[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6KM1H8DW0AZR3SH48YDBFVE":3,"skill-same:01M6KM1H8DW0AZR3SH48YDBFVE":66},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":44,"commitSha":45,"skillDirectory":46,"forksCount":47,"repositoryHtmlUrl":48,"repositoryHomepageUrl":49,"ownerHtmlUrl":50,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":51,"install":52,"resources":65},"01M6KM1H8DW0AZR3SH48YDBFVE","nlp-research-repo-package-installment",null,"Align Python version and repo-declared dependencies (requirements.txt \u002F environment.yml) before installing packages for NLP research code reproduction.","cxcscmu\u002FSkillLearnBench","cxcscmu","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F142838272?v=4","01M6KCQDFQWPDSN0MKZY96MSQP","01M6KCQDM7G70TKJ28NTSQC0RZ",93,"MIT","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Fnlp-paper-reproduction\u002Fnlp-research-repo-package-installment\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"nlp","research","package","repo","nlp research repo package installment","python","packages","code","environment","version","align","dependencies","requirements","research code","for","2026-11-10 10:12:30",false,"---\nname: nlp-research-repo-package-installment\nversion: \"1.0\"\ndescription: Align Python version and repo-declared dependencies (requirements.txt \u002F environment.yml) before installing packages for NLP research code reproduction.\n---\n\n# NLP Research Repo Package Installment\n\nWhen reproducing an NLP research repo, **always align the environment to the repo’s declared dependencies first**. Most failures come from **Python version mismatch** or installing packages without following `requirements.txt` \u002F `environment.yml`.\n\n## What to do (must run before any install)\n\n1. **Read the repo dependency files**\n- Prefer `environment.yml` \u002F `environment.yaml` (often pins **Python** + channels + non-pip deps)\n- Otherwise use `requirements.txt` (pip deps)\n- If both exist, treat `environment.yml` as the base, `requirements.txt` as supplemental unless README says otherwise\n\n2. **Log the current environment (Python version is critical)**  \nWrite `\u002Froot\u002Fpython_int.txt` containing:\n- `python -VV` *(required; Python version is often the root cause)*\n- `python -m pip --version`\n- `python -m pip freeze`\n\n3. **Compare & decide**\n- If the repo expects a specific Python major\u002Fminor and the current Python does not match, it’s usually best to **set up a matching environment**  before installing dependencies.\n        Example: set up a fresh Python 3.11 environment (Docker \u002F Ubuntu) with uv\n        # Install uv\n        apt-get update\n        apt-get install -y --no-install-recommends curl ca-certificates\n        rm -rf \u002Fvar\u002Flib\u002Fapt\u002Flists\u002F*\n        curl -LsSf https:\u002F\u002Fastral.sh\u002Fuv\u002F0.9.7\u002Finstall.sh | sh\n        export PATH=\"\u002Froot\u002F.local\u002Fbin:$PATH\"\n\n        # Install Python + create a venv\n        uv python install 3.11.8\n        uv venv --python 3.11.8 \u002Fopt\u002Fpy311\n\n        # Use the new Python for installs\u002Fruns\n        \u002Fopt\u002Fpy311\u002Fbin\u002Fpython -VV\n        \u002Fopt\u002Fpy311\u002Fbin\u002Fpython -m pip install -U pip setuptools wheel\n\n- Prefer installing from the repo’s dependency files (avoid random upgrades), then run a quick import\u002Fsmoke test.\n","# NLP Research Repo Package Installment\n\nWhen reproducing an NLP research repo, **always align the environment to the repo’s declared dependencies first**. Most failures come from **Python version mismatch** or installing packages without following `requirements.txt` \u002F `environment.yml`.\n\n## What to do (must run before any install)\n\n1. **Read the repo dependency files**\n- Prefer `environment.yml` \u002F `environment.yaml` (often pins **Python** + channels + non-pip deps)\n- Otherwise use `requirements.txt` (pip deps)\n- If both exist, treat `environment.yml` as the base, `requirements.txt` as supplemental unless README says otherwise\n\n2. **Log the current environment (Python version is critical)**  \nWrite `\u002Froot\u002Fpython_int.txt` containing:\n- `python -VV` *(required; Python version is often the root cause)*\n- `python -m pip --version`\n- `python -m pip freeze`\n\n3. **Compare & decide**\n- If the repo expects a specific Python major\u002Fminor and the current Python does not match, it’s usually best to **set up a matching environment**  before installing dependencies.\n        Example: set up a fresh Python 3.11 environment (Docker \u002F Ubuntu) with uv\n        # Install uv\n        apt-get update\n        apt-get install -y --no-install-recommends curl ca-certificates\n        rm -rf \u002Fvar\u002Flib\u002Fapt\u002Flists\u002F*\n        curl -LsSf https:\u002F\u002Fastral.sh\u002Fuv\u002F0.9.7\u002Finstall.sh | sh\n        export PATH=\"\u002Froot\u002F.local\u002Fbin:$PATH\"\n\n        # Install Python + create a venv\n        uv python install 3.11.8\n        uv venv --python 3.11.8 \u002Fopt\u002Fpy311\n\n        # Use the new Python for installs\u002Fruns\n        \u002Fopt\u002Fpy311\u002Fbin\u002Fpython -VV\n        \u002Fopt\u002Fpy311\u002Fbin\u002Fpython -m pip install -U pip setuptools wheel\n\n- Prefer installing from the repo’s dependency files (avoid random upgrades), then run a quick import\u002Fsmoke test.\n",{"name":5,"version":43,"description":7},"1.0","main","726e1f79b96b0cb3d729d0e55a1c847e0b5353ae","skills\u002Fhuman_authored\u002Fnlp-paper-reproduction\u002Fnlp-research-repo-package-installment",7,"https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench","https:\u002F\u002Fcxcscmu.github.io\u002FSkillLearnBench","https:\u002F\u002Fgithub.com\u002Fcxcscmu","2026-10-02 22:55:36",{"source":8,"skillName":5,"commands":53,"prompt":63,"zipAvailable":64},[54,57,60],{"tool":55,"command":56},"npx","npx skills add cxcscmu\u002FSkillLearnBench --skill nlp-research-repo-package-installment",{"tool":58,"command":59},"bunx","bunx skills add cxcscmu\u002FSkillLearnBench --skill nlp-research-repo-package-installment",{"tool":61,"command":62},"pnpm","pnpm dlx skills add cxcscmu\u002FSkillLearnBench --skill nlp-research-repo-package-installment","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Fnlp-paper-reproduction\u002Fnlp-research-repo-package-installment\u002FSKILL.md",true,[],[67,83,106,124,144,156],{"skillNo":68,"name":69,"nameZh":6,"description":70,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":71,"categories":72,"keywords":76,"publishedAt":38},"01M6KM5KH175P5ABP5JMX2SBDQ","object_counter","Count occurrences of an object in the image using computer vision algorithm.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Fvideo-object-counting\u002Fobject_counter\u002FSKILL.md",[73],{"categoryNo":74,"categoryName":75,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",[77,78,79,80,81,82],"object counter","object","vision","computer","Computer Vision","image",{"skillNo":84,"name":85,"nameZh":6,"description":86,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":87,"categories":88,"keywords":92,"publishedAt":38},"01M6KM51TMVXG79MMPCS6Y8G86","travel-planning-workflow","Invoke this skill when performing travel planning. It defines a structured workflow for generating itineraries. Following this workflow is essential to ensure the final plan satisfies user requirements.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftravel-planning\u002Ftravel-planning-workflow\u002FSKILL.md",[89],{"categoryNo":90,"categoryName":91,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[93,94,95,96,97,98,99,100,101,37,102,103,35,104,105],"workflow","planning","planning workflow","travel","travel planning","travel planning workflow","structured","performing","plan","user","it","essential","itineraries",{"skillNo":107,"name":108,"nameZh":6,"description":109,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":110,"categories":111,"keywords":112,"publishedAt":38},"01M6KM4DY820XHS9YTSK5QP5HD","bundled-dataset-search-tool","invoke this skill when you need to perform database search for travel planning. This skill provides some useful pre-packaged tools to look up accommodations, attractions, cities, driving distance, flights, and restaurants from the bundled dataset.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftravel-planning\u002Fbundled-dataset-search-tool\u002FSKILL.md",[],[113,114,115,116,117,118,119,96,120,121,97,122,37,123,94],"search","tool","dataset","bundled dataset search tool","restaurants","Tools","up","look","flights","you","database",{"skillNo":125,"name":126,"nameZh":6,"description":127,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":128,"categories":129,"keywords":130,"publishedAt":38},"01M6KM465BB9PQ0B548HQSVAWZ","glm-output","Output-processing guidance for GLM tasks. Especially useful after glm-basics and glm-calibration when you need verifier-matching metrics from output.nc and a final \u002Froot\u002Fmetrics.json.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftemperature-simulation\u002Fglm-output\u002FSKILL.md",[],[131,132,133,37,134,135,136,137,138,139,140,141,122,142,143],"glm output","output","glm","tasks","metrics","json","basics","guidance","matching","verifier","processing","root","calibration",{"skillNo":145,"name":146,"nameZh":6,"description":147,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":148,"categories":149,"keywords":151,"publishedAt":38},"01M6KM40KY3QWDW5W97S39R2BC","glm-calibration","Calibration guidance for GLM tasks. Often most effective after glm-basics has clarified the setup; glm-output is the companion skill for exact final metric computation.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftemperature-simulation\u002Fglm-calibration\u002FSKILL.md",[150],{"categoryNo":90,"categoryName":91,"taxonomyType":20,"taxonomyTypeDesc":21},[152,143,133,132,138,137,134,153,154,37,155],"glm calibration","setup","companion","metric",{"skillNo":157,"name":158,"nameZh":6,"description":159,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":160,"categories":161,"keywords":162,"publishedAt":38},"01M6KM3VHHVSGMGHJQB3PPT6YG","glm-basics","A good starting point for GLM calibration tasks. Use to inspect glm3.nml, confirm how GLM runs, and identify the relevant files before moving on to calibration and output evaluation.","https:\u002F\u002Fgithub.com\u002Fcxcscmu\u002FSkillLearnBench\u002Fblob\u002Fmain\u002Fskills\u002Fhuman_authored\u002Ftemperature-simulation\u002Fglm-basics\u002FSKILL.md",[],[163,133,137,164,152,143,37,132,165,166,167,168,169,170,134],"glm basics","inspect","relevant","files","good","use","how","Evaluation"]