[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6JDJKCVFQ1237H6EANAFWWV":3,"skill-same:01M6JDJKCVFQ1237H6EANAFWWV":79},{"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":37,"linkOnly":38,"markdownContent":39,"markdownBody":40,"frontMatter":41,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":46,"repositoryHtmlUrl":47,"repositoryHomepageUrl":48,"ownerHtmlUrl":49,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":50,"install":51,"resources":64},"01M6JDJKCVFQ1237H6EANAFWWV","skill-stocktake",null,"Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.","S3YED\u002Fappie-kit","S3YED","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F62743867?v=4","01M6JBKBRRVP6KMS0VWZ27T3R6","01M6JBKBX0KG30284PW1DBYJT1",14,"MIT","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fecc\u002Fskill-stocktake\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36],"skill stocktake","batch","Evaluation","subagent","quality","use","only","scan","commands","full","with","quick","for","modes","2026-11-10 10:12:30",false,"---\nname: skill-stocktake\ndescription: \"Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.\"\norigin: ECC\n---\n\n# skill-stocktake\n\nSlash command (`\u002Fskill-stocktake`) that audits all Claude skills and commands using a quality checklist + AI holistic judgment. Supports two modes: Quick Scan for recently changed skills, and Full Stocktake for a complete review.\n\n## Scope\n\nThe command targets the following paths **relative to the directory where it is invoked**:\n\n| Path | Description |\n|------|-------------|\n| `~\u002F.claude\u002Fskills\u002F` | Global skills (all projects) |\n| `{cwd}\u002F.claude\u002Fskills\u002F` | Project-level skills (if the directory exists) |\n\n**At the start of Phase 1, the command explicitly lists which paths were found and scanned.**\n\n### Targeting a specific project\n\nTo include project-level skills, run from that project's root directory:\n\n```bash\ncd ~\u002Fpath\u002Fto\u002Fmy-project\n\u002Fskill-stocktake\n```\n\nIf the project has no `.claude\u002Fskills\u002F` directory, only global skills and commands are evaluated.\n\n## Modes\n\n| Mode | Trigger | Duration |\n|------|---------|---------|\n| Quick Scan | `results.json` exists (default) | 5–10 min |\n| Full Stocktake | `results.json` absent, or `\u002Fskill-stocktake full` | 20–30 min |\n\n**Results cache:** `~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json`\n\n## Quick Scan Flow\n\nRe-evaluate only skills that have changed since the last run (5–10 min).\n\n1. Read `~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json`\n2. Run: `bash ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fscripts\u002Fquick-diff.sh \\\n         ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json`\n   (Project dir is auto-detected from `$PWD\u002F.claude\u002Fskills`; pass it explicitly only if needed)\n3. If output is `[]`: report \"No changes since last run.\" and stop\n4. Re-evaluate only those changed files using the same Phase 2 criteria\n5. Carry forward unchanged skills from previous results\n6. Output only the diff\n7. Run: `bash ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fscripts\u002Fsave-results.sh \\\n         ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json \u003C\u003C\u003C \"$EVAL_RESULTS\"`\n\n## Full Stocktake Flow\n\n### Phase 1 — Inventory\n\nRun: `bash ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fscripts\u002Fscan.sh`\n\nThe script enumerates skill files, extracts frontmatter, and collects UTC mtimes.\nProject dir is auto-detected from `$PWD\u002F.claude\u002Fskills`; pass it explicitly only if needed.\nPresent the scan summary and inventory table from the script output:\n\n```\nScanning:\n  ✓ ~\u002F.claude\u002Fskills\u002F         (17 files)\n  ✗ {cwd}\u002F.claude\u002Fskills\u002F    (not found — global skills only)\n```\n\n| Skill | 7d use | 30d use | Description |\n|-------|--------|---------|-------------|\n\n### Phase 2 — Quality Evaluation\n\nLaunch an Agent tool subagent (**general-purpose agent**) with the full inventory and checklist:\n\n```text\nAgent(\n  subagent_type=\"general-purpose\",\n  prompt=\"\nEvaluate the following skill inventory against the checklist.\n\n[INVENTORY]\n\n[CHECKLIST]\n\nReturn JSON for each skill:\n{ \\\"verdict\\\": \\\"Keep\\\"|\\\"Improve\\\"|\\\"Update\\\"|\\\"Retire\\\"|\\\"Merge into [X]\\\", \\\"reason\\\": \\\"...\\\" }\n\"\n)\n```\n\nThe subagent reads each skill, applies the checklist, and returns per-skill JSON:\n\n`{ \"verdict\": \"Keep\"|\"Improve\"|\"Update\"|\"Retire\"|\"Merge into [X]\", \"reason\": \"...\" }`\n\n**Chunk guidance:** Process ~20 skills per subagent invocation to keep context manageable. Save intermediate results to `results.json` (`status: \"in_progress\"`) after each chunk.\n\nAfter all skills are evaluated: set `status: \"completed\"`, proceed to Phase 3.\n\n**Resume detection:** If `status: \"in_progress\"` is found on startup, resume from the first unevaluated skill.\n\nEach skill is evaluated against this checklist:\n\n```\n- [ ] Content overlap with other skills checked\n- [ ] Overlap with MEMORY.md \u002F CLAUDE.md checked\n- [ ] Freshness of technical references verified (use WebSearch if tool names \u002F CLI flags \u002F APIs are present)\n- [ ] Usage frequency considered\n```\n\nVerdict criteria:\n\n| Verdict | Meaning |\n|---------|---------|\n| Keep | Useful and current |\n| Improve | Worth keeping, but specific improvements needed |\n| Update | Referenced technology is outdated (verify with WebSearch) |\n| Retire | Low quality, stale, or cost-asymmetric |\n| Merge into [X] | Substantial overlap with another skill; name the merge target |\n\nEvaluation is **holistic AI judgment** — not a numeric rubric. Guiding dimensions:\n- **Actionability**: code examples, commands, or steps that let you act immediately\n- **Scope fit**: name, trigger, and content are aligned; not too broad or narrow\n- **Uniqueness**: value not replaceable by MEMORY.md \u002F CLAUDE.md \u002F another skill\n- **Currency**: technical references work in the current environment\n\n**Reason quality requirements** — the `reason` field must be self-contained and decision-enabling:\n- Do NOT write \"unchanged\" alone — always restate the core evidence\n- For **Retire**: state (1) what specific defect was found, (2) what covers the same need instead\n  - Bad: `\"Superseded\"`\n  - Good: `\"disable-model-invocation: true already set; superseded by continuous-learning-v2 which covers all the same patterns plus confidence scoring. No unique content remains.\"`\n- For **Merge**: name the target and describe what content to integrate\n  - Bad: `\"Overlaps with X\"`\n  - Good: `\"42-line thin content; Step 4 of chatlog-to-article already covers the same workflow. Integrate the 'article angle' tip as a note in that skill.\"`\n- For **Improve**: describe the specific change needed (what section, what action, target size if relevant)\n  - Bad: `\"Too long\"`\n  - Good: `\"276 lines; Section 'Framework Comparison' (L80–140) duplicates ai-era-architecture-principles; delete it to reach ~150 lines.\"`\n- For **Keep** (mtime-only change in Quick Scan): restate the original verdict rationale, do not write \"unchanged\"\n  - Bad: `\"Unchanged\"`\n  - Good: `\"mtime updated but content unchanged. Unique Python reference explicitly imported by rules\u002Fpython\u002F; no overlap found.\"`\n\n### Phase 3 — Summary Table\n\n| Skill | 7d use | Verdict | Reason |\n|-------|--------|---------|--------|\n\n### Phase 4 — Consolidation\n\n1. **Retire \u002F Merge**: present detailed justification per file before confirming with user:\n   - What specific problem was found (overlap, staleness, broken references, etc.)\n   - What alternative covers the same functionality (for Retire: which existing skill\u002Frule; for Merge: the target file and what content to integrate)\n   - Impact of removal (any dependent skills, MEMORY.md references, or workflows affected)\n2. **Improve**: present specific improvement suggestions with rationale:\n   - What to change and why (e.g., \"trim 430→200 lines because sections X\u002FY duplicate python-patterns\")\n   - User decides whether to act\n3. **Update**: present updated content with sources checked\n4. Check MEMORY.md line count; propose compression if >100 lines\n\n## Results File Schema\n\n`~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json`:\n\n**`evaluated_at`**: Must be set to the actual UTC time of evaluation completion.\nObtain via Bash: `date -u +%Y-%m-%dT%H:%M:%SZ`. Never use a date-only approximation like `T00:00:00Z`.\n\n```json\n{\n  \"evaluated_at\": \"2026-02-21T10:00:00Z\",\n  \"mode\": \"full\",\n  \"batch_progress\": {\n    \"total\": 80,\n    \"evaluated\": 80,\n    \"status\": \"completed\"\n  },\n  \"skills\": {\n    \"skill-name\": {\n      \"path\": \"~\u002F.claude\u002Fskills\u002Fskill-name\u002FSKILL.md\",\n      \"verdict\": \"Keep\",\n      \"reason\": \"Concrete, actionable, unique value for X workflow\",\n      \"mtime\": \"2026-01-15T08:30:00Z\"\n    }\n  }\n}\n```\n\n## Notes\n\n- Evaluation is blind: the same checklist applies to all skills regardless of origin (ECC, self-authored, auto-extracted)\n- Archive \u002F delete operations always require explicit user confirmation\n- No verdict branching by skill origin\n","# skill-stocktake\n\nSlash command (`\u002Fskill-stocktake`) that audits all Claude skills and commands using a quality checklist + AI holistic judgment. Supports two modes: Quick Scan for recently changed skills, and Full Stocktake for a complete review.\n\n## Scope\n\nThe command targets the following paths **relative to the directory where it is invoked**:\n\n| Path | Description |\n|------|-------------|\n| `~\u002F.claude\u002Fskills\u002F` | Global skills (all projects) |\n| `{cwd}\u002F.claude\u002Fskills\u002F` | Project-level skills (if the directory exists) |\n\n**At the start of Phase 1, the command explicitly lists which paths were found and scanned.**\n\n### Targeting a specific project\n\nTo include project-level skills, run from that project's root directory:\n\n```bash\ncd ~\u002Fpath\u002Fto\u002Fmy-project\n\u002Fskill-stocktake\n```\n\nIf the project has no `.claude\u002Fskills\u002F` directory, only global skills and commands are evaluated.\n\n## Modes\n\n| Mode | Trigger | Duration |\n|------|---------|---------|\n| Quick Scan | `results.json` exists (default) | 5–10 min |\n| Full Stocktake | `results.json` absent, or `\u002Fskill-stocktake full` | 20–30 min |\n\n**Results cache:** `~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json`\n\n## Quick Scan Flow\n\nRe-evaluate only skills that have changed since the last run (5–10 min).\n\n1. Read `~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json`\n2. Run: `bash ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fscripts\u002Fquick-diff.sh \\\n         ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json`\n   (Project dir is auto-detected from `$PWD\u002F.claude\u002Fskills`; pass it explicitly only if needed)\n3. If output is `[]`: report \"No changes since last run.\" and stop\n4. Re-evaluate only those changed files using the same Phase 2 criteria\n5. Carry forward unchanged skills from previous results\n6. Output only the diff\n7. Run: `bash ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fscripts\u002Fsave-results.sh \\\n         ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json \u003C\u003C\u003C \"$EVAL_RESULTS\"`\n\n## Full Stocktake Flow\n\n### Phase 1 — Inventory\n\nRun: `bash ~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fscripts\u002Fscan.sh`\n\nThe script enumerates skill files, extracts frontmatter, and collects UTC mtimes.\nProject dir is auto-detected from `$PWD\u002F.claude\u002Fskills`; pass it explicitly only if needed.\nPresent the scan summary and inventory table from the script output:\n\n```\nScanning:\n  ✓ ~\u002F.claude\u002Fskills\u002F         (17 files)\n  ✗ {cwd}\u002F.claude\u002Fskills\u002F    (not found — global skills only)\n```\n\n| Skill | 7d use | 30d use | Description |\n|-------|--------|---------|-------------|\n\n### Phase 2 — Quality Evaluation\n\nLaunch an Agent tool subagent (**general-purpose agent**) with the full inventory and checklist:\n\n```text\nAgent(\n  subagent_type=\"general-purpose\",\n  prompt=\"\nEvaluate the following skill inventory against the checklist.\n\n[INVENTORY]\n\n[CHECKLIST]\n\nReturn JSON for each skill:\n{ \\\"verdict\\\": \\\"Keep\\\"|\\\"Improve\\\"|\\\"Update\\\"|\\\"Retire\\\"|\\\"Merge into [X]\\\", \\\"reason\\\": \\\"...\\\" }\n\"\n)\n```\n\nThe subagent reads each skill, applies the checklist, and returns per-skill JSON:\n\n`{ \"verdict\": \"Keep\"|\"Improve\"|\"Update\"|\"Retire\"|\"Merge into [X]\", \"reason\": \"...\" }`\n\n**Chunk guidance:** Process ~20 skills per subagent invocation to keep context manageable. Save intermediate results to `results.json` (`status: \"in_progress\"`) after each chunk.\n\nAfter all skills are evaluated: set `status: \"completed\"`, proceed to Phase 3.\n\n**Resume detection:** If `status: \"in_progress\"` is found on startup, resume from the first unevaluated skill.\n\nEach skill is evaluated against this checklist:\n\n```\n- [ ] Content overlap with other skills checked\n- [ ] Overlap with MEMORY.md \u002F CLAUDE.md checked\n- [ ] Freshness of technical references verified (use WebSearch if tool names \u002F CLI flags \u002F APIs are present)\n- [ ] Usage frequency considered\n```\n\nVerdict criteria:\n\n| Verdict | Meaning |\n|---------|---------|\n| Keep | Useful and current |\n| Improve | Worth keeping, but specific improvements needed |\n| Update | Referenced technology is outdated (verify with WebSearch) |\n| Retire | Low quality, stale, or cost-asymmetric |\n| Merge into [X] | Substantial overlap with another skill; name the merge target |\n\nEvaluation is **holistic AI judgment** — not a numeric rubric. Guiding dimensions:\n- **Actionability**: code examples, commands, or steps that let you act immediately\n- **Scope fit**: name, trigger, and content are aligned; not too broad or narrow\n- **Uniqueness**: value not replaceable by MEMORY.md \u002F CLAUDE.md \u002F another skill\n- **Currency**: technical references work in the current environment\n\n**Reason quality requirements** — the `reason` field must be self-contained and decision-enabling:\n- Do NOT write \"unchanged\" alone — always restate the core evidence\n- For **Retire**: state (1) what specific defect was found, (2) what covers the same need instead\n  - Bad: `\"Superseded\"`\n  - Good: `\"disable-model-invocation: true already set; superseded by continuous-learning-v2 which covers all the same patterns plus confidence scoring. No unique content remains.\"`\n- For **Merge**: name the target and describe what content to integrate\n  - Bad: `\"Overlaps with X\"`\n  - Good: `\"42-line thin content; Step 4 of chatlog-to-article already covers the same workflow. Integrate the 'article angle' tip as a note in that skill.\"`\n- For **Improve**: describe the specific change needed (what section, what action, target size if relevant)\n  - Bad: `\"Too long\"`\n  - Good: `\"276 lines; Section 'Framework Comparison' (L80–140) duplicates ai-era-architecture-principles; delete it to reach ~150 lines.\"`\n- For **Keep** (mtime-only change in Quick Scan): restate the original verdict rationale, do not write \"unchanged\"\n  - Bad: `\"Unchanged\"`\n  - Good: `\"mtime updated but content unchanged. Unique Python reference explicitly imported by rules\u002Fpython\u002F; no overlap found.\"`\n\n### Phase 3 — Summary Table\n\n| Skill | 7d use | Verdict | Reason |\n|-------|--------|---------|--------|\n\n### Phase 4 — Consolidation\n\n1. **Retire \u002F Merge**: present detailed justification per file before confirming with user:\n   - What specific problem was found (overlap, staleness, broken references, etc.)\n   - What alternative covers the same functionality (for Retire: which existing skill\u002Frule; for Merge: the target file and what content to integrate)\n   - Impact of removal (any dependent skills, MEMORY.md references, or workflows affected)\n2. **Improve**: present specific improvement suggestions with rationale:\n   - What to change and why (e.g., \"trim 430→200 lines because sections X\u002FY duplicate python-patterns\")\n   - User decides whether to act\n3. **Update**: present updated content with sources checked\n4. Check MEMORY.md line count; propose compression if >100 lines\n\n## Results File Schema\n\n`~\u002F.claude\u002Fskills\u002Fskill-stocktake\u002Fresults.json`:\n\n**`evaluated_at`**: Must be set to the actual UTC time of evaluation completion.\nObtain via Bash: `date -u +%Y-%m-%dT%H:%M:%SZ`. Never use a date-only approximation like `T00:00:00Z`.\n\n```json\n{\n  \"evaluated_at\": \"2026-02-21T10:00:00Z\",\n  \"mode\": \"full\",\n  \"batch_progress\": {\n    \"total\": 80,\n    \"evaluated\": 80,\n    \"status\": \"completed\"\n  },\n  \"skills\": {\n    \"skill-name\": {\n      \"path\": \"~\u002F.claude\u002Fskills\u002Fskill-name\u002FSKILL.md\",\n      \"verdict\": \"Keep\",\n      \"reason\": \"Concrete, actionable, unique value for X workflow\",\n      \"mtime\": \"2026-01-15T08:30:00Z\"\n    }\n  }\n}\n```\n\n## Notes\n\n- Evaluation is blind: the same checklist applies to all skills regardless of origin (ECC, self-authored, auto-extracted)\n- Archive \u002F delete operations always require explicit user confirmation\n- No verdict branching by skill origin\n",{"name":5,"origin":42,"description":7},"ECC","master","8ec37df6d71fb664ea19d32c079e7d3ff931a8e0","skills\u002Fecc\u002Fskill-stocktake",3,"https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit","https:\u002F\u002Fweblyfe.ai","https:\u002F\u002Fgithub.com\u002FS3YED","2026-08-27 01:54:02",{"source":8,"skillName":5,"commands":52,"prompt":62,"zipAvailable":63},[53,56,59],{"tool":54,"command":55},"npx","npx skills add S3YED\u002Fappie-kit --skill skill-stocktake",{"tool":57,"command":58},"bunx","bunx skills add S3YED\u002Fappie-kit --skill skill-stocktake",{"tool":60,"command":61},"pnpm","pnpm dlx skills add S3YED\u002Fappie-kit --skill skill-stocktake","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fecc\u002Fskill-stocktake\u002FSKILL.md",true,[65,71,75],{"path":66,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":70},"scripts\u002Fquick-diff.sh","SCRIPT","脚本",3271,"https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fecc\u002Fskill-stocktake\u002Fscripts\u002Fquick-diff.sh",{"path":72,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":73,"sourceHtmlUrl":74},"scripts\u002Fsave-results.sh",1952,"https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fecc\u002Fskill-stocktake\u002Fscripts\u002Fsave-results.sh",{"path":76,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":77,"sourceHtmlUrl":78},"scripts\u002Fscan.sh",5677,"https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fecc\u002Fskill-stocktake\u002Fscripts\u002Fscan.sh",[80,112,147,172,203,226],{"skillNo":81,"name":82,"nameZh":6,"description":83,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":84,"categories":85,"keywords":93,"publishedAt":37},"01M6JFD4M6N4DSGC7TXEJ5R3J2","ai-music","AI music generation and audio tools: HeartMuLa lyrics-to-music generation, songwriting craft (+ Suno prompts), and audio spectrogram\u002Ffeature visualization.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fwethlete\u002Fai-music\u002FSKILL.md",[86,89,92],{"categoryNo":87,"categoryName":88,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":90,"categoryName":91,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111],"music","ai music","humanizer","visualization","Tools","Audio","hermes","hermes agent","songwriting","suno","lyrics","prompts","heartmula","craft","generation","feature","ai music generation","music generation",{"skillNo":113,"name":114,"nameZh":6,"description":115,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":116,"categories":117,"keywords":126,"publishedAt":37},"01M6JFCZE4XNFQFMNZDHKHT5V5","agentic-webdesign-design-system-ingestion","Use v0 Design Systems 2.0, Bolt Design System Agents, or Lovable to generate production UI from a client's real design system components — not generic Tailwind. Use when building a client website where brand consistency matters.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fweb-design\u002Fagentic-webdesign-design-system-ingestion\u002FSKILL.md",[118,121],{"categoryNo":119,"categoryName":120,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":122,"categoryName":123,"taxonomyType":124,"taxonomyTypeDesc":125},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146],"design","agentic","design system","system","ingestion","webdesign","agentic webdesign design system ingestion","components","generate","design systems","website","ui","Tailwind","bolt","lovable","v0","design-system","wed","design system components","appie",{"skillNo":148,"name":149,"nameZh":6,"description":150,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":151,"categories":152,"keywords":155,"publishedAt":37},"01M6JFCVPX3913CFAS6QQJ33ZB","agentic-webdesign-agent-elements","Use 21st.dev Agent Elements — 25 shadcn\u002Fui components purpose-built for AI agent UIs. Tool cards (Bash, Edit, Search, Plan, Subagent, MCP), chat, input, streaming. 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