version error, the package requires Python 3.10+. Find a compatible Python:\n```bash\npython3 --version  # check version\n# If \u003C 3.10, try: python3.12 -m pip install sports-skills\n# On macOS with Homebrew: \u002Fopt\u002Fhomebrew\u002Fbin\u002Fpython3.12 -m pip install sports-skills\n```\nNo API keys required.\n\n## Quick Start\n\nPrefer the CLI — it avoids Python import path issues:\n```bash\nsports-skills cbb get_scoreboard\nsports-skills cbb get_rankings\nsports-skills cbb get_standings --group=23\n```\n\n## CRITICAL: Before Any Query\n\nCRITICAL: Before calling any data endpoint, verify:\n- Season year is derived from the system prompt's `currentDate` — never hardcoded.\n- For standings, the `group` parameter is set to the correct conference ID (see `references\u002Fapi-reference.md`).\n- If only a team name is provided, use `get_teams` to resolve the team ID.\n\n## Choosing the Season\n\nDerive the current year from the system prompt's date (e.g., `currentDate: 2026-02-28` → current year is 2026).\n\n- **If the user specifies a season**, use it as-is.\n- **If the user says \"current\", \"this season\", or doesn't specify**: The CBB season runs November–April. If the current month is November or December, use `season = current_year + 1`. If January–April, use `season = current_year`. If May–October (offseason), use `season = current_year` (most recently completed season).\n\n## Important: College vs. Pro Differences\n\n- **Standings are per-conference** — use the `group` parameter to filter\n- **Rankings replace leaders** — college uses AP Top 25 and Coaches Poll\n- **Ranked teams** have a `rank` field (null = unranked) on scoreboard competitors\n- **360+ D1 teams** — many games per day during the season (50+ during conference play)\n- **March Madness** — NCAA Tournament runs in March\u002FApril with 68 teams\n\n## Commands\n\n| Command | Description |\n|---|---|\n| `get_scoreboard` | Live\u002Frecent college basketball scores |\n| `get_standings` | Standings by conference (use `group` parameter) |\n| `get_teams` | All 360+ D1 men's basketball teams |\n| `get_team_roster` | Full roster for a team |\n| `get_team_schedule` | Schedule for a specific team |\n| `get_game_summary` | Detailed box score and player stats |\n| `get_rankings` | AP Top 25 and Coaches Poll rankings |\n| `get_news` | College basketball news |\n| `get_play_by_play` | Full play-by-play for a game |\n| `get_win_probability` | Win probability chart data |\n| `get_schedule` | Schedule for a date or season |\n| `get_futures` | Futures\u002Fodds markets (National Championship, etc.) |\n| `get_team_stats` | Team statistical profile |\n| `get_player_stats` | Player statistical profile |\n\nSee `references\u002Fapi-reference.md` for full parameter lists and return shapes.\n\n## Examples\n\nExample 1: Current rankings\nUser says: \"What are the college basketball rankings?\"\nActions:\n1. Call `get_rankings()`\nResult: AP Top 25 and Coaches Poll with rank, previous rank, record, and points\n\nExample 2: Conference standings\nUser says: \"Show me SEC basketball standings\"\nActions:\n1. Derive season year from `currentDate`\n2. Call `get_standings(group=23, season=\u003Cderived_year>)` (group 23 = SEC)\nResult: SEC standings with W-L records per team\n\nExample 3: Today's scores\nUser says: \"What are today's college basketball scores?\"\nActions:\n1. Call `get_scoreboard()`\nResult: All live and recent CBB games with scores and ranked status\n\nExample 4: Team roster\nUser says: \"Show me Duke's roster\"\nActions:\n1. Call `get_team_roster(team_id=\"150\")`\nResult: Full Duke roster with name, position, jersey number\n\nExample 5: March Madness futures\nUser says: \"Who's favored to win March Madness?\"\nActions:\n1. Call `get_futures(limit=10)`\nResult: Top National Championship contenders with odds values\n\nExample 6: Team statistics\nUser says: \"Show me Duke's team stats\"\nActions:\n1. Derive season year from `currentDate`\n2. Call `get_team_stats(team_id=\"150\", season_year=\u003Cderived_year>)`\nResult: Duke's season stats by category with value, rank, and per-game averages\n\n## Commands that DO NOT exist — never call these\n\n- ~~`get_odds`~~ \u002F ~~`get_betting_odds`~~ — not available. For prediction market odds, use the polymarket or kalshi skill.\n- ~~`search_teams`~~ — does not exist. Use `get_teams` instead.\n- ~~`get_box_score`~~ — does not exist. Use `get_game_summary` instead.\n- ~~`get_player_ratings`~~ — does not exist. Use `get_player_stats` instead.\n- ~~`get_ap_poll`~~ — does not exist. Use `get_rankings` instead.\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. If no events found, check if it's the off-season (CBB runs November–April)\n2. If standings are empty without a group filter, try a specific conference\n3. During March Madness, the scoreboard will have tournament games\n4. Only report failure with a clean message after exhausting alternatives\n\n## Troubleshooting\n\nError: `sports-skills` command not found\nCause: Package not installed\nSolution: Run `pip install sports-skills`\n\nError: No games found on scoreboard\nCause: CBB is seasonal (November–April); off-season scoreboard will be empty\nSolution: Use `get_rankings` or `get_news` year-round; check `get_schedule` for when the season resumes\n\nError: Too many games returned — hard to filter\nCause: During the season, 50+ games per day are scheduled\nSolution: Use `--group` to filter by conference, or `--limit` to cap results\n\nError: Rankings empty\nCause: Rankings are published weekly during the season (November–March) only\nSolution: Use `get_news` in the offseason; rankings resume in November\n","# College Basketball Data (CBB)\n\nBefore writing queries, consult `references\u002Fapi-reference.md` for endpoints, conference IDs, team IDs, and data 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 with a Python version error, the package requires Python 3.10+. Find a compatible Python:\n```bash\npython3 --version  # check version\n# If \u003C 3.10, try: python3.12 -m pip install sports-skills\n# On macOS with Homebrew: \u002Fopt\u002Fhomebrew\u002Fbin\u002Fpython3.12 -m pip install sports-skills\n```\nNo API keys required.\n\n## Quick Start\n\nPrefer the CLI — it avoids Python import path issues:\n```bash\nsports-skills cbb get_scoreboard\nsports-skills cbb get_rankings\nsports-skills cbb get_standings --group=23\n```\n\n## CRITICAL: Before Any Query\n\nCRITICAL: Before calling any data endpoint, verify:\n- Season year is derived from the system prompt's `currentDate` — never hardcoded.\n- For standings, the `group` parameter is set to the correct conference ID (see `references\u002Fapi-reference.md`).\n- If only a team name is provided, use `get_teams` to resolve the team ID.\n\n## Choosing the Season\n\nDerive the current year from the system prompt's date (e.g., `currentDate: 2026-02-28` → current year is 2026).\n\n- **If the user specifies a season**, use it as-is.\n- **If the user says \"current\", \"this season\", or doesn't specify**: The CBB season runs November–April. If the current month is November or December, use `season = current_year + 1`. If January–April, use `season = current_year`. If May–October (offseason), use `season = current_year` (most recently completed season).\n\n## Important: College vs. Pro Differences\n\n- **Standings are per-conference** — use the `group` parameter to filter\n- **Rankings replace leaders** — college uses AP Top 25 and Coaches Poll\n- **Ranked teams** have a `rank` field (null = unranked) on scoreboard competitors\n- **360+ D1 teams** — many games per day during the season (50+ during conference play)\n- **March Madness** — NCAA Tournament runs in March\u002FApril with 68 teams\n\n## Commands\n\n| Command | Description |\n|---|---|\n| `get_scoreboard` | Live\u002Frecent college basketball scores |\n| `get_standings` | Standings by conference (use `group` parameter) |\n| `get_teams` | All 360+ D1 men's basketball teams |\n| `get_team_roster` | Full roster for a team |\n| `get_team_schedule` | Schedule for a specific team |\n| `get_game_summary` | Detailed box score and player stats |\n| `get_rankings` | AP Top 25 and Coaches Poll rankings |\n| `get_news` | College basketball news |\n| `get_play_by_play` | Full play-by-play for a game |\n| `get_win_probability` | Win probability chart data |\n| `get_schedule` | Schedule for a date or season |\n| `get_futures` | Futures\u002Fodds markets (National Championship, etc.) |\n| `get_team_stats` | Team statistical profile |\n| `get_player_stats` | Player statistical profile |\n\nSee `references\u002Fapi-reference.md` for full parameter lists and return shapes.\n\n## Examples\n\nExample 1: Current rankings\nUser says: \"What are the college basketball rankings?\"\nActions:\n1. Call `get_rankings()`\nResult: AP Top 25 and Coaches Poll with rank, previous rank, record, and points\n\nExample 2: Conference standings\nUser says: \"Show me SEC basketball standings\"\nActions:\n1. Derive season year from `currentDate`\n2. Call `get_standings(group=23, season=\u003Cderived_year>)` (group 23 = SEC)\nResult: SEC standings with W-L records per team\n\nExample 3: Today's scores\nUser says: \"What are today's college basketball scores?\"\nActions:\n1. Call `get_scoreboard()`\nResult: All live and recent CBB games with scores and ranked status\n\nExample 4: Team roster\nUser says: \"Show me Duke's roster\"\nActions:\n1. Call `get_team_roster(team_id=\"150\")`\nResult: Full Duke roster with name, position, jersey number\n\nExample 5: March Madness futures\nUser says: \"Who's favored to win March Madness?\"\nActions:\n1. Call `get_futures(limit=10)`\nResult: Top National Championship contenders with odds values\n\nExample 6: Team statistics\nUser says: \"Show me Duke's team stats\"\nActions:\n1. Derive season year from `currentDate`\n2. Call `get_team_stats(team_id=\"150\", season_year=\u003Cderived_year>)`\nResult: Duke's season stats by category with value, rank, and per-game averages\n\n## Commands that DO NOT exist — never call these\n\n- ~~`get_odds`~~ \u002F ~~`get_betting_odds`~~ — not available. For prediction market odds, use the polymarket or kalshi skill.\n- ~~`search_teams`~~ — does not exist. Use `get_teams` instead.\n- ~~`get_box_score`~~ — does not exist. Use `get_game_summary` instead.\n- ~~`get_player_ratings`~~ — does not exist. Use `get_player_stats` instead.\n- ~~`get_ap_poll`~~ — does not exist. Use `get_rankings` instead.\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. If no events found, check if it's the off-season (CBB runs November–April)\n2. If standings are empty without a group filter, try a specific conference\n3. During March Madness, the scoreboard will have tournament games\n4. Only report failure with a clean message after exhausting alternatives\n\n## Troubleshooting\n\nError: `sports-skills` command not found\nCause: Package not installed\nSolution: Run `pip install sports-skills`\n\nError: No games found on scoreboard\nCause: CBB is seasonal (November–April); off-season scoreboard will be empty\nSolution: Use `get_rankings` or `get_news` year-round; check `get_schedule` for when the season resumes\n\nError: Too many games returned — hard to filter\nCause: During the season, 50+ games per day are scheduled\nSolution: Use `--group` to filter by conference, or `--limit` to cap results\n\nError: Rankings empty\nCause: Rankings are published weekly during the season (November–March) only\nSolution: Use `get_news` in the offseason; rankings resume in November\n",{"name":5,"origin":24,"license":15,"version":25,"description":7,"compatibility":26},"github.com\u002Fmachina-sports\u002Fsports-skills (skill: cbb-data)","1.0.0","yana-ai >= 0.14.0","main","481dcd7dd2e288b9d627a2bd017db70e64e6c6fa","core\u002Fskills\u002Fsports--cbb-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.","2026-11-13 13:15:29",{"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--cbb-data",{"tool":43,"command":44},"bunx","bunx skills add Horonomos-laps\u002FYana-AI --skill sports--cbb-data",{"tool":46,"command":47},"pnpm","pnpm dlx skills add Horonomos-laps\u002FYana-AI --skill sports--cbb-data","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fsports--cbb-data\u002FSKILL.md",true,[51],{"path":52,"resourceType":53,"resourceTypeDesc":54,"sizeBytes":55,"sourceHtmlUrl":56},"scripts\u002Fvalidate_params.sh","SCRIPT","脚本",1472,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fsports--cbb-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",[],[]]