[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M73FWKBQ0TGT7SMANF049SVB":3,"skill-same:01M73FWKBQ0TGT7SMANF049SVB":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},"01M73FWKBQ0TGT7SMANF049SVB","sports--football-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--football-data\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: sports--football-data\ndescription: >-\n  |\norigin: \"github.com\u002Fmachina-sports\u002Fsports-skills (skill: football-data)\"\nlicense: MIT\nversion: \"1.0.0\"\ncompatibility: \"yana-ai >= 0.14.0\"\n---\n\n# Football Data\n\nBefore writing queries, consult `references\u002Fapi-reference.md` for endpoints, ID conventions, 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 (package not found or Python version error), install from GitHub:\n```bash\npip install git+https:\u002F\u002Fgithub.com\u002Fmachina-sports\u002Fsports-skills.git\n```\nThe package requires Python 3.10+. If your default Python is older, use a specific version:\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 football get_daily_schedule\nsports-skills football get_season_standings --season_id=premier-league-2025\n```\n\nPython SDK (alternative):\n```python\nfrom sports_skills import football\n\nstandings = football.get_season_standings(season_id=\"premier-league-2025\")\nschedule = football.get_daily_schedule()\n```\n\n## CRITICAL: Before Any Query\n\nCRITICAL: Before calling any data endpoint, verify:\n- Season ID is derived from `get_current_season(competition_id=\"...\")` — never hardcoded.\n- Team ID is verified via `search_team(query=\"...\")` if only a name is provided.\n- `get_event_xg` and `get_event_players_statistics` (with xG) are only called for top-5 leagues (EPL, La Liga, Bundesliga, Serie A, Ligue 1).\n- `get_season_leaders` and `get_missing_players` are only called for Premier League seasons (season_id must start with `premier-league-`).\n\n## Choosing the Season\n\nDerive the current year from the system prompt's date (e.g., `currentDate: 2026-02-16` → current year is 2026).\n\n- **If the user specifies a season**, use it as-is.\n- **If the user says \"current\", \"latest\", or doesn't specify**: Call `get_current_season(competition_id=\"...\")` to get the active season_id. Do NOT guess or hardcode the year.\n- **Season format**: Always `{league-slug}-{year}` (e.g., `\"premier-league-2025\"` for the 2025-26 season). The year is the start year of the season, not the end year.\n- **MLS exception**: MLS runs spring-fall within a single calendar year. Use `get_current_season(competition_id=\"mls\")`.\n\n## Commands\n\n| Command | Description |\n|---|---|\n| `get_current_season` | Detect current season for a competition |\n| `get_competitions` | List available competitions with current season info |\n| `get_competition_seasons` | Available seasons for a competition |\n| `get_season_schedule` | Full season match schedule |\n| `get_season_standings` | League table for a season |\n| `get_season_leaders` | Top scorers\u002Fleaders (Premier League only) |\n| `get_season_teams` | Teams in a season |\n| `search_team` | Search for a team by name |\n| `search_player` | Search for a player by name |\n| `get_team_profile` | Basic team info (no squad\u002Froster) |\n| `get_daily_schedule` | All matches for a date across all leagues |\n| `get_event_summary` | Match summary with scores |\n| `get_event_lineups` | Match lineups |\n| `get_event_statistics` | Match team statistics |\n| `get_event_timeline` | Match timeline (goals, cards, subs) |\n| `get_team_schedule` | Schedule for a specific team |\n| `get_head_to_head` | UNAVAILABLE — returns empty |\n| `get_event_xg` | xG data (top 5 leagues only) |\n| `get_event_players_statistics` | Player-level match stats with optional xG |\n| `get_missing_players` | Injured\u002Fdoubtful players (Premier League only) |\n| `get_season_transfers` | Transfer history via Transfermarkt |\n| `get_player_season_stats` | Player season stats via ESPN |\n| `get_player_profile` | Player profile (FPL and\u002For Transfermarkt) |\n\nSee `references\u002Fapi-reference.md` for full parameter lists, return shapes, and data coverage table.\n\n## Examples\n\nExample 1: Premier League table\nUser says: \"Show me the Premier League table\"\nActions:\n1. Call `get_current_season(competition_id=\"premier-league\")` to get the current season_id\n2. Call `get_season_standings(season_id=\u003Cseason_id from step 1>)`\nResult: Standings table with position, team, played, won, drawn, lost, GD, points\n\nExample 2: Match report\nUser says: \"How did Arsenal vs Liverpool go?\"\nActions:\n1. Call `get_daily_schedule()` or `get_team_schedule(team_id=\"359\")` to find the event_id\n2. Call `get_event_summary(event_id=\"...\")` for the score\n3. Call `get_event_statistics(event_id=\"...\")` for possession, shots, etc.\n4. Call `get_event_xg(event_id=\"...\")` for xG comparison (EPL — top 5 only)\nResult: Match report with scores, key stats, and xG\n\nExample 3: Team deep dive\nUser says: \"Deep dive on Chelsea's recent form\"\nActions:\n1. Call `search_team(query=\"Chelsea\")` → team_id=363, competition=premier-league\n2. Call `get_team_schedule(team_id=\"363\", competition_id=\"premier-league\")` → find recent closed events\n3. For each recent match, call in parallel: `get_event_xg`, `get_event_statistics`, `get_event_players_statistics`\n4. Call `get_missing_players(season_id=\u003Cseason_id>)` → filter Chelsea's injured\u002Fdoubtful players\nResult: xG trend across matches, key player stats, and injury report\n\nExample 4: Player market value\nUser says: \"What's Saka's market value?\"\nActions:\n1. Call `get_player_profile(tm_player_id=\"433177\")` for Transfermarkt data\n2. Optionally add `fpl_id` for FPL stats\nResult: Market value, value history, and transfer history\n\nExample 5: Non-PL club\nUser says: \"Tell me about Corinthians\"\nActions:\n1. Call `search_team(query=\"Corinthians\")` → team_id=874, competition=serie-a-brazil\n2. Call `get_team_schedule(team_id=\"874\", competition_id=\"serie-a-brazil\")` for fixtures\n3. Pick a recent match and call `get_event_timeline(event_id=\"...\")` for goals, cards, subs\nResult: Fixtures, timeline events (note: xG, FPL stats, and season leaders NOT available for Brazilian Serie A)\n\n## Commands that DO NOT exist — never call these\n\n- ~~`get_standings`~~ — the correct command is `get_season_standings` (requires `season_id`).\n- ~~`get_live_scores`~~ — not available. Use `get_daily_schedule()` for today's matches.\n- ~~`get_team_squad`~~ \u002F ~~`get_team_roster`~~ — `get_team_profile` does NOT return players. Use `get_season_leaders` for PL player IDs, then `get_player_profile`.\n- ~~`get_transfers`~~ — the correct command is `get_season_transfers` (requires `season_id` + `tm_player_ids`).\n- ~~`get_match_results`~~ \u002F ~~`get_match`~~ — use `get_event_summary` with an `event_id`.\n- ~~`get_player_stats`~~ — use `get_event_players_statistics` for match-level stats, or `get_player_profile` for career data.\n- ~~`get_scores`~~ \u002F ~~`get_results`~~ — use `get_event_summary` with an `event_id`.\n- ~~`get_fixtures`~~ — use `get_daily_schedule` for today's matches or `get_season_schedule` for a full season.\n- ~~`get_league_table`~~ — use `get_season_standings` with a `season_id`.\n\nIf a command is not in the Commands table above, it does not exist. Do not try commands not listed.\n\n## Error Handling\n\nWhen a command fails (wrong event_id, missing data, network error, etc.), **do not surface the raw error to the user**. Instead:\n1. Catch it silently — treat the failure as an exploratory miss.\n2. Try alternatives — if an event_id returns no data, call `get_daily_schedule()` or `get_team_schedule()` to discover the correct ID.\n3. Only report failure after exhausting alternatives — use a clean message (e.g., \"I couldn't find that match — can you confirm the teams or date?\").\n\n## Troubleshooting\n\nError: `sports-skills` command not found\nCause: Package not installed\nSolution: Run `pip install sports-skills`. If not on PyPI, install from GitHub: `pip install git+https:\u002F\u002Fgithub.com\u002Fmachina-sports\u002Fsports-skills.git`\n\nError: `ModuleNotFoundError: No module named 'sports_skills'`\nCause: Package not installed or path issue\nSolution: Install the package. Prefer the CLI over Python imports to avoid path issues\n\nError: `get_season_leaders` or `get_missing_players` returns empty for a non-PL league\nCause: These commands only work for Premier League; they silently return empty for other leagues\nSolution: Check the Data Coverage table in `references\u002Fapi-reference.md`. For other leagues, use `get_event_players_statistics` for player data\n\nError: `get_team_profile` returns no players\nCause: This command does not return squad rosters — this is expected behavior\nSolution: For PL teams, use `get_season_leaders` to find player FPL IDs, then `get_player_profile(fpl_id=\"...\")`\n\nError: Wrong season_id format\nCause: Season ID must follow the `{league-slug}-{year}` format\nSolution: Use `get_current_season(competition_id=\"...\")` to discover the correct format. Example: `\"premier-league-2025\"`, not `\"2025-2026\"` or `\"EPL-2025\"`\n\nError: No xG data for a recent match\nCause: Understat data may lag 24-48 hours after a match ends\nSolution: If `get_event_xg` returns empty for a recent top-5 match, retry later. Only available for EPL, La Liga, Bundesliga, Serie A, Ligue 1\n\nError: Team or event ID unknown\nCause: ID was guessed instead of looked up\nSolution: Use `search_team(query=\"team name\")` to find team IDs, or `get_daily_schedule` \u002F `get_season_schedule` to find event IDs. Never guess IDs.\n","# Football Data\n\nBefore writing queries, consult `references\u002Fapi-reference.md` for endpoints, ID conventions, 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 (package not found or Python version error), install from GitHub:\n```bash\npip install git+https:\u002F\u002Fgithub.com\u002Fmachina-sports\u002Fsports-skills.git\n```\nThe package requires Python 3.10+. If your default Python is older, use a specific version:\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 football get_daily_schedule\nsports-skills football get_season_standings --season_id=premier-league-2025\n```\n\nPython SDK (alternative):\n```python\nfrom sports_skills import football\n\nstandings = football.get_season_standings(season_id=\"premier-league-2025\")\nschedule = football.get_daily_schedule()\n```\n\n## CRITICAL: Before Any Query\n\nCRITICAL: Before calling any data endpoint, verify:\n- Season ID is derived from `get_current_season(competition_id=\"...\")` — never hardcoded.\n- Team ID is verified via `search_team(query=\"...\")` if only a name is provided.\n- `get_event_xg` and `get_event_players_statistics` (with xG) are only called for top-5 leagues (EPL, La Liga, Bundesliga, Serie A, Ligue 1).\n- `get_season_leaders` and `get_missing_players` are only called for Premier League seasons (season_id must start with `premier-league-`).\n\n## Choosing the Season\n\nDerive the current year from the system prompt's date (e.g., `currentDate: 2026-02-16` → current year is 2026).\n\n- **If the user specifies a season**, use it as-is.\n- **If the user says \"current\", \"latest\", or doesn't specify**: Call `get_current_season(competition_id=\"...\")` to get the active season_id. Do NOT guess or hardcode the year.\n- **Season format**: Always `{league-slug}-{year}` (e.g., `\"premier-league-2025\"` for the 2025-26 season). The year is the start year of the season, not the end year.\n- **MLS exception**: MLS runs spring-fall within a single calendar year. Use `get_current_season(competition_id=\"mls\")`.\n\n## Commands\n\n| Command | Description |\n|---|---|\n| `get_current_season` | Detect current season for a competition |\n| `get_competitions` | List available competitions with current season info |\n| `get_competition_seasons` | Available seasons for a competition |\n| `get_season_schedule` | Full season match schedule |\n| `get_season_standings` | League table for a season |\n| `get_season_leaders` | Top scorers\u002Fleaders (Premier League only) |\n| `get_season_teams` | Teams in a season |\n| `search_team` | Search for a team by name |\n| `search_player` | Search for a player by name |\n| `get_team_profile` | Basic team info (no squad\u002Froster) |\n| `get_daily_schedule` | All matches for a date across all leagues |\n| `get_event_summary` | Match summary with scores |\n| `get_event_lineups` | Match lineups |\n| `get_event_statistics` | Match team statistics |\n| `get_event_timeline` | Match timeline (goals, cards, subs) |\n| `get_team_schedule` | Schedule for a specific team |\n| `get_head_to_head` | UNAVAILABLE — returns empty |\n| `get_event_xg` | xG data (top 5 leagues only) |\n| `get_event_players_statistics` | Player-level match stats with optional xG |\n| `get_missing_players` | Injured\u002Fdoubtful players (Premier League only) |\n| `get_season_transfers` | Transfer history via Transfermarkt |\n| `get_player_season_stats` | Player season stats via ESPN |\n| `get_player_profile` | Player profile (FPL and\u002For Transfermarkt) |\n\nSee `references\u002Fapi-reference.md` for full parameter lists, return shapes, and data coverage table.\n\n## Examples\n\nExample 1: Premier League table\nUser says: \"Show me the Premier League table\"\nActions:\n1. Call `get_current_season(competition_id=\"premier-league\")` to get the current season_id\n2. Call `get_season_standings(season_id=\u003Cseason_id from step 1>)`\nResult: Standings table with position, team, played, won, drawn, lost, GD, points\n\nExample 2: Match report\nUser says: \"How did Arsenal vs Liverpool go?\"\nActions:\n1. Call `get_daily_schedule()` or `get_team_schedule(team_id=\"359\")` to find the event_id\n2. Call `get_event_summary(event_id=\"...\")` for the score\n3. Call `get_event_statistics(event_id=\"...\")` for possession, shots, etc.\n4. Call `get_event_xg(event_id=\"...\")` for xG comparison (EPL — top 5 only)\nResult: Match report with scores, key stats, and xG\n\nExample 3: Team deep dive\nUser says: \"Deep dive on Chelsea's recent form\"\nActions:\n1. Call `search_team(query=\"Chelsea\")` → team_id=363, competition=premier-league\n2. Call `get_team_schedule(team_id=\"363\", competition_id=\"premier-league\")` → find recent closed events\n3. For each recent match, call in parallel: `get_event_xg`, `get_event_statistics`, `get_event_players_statistics`\n4. Call `get_missing_players(season_id=\u003Cseason_id>)` → filter Chelsea's injured\u002Fdoubtful players\nResult: xG trend across matches, key player stats, and injury report\n\nExample 4: Player market value\nUser says: \"What's Saka's market value?\"\nActions:\n1. Call `get_player_profile(tm_player_id=\"433177\")` for Transfermarkt data\n2. Optionally add `fpl_id` for FPL stats\nResult: Market value, value history, and transfer history\n\nExample 5: Non-PL club\nUser says: \"Tell me about Corinthians\"\nActions:\n1. Call `search_team(query=\"Corinthians\")` → team_id=874, competition=serie-a-brazil\n2. Call `get_team_schedule(team_id=\"874\", competition_id=\"serie-a-brazil\")` for fixtures\n3. Pick a recent match and call `get_event_timeline(event_id=\"...\")` for goals, cards, subs\nResult: Fixtures, timeline events (note: xG, FPL stats, and season leaders NOT available for Brazilian Serie A)\n\n## Commands that DO NOT exist — never call these\n\n- ~~`get_standings`~~ — the correct command is `get_season_standings` (requires `season_id`).\n- ~~`get_live_scores`~~ — not available. Use `get_daily_schedule()` for today's matches.\n- ~~`get_team_squad`~~ \u002F ~~`get_team_roster`~~ — `get_team_profile` does NOT return players. Use `get_season_leaders` for PL player IDs, then `get_player_profile`.\n- ~~`get_transfers`~~ — the correct command is `get_season_transfers` (requires `season_id` + `tm_player_ids`).\n- ~~`get_match_results`~~ \u002F ~~`get_match`~~ — use `get_event_summary` with an `event_id`.\n- ~~`get_player_stats`~~ — use `get_event_players_statistics` for match-level stats, or `get_player_profile` for career data.\n- ~~`get_scores`~~ \u002F ~~`get_results`~~ — use `get_event_summary` with an `event_id`.\n- ~~`get_fixtures`~~ — use `get_daily_schedule` for today's matches or `get_season_schedule` for a full season.\n- ~~`get_league_table`~~ — use `get_season_standings` with a `season_id`.\n\nIf a command is not in the Commands table above, it does not exist. Do not try commands not listed.\n\n## Error Handling\n\nWhen a command fails (wrong event_id, missing data, network error, etc.), **do not surface the raw error to the user**. Instead:\n1. Catch it silently — treat the failure as an exploratory miss.\n2. Try alternatives — if an event_id returns no data, call `get_daily_schedule()` or `get_team_schedule()` to discover the correct ID.\n3. Only report failure after exhausting alternatives — use a clean message (e.g., \"I couldn't find that match — can you confirm the teams or date?\").\n\n## Troubleshooting\n\nError: `sports-skills` command not found\nCause: Package not installed\nSolution: Run `pip install sports-skills`. If not on PyPI, install from GitHub: `pip install git+https:\u002F\u002Fgithub.com\u002Fmachina-sports\u002Fsports-skills.git`\n\nError: `ModuleNotFoundError: No module named 'sports_skills'`\nCause: Package not installed or path issue\nSolution: Install the package. Prefer the CLI over Python imports to avoid path issues\n\nError: `get_season_leaders` or `get_missing_players` returns empty for a non-PL league\nCause: These commands only work for Premier League; they silently return empty for other leagues\nSolution: Check the Data Coverage table in `references\u002Fapi-reference.md`. For other leagues, use `get_event_players_statistics` for player data\n\nError: `get_team_profile` returns no players\nCause: This command does not return squad rosters — this is expected behavior\nSolution: For PL teams, use `get_season_leaders` to find player FPL IDs, then `get_player_profile(fpl_id=\"...\")`\n\nError: Wrong season_id format\nCause: Season ID must follow the `{league-slug}-{year}` format\nSolution: Use `get_current_season(competition_id=\"...\")` to discover the correct format. Example: `\"premier-league-2025\"`, not `\"2025-2026\"` or `\"EPL-2025\"`\n\nError: No xG data for a recent match\nCause: Understat data may lag 24-48 hours after a match ends\nSolution: If `get_event_xg` returns empty for a recent top-5 match, retry later. Only available for EPL, La Liga, Bundesliga, Serie A, Ligue 1\n\nError: Team or event ID unknown\nCause: ID was guessed instead of looked up\nSolution: Use `search_team(query=\"team name\")` to find team IDs, or `get_daily_schedule` \u002F `get_season_schedule` to find event IDs. Never guess IDs.\n",{"name":5,"origin":24,"license":15,"version":25,"description":7,"compatibility":26},"github.com\u002Fmachina-sports\u002Fsports-skills (skill: football-data)","1.0.0","yana-ai >= 0.14.0","main","481dcd7dd2e288b9d627a2bd017db70e64e6c6fa","core\u002Fskills\u002Fsports--football-data",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":38,"prompt":48,"zipAvailable":49},[39,42,45],{"tool":40,"command":41},"npx","npx skills add Horonomos-laps\u002FYana-AI --skill sports--football-data",{"tool":43,"command":44},"bunx","bunx skills add Horonomos-laps\u002FYana-AI --skill sports--football-data",{"tool":46,"command":47},"pnpm","pnpm dlx skills add Horonomos-laps\u002FYana-AI --skill sports--football-data","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fsports--football-data\u002FSKILL.md",true,[51],{"path":52,"resourceType":53,"resourceTypeDesc":54,"sizeBytes":55,"sourceHtmlUrl":56},"scripts\u002Fvalidate_params.sh","SCRIPT","脚本",775,"https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fsports--football-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",[],[]]