[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6GJMEGAV4QJ4FVT4MY8VCWF":3,"skill-same:01M6GJMEGAV4QJ4FVT4MY8VCWF":90},{"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":37,"linkOnly":38,"markdownContent":39,"markdownBody":40,"frontMatter":41,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":6,"ownerHtmlUrl":53,"ownerBlogUrl":6,"ownerDescription":54,"updatedAt":55,"install":56,"resources":69},"01M6GJMEGAV4QJ4FVT4MY8VCWF","specstory-link-trail",null,"Track all URLs fetched during SpecStory AI coding sessions. Run when user says \"show my link trail\", \"what URLs did I visit\", \"list fetched links\", or \"show web fetches\".","zapabob\u002FSkills","zapabob","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130830376?v=4","01M6DBMYZAGRTFQDSQYW3W764P","峯岸 亮","01M6DBMZ3GKDSJ01NZ9XTZD7JD",2,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fspecstory-link-trail\u002Fvariants\u002Fcursor-staging\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36],"link","specstory link trail","user","my","visit","links","pattern","show","ai coding","web","list","read","history","coding","Bash","file","run","sessions","2026-11-10 10:12:30",false,"---\nname: specstory-link-trail\ndescription: Track all URLs fetched during SpecStory AI coding sessions. Run when user says \"show my link trail\", \"what URLs did I visit\", \"list fetched links\", or \"show web fetches\".\nlicense: Apache-2.0\nmetadata:\n  author: SpecStory, Inc.\n  version: \"1.0.0\"\n  argument-hint: \"[history-file-or-pattern]\"\nallowed-tools: Bash, Read\nshort_description: Track all URLs fetched during SpecStory AI coding sessions. Run when user says \"show my link trail\", \"what URLs did I visit\", \"list fetched \n---\n\n# SpecStory Link Trail\n\nReviews your `.specstory\u002Fhistory` sessions and creates a summary of all URLs that were fetched via WebFetch tool calls. Useful for auditing external resources accessed during development.\n\n## How It Works\n\n1. **Parses** SpecStory history files for WebFetch tool calls\n2. **Extracts** URLs, status codes, and context\n3. **Groups** by session with timestamps\n4. **Separates** successful fetches from failures\n5. **Deduplicates** repeated URLs with fetch counts\n\n## Why Track Links?\n\nDuring AI-assisted coding, your assistant fetches documentation, APIs, and resources on your behalf. Link Trail helps you:\n- Audit what external resources were accessed\n- Find that documentation page you saw earlier\n- Review failed fetches that might need retry\n- Understand your research patterns\n\n## Usage\n\n### Slash Command\n\n| User says | Script behavior |\n|-----------|-----------------|\n| `\u002Fspecstory-link-trail` | All sessions in history |\n| `\u002Fspecstory-link-trail today` | Today's sessions only |\n| `\u002Fspecstory-link-trail last session` | Most recent session |\n| `\u002Fspecstory-link-trail 2026-01-22` | Sessions from specific date |\n| `\u002Fspecstory-link-trail *.md` | Custom glob pattern |\n\n### Direct Script Usage\n\n```bash\n# All sessions\npython skills\u002Fspecstory-link-trail\u002Fparse_webfetch.py .specstory\u002Fhistory\u002F*.md | \\\n  python skills\u002Fspecstory-link-trail\u002Fgenerate_report.py -\n\n# Specific session\npython skills\u002Fspecstory-link-trail\u002Fparse_webfetch.py .specstory\u002Fhistory\u002F2026-01-22*.md | \\\n  python skills\u002Fspecstory-link-trail\u002Fgenerate_report.py -\n\n# Sessions from a date range\npython skills\u002Fspecstory-link-trail\u002Fparse_webfetch.py .specstory\u002Fhistory\u002F2026-01-2*.md | \\\n  python skills\u002Fspecstory-link-trail\u002Fgenerate_report.py -\n```\n\n## Output\n\n```\nLink Trail Report\n=================\n\nSessions analyzed: 5\nTotal URLs fetched: 23 (18 successful, 5 failed)\n\nSession: fix-authentication-bug (2026-01-22)\n--------------------------------------------\nSuccessful fetches:\n  - https:\u002F\u002Fdocs.github.com\u002Fen\u002Frest\u002Fauthentication (×2)\n  - https:\u002F\u002Fjwt.io\u002Fintroduction\n  - https:\u002F\u002Fdeveloper.mozilla.org\u002Fen-US\u002Fdocs\u002FWeb\u002FHTTP\u002FStatus\u002F401\n\nFailed fetches:\n  - https:\u002F\u002Finternal.company.com\u002Fapi\u002Fdocs (403 Forbidden)\n\nSession: add-caching-layer (2026-01-21)\n---------------------------------------\nSuccessful fetches:\n  - https:\u002F\u002Fredis.io\u002Fdocs\u002Flatest\u002Fcommands\n  - https:\u002F\u002Fdocs.python.org\u002F3\u002Flibrary\u002Ffunctools.html#functools.lru_cache\n  - https:\u002F\u002Fstackoverflow.com\u002Fquestions\u002F... (×3)\n\nSummary by Domain\n-----------------\n  github.com: 5 fetches\n  stackoverflow.com: 4 fetches\n  docs.python.org: 3 fetches\n  redis.io: 2 fetches\n  (9 other domains): 9 fetches\n```\n\n## Present Results to User\n\nThe script output IS the report. Present it directly without additional commentary, but you may:\n\n1. **Highlight key findings** - Most frequently accessed domains, any failed fetches\n2. **Offer follow-ups** - \"Want me to retry the failed fetches?\" or \"Need details on any of these?\"\n\n### Example Response\n\n```\nHere's your link trail from recent sessions:\n\n[script output here]\n\nI noticed 5 failed fetches - mostly internal URLs that require authentication.\nThe most accessed domain was github.com (5 fetches), mostly for their REST API docs.\n\nWould you like me to:\n- Retry any of the failed fetches?\n- Open any of these links?\n- Filter to a specific session?\n```\n\n## Notes\n\n- Uses streaming parsing for large history files\n- URLs are extracted from WebFetch tool calls in the history\n- Fetch counts show when the same URL was accessed multiple times\n- Failed fetches include the HTTP status code when available\n","# SpecStory Link Trail\n\nReviews your `.specstory\u002Fhistory` sessions and creates a summary of all URLs that were fetched via WebFetch tool calls. Useful for auditing external resources accessed during development.\n\n## How It Works\n\n1. **Parses** SpecStory history files for WebFetch tool calls\n2. **Extracts** URLs, status codes, and context\n3. **Groups** by session with timestamps\n4. **Separates** successful fetches from failures\n5. **Deduplicates** repeated URLs with fetch counts\n\n## Why Track Links?\n\nDuring AI-assisted coding, your assistant fetches documentation, APIs, and resources on your behalf. Link Trail helps you:\n- Audit what external resources were accessed\n- Find that documentation page you saw earlier\n- Review failed fetches that might need retry\n- Understand your research patterns\n\n## Usage\n\n### Slash Command\n\n| User says | Script behavior |\n|-----------|-----------------|\n| `\u002Fspecstory-link-trail` | All sessions in history |\n| `\u002Fspecstory-link-trail today` | Today's sessions only |\n| `\u002Fspecstory-link-trail last session` | Most recent session |\n| `\u002Fspecstory-link-trail 2026-01-22` | Sessions from specific date |\n| `\u002Fspecstory-link-trail *.md` | Custom glob pattern |\n\n### Direct Script Usage\n\n```bash\n# All sessions\npython skills\u002Fspecstory-link-trail\u002Fparse_webfetch.py .specstory\u002Fhistory\u002F*.md | \\\n  python skills\u002Fspecstory-link-trail\u002Fgenerate_report.py -\n\n# Specific session\npython skills\u002Fspecstory-link-trail\u002Fparse_webfetch.py .specstory\u002Fhistory\u002F2026-01-22*.md | \\\n  python skills\u002Fspecstory-link-trail\u002Fgenerate_report.py -\n\n# Sessions from a date range\npython skills\u002Fspecstory-link-trail\u002Fparse_webfetch.py .specstory\u002Fhistory\u002F2026-01-2*.md | \\\n  python skills\u002Fspecstory-link-trail\u002Fgenerate_report.py -\n```\n\n## Output\n\n```\nLink Trail Report\n=================\n\nSessions analyzed: 5\nTotal URLs fetched: 23 (18 successful, 5 failed)\n\nSession: fix-authentication-bug (2026-01-22)\n--------------------------------------------\nSuccessful fetches:\n  - https:\u002F\u002Fdocs.github.com\u002Fen\u002Frest\u002Fauthentication (×2)\n  - https:\u002F\u002Fjwt.io\u002Fintroduction\n  - https:\u002F\u002Fdeveloper.mozilla.org\u002Fen-US\u002Fdocs\u002FWeb\u002FHTTP\u002FStatus\u002F401\n\nFailed fetches:\n  - https:\u002F\u002Finternal.company.com\u002Fapi\u002Fdocs (403 Forbidden)\n\nSession: add-caching-layer (2026-01-21)\n---------------------------------------\nSuccessful fetches:\n  - https:\u002F\u002Fredis.io\u002Fdocs\u002Flatest\u002Fcommands\n  - https:\u002F\u002Fdocs.python.org\u002F3\u002Flibrary\u002Ffunctools.html#functools.lru_cache\n  - https:\u002F\u002Fstackoverflow.com\u002Fquestions\u002F... (×3)\n\nSummary by Domain\n-----------------\n  github.com: 5 fetches\n  stackoverflow.com: 4 fetches\n  docs.python.org: 3 fetches\n  redis.io: 2 fetches\n  (9 other domains): 9 fetches\n```\n\n## Present Results to User\n\nThe script output IS the report. Present it directly without additional commentary, but you may:\n\n1. **Highlight key findings** - Most frequently accessed domains, any failed fetches\n2. **Offer follow-ups** - \"Want me to retry the failed fetches?\" or \"Need details on any of these?\"\n\n### Example Response\n\n```\nHere's your link trail from recent sessions:\n\n[script output here]\n\nI noticed 5 failed fetches - mostly internal URLs that require authentication.\nThe most accessed domain was github.com (5 fetches), mostly for their REST API docs.\n\nWould you like me to:\n- Retry any of the failed fetches?\n- Open any of these links?\n- Filter to a specific session?\n```\n\n## Notes\n\n- Uses streaming parsing for large history files\n- URLs are extracted from WebFetch tool calls in the history\n- Fetch counts show when the same URL was accessed multiple times\n- Failed fetches include the HTTP status code when available\n",{"name":5,"license":15,"metadata":42,"description":7,"allowed-tools":46,"short_description":47},{"author":43,"version":44,"argument-hint":45},"SpecStory, Inc.","1.0.0","[history-file-or-pattern]","Bash, Read","Track all URLs fetched during SpecStory AI coding sessions. Run when user says \"show my link trail\", \"what URLs did I visit\", \"list fetched","main","0d1434f89f4bc6b07e9d272accd8c1013768820f","registry\u002Fskills\u002Fspecstory-link-trail\u002Fvariants\u002Fcursor-staging",0,"https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills","https:\u002F\u002Fgithub.com\u002Fzapabob","The Open University of JAPAN　2019-now\r\n\r\nTokyo University of Science　2007-2010","2026-10-26 16:29:01",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add zapabob\u002FSkills --skill specstory-link-trail",{"tool":62,"command":63},"bunx","bunx skills add zapabob\u002FSkills --skill specstory-link-trail",{"tool":65,"command":66},"pnpm","pnpm dlx skills add zapabob\u002FSkills --skill specstory-link-trail","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fspecstory-link-trail\u002Fvariants\u002Fcursor-staging\u002FSKILL.md",true,[70,76,80,86],{"path":71,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":74,"sourceHtmlUrl":75},"extract_urls_context.py","SCRIPT","脚本",11219,"https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fspecstory-link-trail\u002Fvariants\u002Fcursor-staging\u002Fextract_urls_context.py",{"path":77,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":78,"sourceHtmlUrl":79},"generate_report.py",8713,"https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fspecstory-link-trail\u002Fvariants\u002Fcursor-staging\u002Fgenerate_report.py",{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":84,"sourceHtmlUrl":85},"LICENSE.txt","LICENSE","许可证",11356,"https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fspecstory-link-trail\u002Fvariants\u002Fcursor-staging\u002FLICENSE.txt",{"path":87,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":88,"sourceHtmlUrl":89},"parse_webfetch.py",8640,"https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fspecstory-link-trail\u002Fvariants\u002Fcursor-staging\u002Fparse_webfetch.py",[91,130,165,192,219,236],{"skillNo":92,"name":93,"nameZh":6,"description":94,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":95,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":111,"publishedAt":37},"01M6GJTE1GESGGF9K028Y7753E","xurl","X\u002FTwitter via xurl CLI: post, search, DM, media, v2 API.","MIT","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fxurl\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[98,103,106],{"categoryNo":99,"categoryName":100,"taxonomyType":101,"taxonomyTypeDesc":102},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":104,"categoryName":105,"taxonomyType":101,"taxonomyTypeDesc":102},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":107,"categoryName":108,"taxonomyType":109,"taxonomyTypeDesc":110},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[93,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,48,127,128,129],"openclaw","macos","cli","github","linux","windows","official","search","https","social-media","api","Media","hermes","hermes agent","twitter","social","via","post",{"skillNo":131,"name":132,"nameZh":6,"description":133,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":95,"licenseFileUrl":6,"sourceHtmlUrl":134,"categories":135,"keywords":147,"publishedAt":37},"01M6GJT8S1PXQ8WPXT1HSNBWH2","writing-plans","Write implementation plans: bite-sized tasks, paths, code.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwriting-plans\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[136,139,142,143,144],{"categoryNo":137,"categoryName":138,"taxonomyType":101,"taxonomyTypeDesc":102},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":140,"categoryName":141,"taxonomyType":101,"taxonomyTypeDesc":102},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":104,"categoryName":105,"taxonomyType":101,"taxonomyTypeDesc":102},{"categoryNo":107,"categoryName":108,"taxonomyType":109,"taxonomyTypeDesc":110},{"categoryNo":145,"categoryName":146,"taxonomyType":109,"taxonomyTypeDesc":110},"01JBSEEDCAT000000000000036","内容创作者",[148,149,150,151,113,152,116,153,117,154,155,156,157,158,159,160,161,162,163,164],"writing","writing plans","plans","design","review","workflow","documentation","tasks","development","code","planning","code-review","subagent","write","superpowers","paths","test-driven-development",{"skillNo":166,"name":167,"nameZh":6,"description":168,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":95,"licenseFileUrl":6,"sourceHtmlUrl":169,"categories":170,"keywords":174,"publishedAt":37},"01M6GJST0H5X7WHBJ3BZK0DVKH","whisper","OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwhisper\u002Fvariants\u002Fhermes-agent-optional\u002FSKILL.md",[171],{"categoryNo":172,"categoryName":173,"taxonomyType":101,"taxonomyTypeDesc":102},"01JBSEEDCAT000000000000016","图像与多媒体",[167,113,116,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191],"openai","speech","multimodal","Transformers","ASR","Audio","text","model","speech recognition","use","general","multilingual","translation","english","identification","processing","Audio Processing",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":95,"licenseFileUrl":6,"sourceHtmlUrl":196,"categories":197,"keywords":201,"publishedAt":37},"01M6GJSMRQ8EETZTYMG72P70EA","weights-and-biases","W&B: log ML experiments, sweeps, model registry, dashboards.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fweights-and-biases\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[198],{"categoryNo":199,"categoryName":200,"taxonomyType":101,"taxonomyTypeDesc":102},"01JBSEEDCAT000000000000013","分析与可视化",[202,113,203,204,117,205,206,207,208,209,210,182,211,212,213,214,215,216,217,218],"weights and biases","tensorflow","experiments","pytorch","visualization","registry","real-time","tuning","dashboards","experiment","log","time","Experiment Tracking","Model Registry","Hyperparameter Tuning","WandB","Real-Time Visualization",{"skillNo":220,"name":221,"nameZh":6,"description":222,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":95,"licenseFileUrl":6,"sourceHtmlUrl":223,"categories":224,"keywords":226,"publishedAt":37},"01M6GJS19KDPRY112JTR326S06","watchers","Poll RSS, JSON APIs, and GitHub with watermark dedup.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwatchers\u002Fvariants\u002Fhermes-agent-optional\u002FSKILL.md",[225],{"categoryNo":104,"categoryName":105,"taxonomyType":101,"taxonomyTypeDesc":102},[221,113,227,115,116,228,229,230,231,232,233,124,125,234,235],"terminal","automation","http","monitoring","cron","json","rss","devops","with",{"skillNo":237,"name":238,"nameZh":6,"description":239,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":95,"licenseFileUrl":6,"sourceHtmlUrl":240,"categories":241,"keywords":244,"publishedAt":37},"01M6GJRHJD2A6Q830SWF9W48BC","serving-llms-vllm","vLLM: high-throughput LLM serving, OpenAI API, quantization.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fvllm\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[242,243],{"categoryNo":99,"categoryName":100,"taxonomyType":101,"taxonomyTypeDesc":102},{"categoryNo":107,"categoryName":108,"taxonomyType":109,"taxonomyTypeDesc":110},[245,246,247,116,248,175,249,250,251,178,252,122,253,254,255,256,257,258,259,260],"llms","vLLM","serving llms vllm","research","openai api","tensor","Inference Serving","Production","llm serving","High Throughput","PagedAttention","Continuous Batching","Quantization","Tensor Parallelism","high-throughput","throughput"]