[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CZ6S2C54G03K71G77H22KE":3,"skill-same:01M6CZ6S2C54G03K71G77H22KE":104},{"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":23,"publishedAt":40,"linkOnly":41,"markdownContent":42,"markdownBody":43,"frontMatter":44,"refName":45,"commitSha":46,"skillDirectory":47,"forksCount":48,"repositoryHtmlUrl":49,"repositoryHomepageUrl":6,"ownerHtmlUrl":50,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":51,"install":52,"resources":65},"01M6CZ6S2C54G03K71G77H22KE","structured-intelligence-skill-creator",null,"Create or update repository skills that conform to local templates, provider metadata requirements, registry rules, and validation workflows.","Scientific-Tooling\u002Fstructured-intelligence","Scientific-Tooling","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F267453265?v=4","01M6CZ1SE6GGD4F67EAQ0PVX38","Scientific Tooling","01M6CZ1SJKCFVGH10Z3A152K02",4,"MIT","https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39],"skill creator","intelligence","structured","structured intelligence skill creator","workflows","create","update","registry","validation","metadata","repository","templates","Rules","provider","local","requirements","2026-11-10 10:12:30",false,"---\nname: structured-intelligence-skill-creator\ndescription: Create or update repository skills that conform to local templates, provider metadata requirements, registry rules, and validation workflows.\n---\n\n# Skill: structured-intelligence-skill-creator\n\n## Use When\n\n- A user wants to create a new skill in this repository under `skills\u002F\u003Cskill-id>\u002F`.\n- A user wants to update an existing repository skill without breaking local conventions.\n- The task must produce a Codex- and Claude-compatible skill bundle with matching registry metadata.\n\n## Inputs\n\n- Required:\n  - `skill-id` in `kebab-case`\n  - human-friendly skill name\n  - one-line description\n- Optional:\n  - owner override\n  - version override\n  - whether the skill needs `scripts\u002F`, `references\u002F`, or `assets\u002F`\n  - example prompts, input schema, or output contract\n\n## Workflow\n\n1. Confirm the task is a skill, not an agent. Skill folders live under `skills\u002F\u003Cid>\u002F`.\n2. Read only the local files needed to stay aligned with the repository:\n   - `docs\u002Fconventions.md`\n   - `skills\u002FREADME.md`\n   - `skills\u002Fregistry.yaml`\n   - `skills\u002F_templates\u002Fskill\u002F*`\n   - `references\u002Fproject-skill-checklist.md` from this skill when exact requirements are needed\n3. For a new skill, prefer deterministic scaffolding:\n   - If bundled scripts are available, run `scripts\u002Frun.sh \u003Cskill-id> [repo-root]`\n   - Otherwise run the repository helper: `.\u002Fscripts\u002Fbootstrap_new_skill.sh \u003Cskill-id>`\n4. Replace all template placeholders before finishing:\n   - `config.yaml`: `id`, `name`, `version`, `owner`, `description`\n   - `SKILL.md`: use conditions, inputs, workflow, output contract, limits\n   - `agents\u002Fopenai.yaml` and `agents\u002Fclaude.yaml`: matching display text and provider-specific default prompt\n5. Keep the bundle minimal:\n   - Add scripts only when deterministic execution or repeated logic is useful\n   - Add references only when they reduce `SKILL.md` size or hold project-specific detail\n   - Do not add generic changelogs, installation guides, or duplicate documentation\n6. Register the skill in `skills\u002Fregistry.yaml` and keep `id`, `name`, and `version` identical to `config.yaml`.\n7. Validate with `.\u002Fscripts\u002Fvalidate_structure.sh` before returning the task as complete.\n8. Report the created or updated files, validation result, and install commands for both tools.\n\n## Output Contract\n\n- `skills\u002F\u003Cskill-id>\u002Fconfig.yaml` with valid metadata\n- `skills\u002F\u003Cskill-id>\u002FSKILL.md` with explicit inputs, outputs, and limits\n- `skills\u002F\u003Cskill-id>\u002Fagents\u002Fopenai.yaml`\n- `skills\u002F\u003Cskill-id>\u002Fagents\u002Fclaude.yaml`\n- optional `scripts\u002F`, `references\u002F`, and `assets\u002F` only when justified\n- matching entry in `skills\u002Fregistry.yaml`\n- validation status from `.\u002Fscripts\u002Fvalidate_structure.sh`\n- install commands:\n  - `.\u002Fscripts\u002Finstall_skill.sh \u003Cskill-id>`\n  - `.\u002Fscripts\u002Finstall_skill.sh \u003Cskill-id> --tool claude`\n\n## Limits\n\n- Do not overwrite an existing skill blindly; read the current bundle first.\n- Do not leave placeholder strings from the template.\n- Do not introduce a registry entry without a real folder and matching config.\n- Common failure cases:\n  - invalid `kebab-case` id\n  - semver mismatch between registry and `config.yaml`\n  - missing `agents\u002Fopenai.yaml` or `agents\u002Fclaude.yaml`\n  - using the wrong default prompt format (`$skill-id` for OpenAI, bare `skill-id` for Claude)\n  - skipping `.\u002Fscripts\u002Fvalidate_structure.sh`\n","# Skill: structured-intelligence-skill-creator\n\n## Use When\n\n- A user wants to create a new skill in this repository under `skills\u002F\u003Cskill-id>\u002F`.\n- A user wants to update an existing repository skill without breaking local conventions.\n- The task must produce a Codex- and Claude-compatible skill bundle with matching registry metadata.\n\n## Inputs\n\n- Required:\n  - `skill-id` in `kebab-case`\n  - human-friendly skill name\n  - one-line description\n- Optional:\n  - owner override\n  - version override\n  - whether the skill needs `scripts\u002F`, `references\u002F`, or `assets\u002F`\n  - example prompts, input schema, or output contract\n\n## Workflow\n\n1. Confirm the task is a skill, not an agent. Skill folders live under `skills\u002F\u003Cid>\u002F`.\n2. Read only the local files needed to stay aligned with the repository:\n   - `docs\u002Fconventions.md`\n   - `skills\u002FREADME.md`\n   - `skills\u002Fregistry.yaml`\n   - `skills\u002F_templates\u002Fskill\u002F*`\n   - `references\u002Fproject-skill-checklist.md` from this skill when exact requirements are needed\n3. For a new skill, prefer deterministic scaffolding:\n   - If bundled scripts are available, run `scripts\u002Frun.sh \u003Cskill-id> [repo-root]`\n   - Otherwise run the repository helper: `.\u002Fscripts\u002Fbootstrap_new_skill.sh \u003Cskill-id>`\n4. Replace all template placeholders before finishing:\n   - `config.yaml`: `id`, `name`, `version`, `owner`, `description`\n   - `SKILL.md`: use conditions, inputs, workflow, output contract, limits\n   - `agents\u002Fopenai.yaml` and `agents\u002Fclaude.yaml`: matching display text and provider-specific default prompt\n5. Keep the bundle minimal:\n   - Add scripts only when deterministic execution or repeated logic is useful\n   - Add references only when they reduce `SKILL.md` size or hold project-specific detail\n   - Do not add generic changelogs, installation guides, or duplicate documentation\n6. Register the skill in `skills\u002Fregistry.yaml` and keep `id`, `name`, and `version` identical to `config.yaml`.\n7. Validate with `.\u002Fscripts\u002Fvalidate_structure.sh` before returning the task as complete.\n8. Report the created or updated files, validation result, and install commands for both tools.\n\n## Output Contract\n\n- `skills\u002F\u003Cskill-id>\u002Fconfig.yaml` with valid metadata\n- `skills\u002F\u003Cskill-id>\u002FSKILL.md` with explicit inputs, outputs, and limits\n- `skills\u002F\u003Cskill-id>\u002Fagents\u002Fopenai.yaml`\n- `skills\u002F\u003Cskill-id>\u002Fagents\u002Fclaude.yaml`\n- optional `scripts\u002F`, `references\u002F`, and `assets\u002F` only when justified\n- matching entry in `skills\u002Fregistry.yaml`\n- validation status from `.\u002Fscripts\u002Fvalidate_structure.sh`\n- install commands:\n  - `.\u002Fscripts\u002Finstall_skill.sh \u003Cskill-id>`\n  - `.\u002Fscripts\u002Finstall_skill.sh \u003Cskill-id> --tool claude`\n\n## Limits\n\n- Do not overwrite an existing skill blindly; read the current bundle first.\n- Do not leave placeholder strings from the template.\n- Do not introduce a registry entry without a real folder and matching config.\n- Common failure cases:\n  - invalid `kebab-case` id\n  - semver mismatch between registry and `config.yaml`\n  - missing `agents\u002Fopenai.yaml` or `agents\u002Fclaude.yaml`\n  - using the wrong default prompt format (`$skill-id` for OpenAI, bare `skill-id` for Claude)\n  - skipping `.\u002Fscripts\u002Fvalidate_structure.sh`\n",{"name":5,"description":7},"main","5118e7fda890e9aa819cb71e003cd243d3a31970","skills\u002Fstructured-intelligence-skill-creator",1,"https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence","https:\u002F\u002Fgithub.com\u002FScientific-Tooling","2026-11-03 00:01:40",{"source":8,"skillName":5,"commands":53,"prompt":63,"zipAvailable":64},[54,57,60],{"tool":55,"command":56},"npx","npx skills add Scientific-Tooling\u002Fstructured-intelligence --skill structured-intelligence-skill-creator",{"tool":58,"command":59},"bunx","bunx skills add Scientific-Tooling\u002Fstructured-intelligence --skill structured-intelligence-skill-creator",{"tool":61,"command":62},"pnpm","pnpm dlx skills add Scientific-Tooling\u002Fstructured-intelligence --skill structured-intelligence-skill-creator","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002FSKILL.md",true,[66,72,76,80,86,90,94,98],{"path":67,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":70,"sourceHtmlUrl":71},"agents\u002Fclaude.yaml","REFERENCE","参考文档",378,"https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002Fagents\u002Fclaude.yaml",{"path":73,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":74,"sourceHtmlUrl":75},"agents\u002Fopenai.yaml",379,"https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002Fagents\u002Fopenai.yaml",{"path":77,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":78,"sourceHtmlUrl":79},"agents\u002FREADME.md",322,"https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002Fagents\u002FREADME.md",{"path":81,"resourceType":82,"resourceTypeDesc":83,"sizeBytes":84,"sourceHtmlUrl":85},"assets\u002F.gitkeep","ASSET","资产文件",0,"https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002Fassets\u002F.gitkeep",{"path":87,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":88,"sourceHtmlUrl":89},"config.yaml",325,"https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002Fconfig.yaml",{"path":91,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":92,"sourceHtmlUrl":93},"references\u002Fproject-skill-checklist.md",1540,"https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002Freferences\u002Fproject-skill-checklist.md",{"path":95,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":96,"sourceHtmlUrl":97},"references\u002FREADME.md",68,"https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002Freferences\u002FREADME.md",{"path":99,"resourceType":100,"resourceTypeDesc":101,"sizeBytes":102,"sourceHtmlUrl":103},"scripts\u002Frun.sh","SCRIPT","脚本",1343,"https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstructured-intelligence-skill-creator\u002Fscripts\u002Frun.sh",[105,118,131,145,157,169],{"skillNo":106,"name":107,"nameZh":6,"description":108,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":109,"categories":110,"keywords":111,"publishedAt":40},"01M6CZ6M3JFN400406T1NPWNER","stat-survival-analysis","Estimate and compare survival functions using Kaplan-Meier curves and log-rank test, with optional Cox proportional hazards regression.","https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstat-survival-analysis\u002FSKILL.md",[],[112,113,114,115,116,117],"stat survival analysis","analysis","functions","log","regression","test",{"skillNo":119,"name":120,"nameZh":6,"description":121,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":122,"categories":123,"keywords":124,"publishedAt":40},"01M6CZ6G5JPDZASM4DRD9QCTEE","stat-pca","Perform PCA on a numeric data matrix to reduce dimensionality, visualize sample structure, and identify top contributing features.","https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstat-pca\u002FSKILL.md",[],[125,126,127,128,129,130],"stat pca","sample","structure","data","contributing","visualize",{"skillNo":132,"name":133,"nameZh":6,"description":134,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":135,"categories":136,"keywords":137,"publishedAt":40},"01M6CZ6D9A3N6849BT9VYFSBK5","stat-pairwise-correlation","Compute pairwise correlations and significance tests across all numeric variables, and produce a correlation heatmap.","https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstat-pairwise-correlation\u002FSKILL.md",[],[138,139,140,141,142,143,144],"stat pairwise correlation","correlation","compute","tests","across","heatmap","produce",{"skillNo":146,"name":147,"nameZh":6,"description":148,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":149,"categories":150,"keywords":151,"publishedAt":40},"01M6CZ69DMF1PDKW83RWARQX6D","stat-nonlinear-embedding","Embed high-dimensional data into 2D using t-SNE or UMAP for exploratory visualization of sample or cell relationships.","https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstat-nonlinear-embedding\u002FSKILL.md",[],[152,153,154,126,155,128,156],"stat nonlinear embedding","exploratory visualization","cell","relationships","visualization",{"skillNo":158,"name":159,"nameZh":6,"description":160,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":161,"categories":162,"keywords":163,"publishedAt":40},"01M6CZ65YZGJV40F2FZNH04PBS","stat-logistic-regression","Fit a logistic regression model for binary outcomes, report odds ratios and model performance (AUC-ROC, confusion matrix).","https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstat-logistic-regression\u002FSKILL.md",[],[164,116,165,166,167,168],"stat logistic regression","report","outcomes","performance","model",{"skillNo":170,"name":171,"nameZh":6,"description":172,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":173,"categories":174,"keywords":175,"publishedAt":40},"01M6CZ63JR8A7YR02312EY9AQ4","stat-learn-bayesian-network","Learn the structure and conditional probabilities of a Bayesian network from observational data for causal discovery or dependency modeling.","https:\u002F\u002Fgithub.com\u002FScientific-Tooling\u002Fstructured-intelligence\u002Fblob\u002Fmain\u002Fskills\u002Fstat-learn-bayesian-network\u002FSKILL.md",[],[176,177,178,128,179,180,127,181],"learn","network","stat learn bayesian network","discovery","dependency","modeling"]