[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6C217YHBHTNWT533RWRGDR2":3,"skill-same:01M6C217YHBHTNWT533RWRGDR2":89},{"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":26,"publishedAt":52,"linkOnly":53,"markdownContent":54,"markdownBody":55,"frontMatter":56,"refName":65,"commitSha":66,"skillDirectory":67,"forksCount":68,"repositoryHtmlUrl":69,"repositoryHomepageUrl":70,"ownerHtmlUrl":71,"ownerBlogUrl":72,"ownerDescription":73,"updatedAt":74,"install":75,"resources":88},"01M6C217YHBHTNWT533RWRGDR2","research-quality-audit",null,"Audit a research corpus for shallow stubs, missing sources, and doc-depth issues. Detects docs written from abstracts rather than full papers; can dispatch expansion agents.","jmagly\u002Faiwg","jmagly","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F1159087?v=4","01M6C10AK8N2WCSQN11FYGTJWN","Joseph Magly","01M6C10AQ8A2RMED1Y1BSVY7NF",229,"MIT","https:\u002F\u002Fgithub.com\u002Fjmagly\u002Faiwg\u002Fblob\u002Fmain\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-quality-audit\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],"research","quality audit","audit","quality","research quality","research quality audit","depth","docs","for","expansion","sonnet","papers","sources","full","fix","write","read","grep","coding","format","json","Bash","doc","issues","validation","2026-11-10 10:12:30",false,"---\nnamespace: aiwg\nplatforms: [all]\nname: research-quality-audit\ndescription: Audit a research corpus for shallow stubs, missing sources, and doc-depth issues. Detects docs written from abstracts rather than full papers; can dispatch expansion agents.\ncommandHint:\n  argumentHint: \"[--range REF-XXX:YYY] [--fix] [--threshold N] [--format full|summary|json]\"\n  allowedTools: Read, Write, Glob, Grep, Bash, Agent\n  model: sonnet\n  category: research-validation\n  modelRole: coding\n  modelTier: standard\n---\n\n# Research Quality Audit\n\nAudit the research corpus for shallow stubs, incomplete documentation, and missing source files. Detects analysis docs written from abstracts alone (the root cause of the 88-stub incident) and reports doc depth metrics across the corpus.\n\n## Triggers\n\n- \"audit research quality\"\n- \"check for stubs\"\n- \"find shallow docs\"\n- \"research quality audit\"\n- \"how deep are the analysis docs?\"\n- `\u002Fresearch-quality-audit`\n\n## Parameters\n\n### `--range REF-XXX:YYY` (optional)\nAudit a specific range of REF identifiers. Default: entire corpus.\n\n### `--fix` (optional)\nAuto-dispatch expansion agents to deepen stubs. Each stub gets a focused agent that reads the full PDF\u002Fsource and rewrites the analysis doc.\n\n### `--threshold N` (optional)\nMinimum line count for a doc to be considered non-stub. Default: 80.\n\n### `--format` (optional)\nOutput format: `full` (default), `summary`, or `json`.\n\n### `--pdf-check` (optional)\nAlso verify that each REF has an actual PDF or source file, not just metadata.\n\n## Execution Flow\n\n### Phase 1: Corpus Scan\n\n1. **Glob** all finding docs: `.aiwg\u002Fresearch\u002Ffindings\u002FREF-*.md`\n   (and\u002For `documentation\u002Freferences\u002FREF-*.md` depending on corpus layout)\n2. For each doc, collect:\n   - **Line count** (total lines)\n   - **Content lines** (non-empty, non-frontmatter, non-heading lines)\n   - **Section count** (number of `##` headings)\n   - **Key quote count** (blockquotes or inline quotes)\n   - **Source availability** — does the PDF exist at the referenced `pdf_location`?\n   - **Full text available** — does `sources\u002Ftext\u002FREF-XXX.txt` exist?\n   - **Frontmatter completeness** — required fields present?\n\n### Phase 2: Classification\n\nClassify each doc into quality tiers:\n\n| Tier | Content Lines | Sections | Quotes | Verdict |\n|------|-------------|----------|--------|---------|\n| **Full** | >= 150 | >= 8 | >= 3 | Comprehensive analysis |\n| **Adequate** | 80-149 | >= 5 | >= 1 | Meets minimum depth |\n| **Stub** | 40-79 | >= 3 | 0 | Written from abstract — needs expansion |\n| **Skeleton** | \u003C 40 | any | 0 | Placeholder only — needs full rewrite |\n\nAdditional flags:\n- **No PDF**: analysis exists but source PDF is missing\n- **No full text**: PDF exists but text extraction was not run\n- **Abstract-only indicators**: doc mentions \"abstract\" but no methodology\u002Fresults sections\n\n### Phase 3: Report\n\n```\nResearch Quality Audit\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\nCorpus: 372 documents\nThreshold: 80 content lines\n\nQuality Distribution:\n  Full (150+):      124 (33%)  ████████████████░░░░░░░░░░\n  Adequate (80-149): 89 (24%)  ████████████░░░░░░░░░░░░░░\n  Stub (40-79):      98 (26%)  █████████████░░░░░░░░░░░░░\n  Skeleton (\u003C40):    61 (16%)  ████████░░░░░░░░░░░░░░░░░░\n\nStatistics:\n  Mean content lines:  112\n  Median:              94\n  Min:                 12 (REF-299)\n  Max:                 591 (REF-018)\n\nSource Availability:\n  PDF present:         348 \u002F 372 (94%)\n  Full text extracted:  201 \u002F 372 (54%)\n  Missing PDF:          24 papers\n  Missing text:        171 papers\n\nStubs Requiring Expansion (159):\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\n  REF-253  22 lines  skeleton  No PDF    \"Agentic Design Patterns\"\n  REF-254  35 lines  skeleton  Has PDF   \"Multi-Agent Debate\"\n  REF-255  45 lines  stub      Has PDF   \"Language Agent Tree Search\"\n  REF-256  48 lines  stub      No text   \"ReAct: Synergizing Reasoning\"\n  ...\n\nTop 10 Shallowest (candidates for immediate expansion):\n  1. REF-299  12 lines  skeleton  \"Toolformer: Language Models Can...\"\n  2. REF-312  15 lines  skeleton  \"WebArena: A Realistic Web...\"\n  3. REF-253  22 lines  skeleton  \"Agentic Design Patterns...\"\n  ...\n```\n\n### Phase 4: Auto-Fix (if --fix)\n\nWhen `--fix` is specified:\n\n1. **Filter fixable stubs** — only expand docs that have a PDF or full text available\n2. **Batch by priority** — shallowest docs first, batch into groups of 10\n3. **Dispatch expansion agents** — each agent:\n   - Reads the full PDF\u002Fextracted text for the source\n   - Rewrites the analysis doc with comprehensive content\n   - Target: 150+ content lines with methodology, findings, limitations, key quotes\n4. **Re-audit after expansion** — run Phase 1-3 again to verify improvements\n5. **Report** — docs expanded, mean line improvement, remaining stubs\n\n```\nAuto-Fix Results:\n  Dispatched: 10 expansion agents (batch 1 of 16)\n  Expanded: 10 \u002F 10\n  Mean improvement: 77 → 161 lines (+109%)\n  Remaining stubs: 149\n\n  Run again with --fix to process next batch.\n```\n\n## Integration Points\n\n| Component | Relationship |\n|-----------|-------------|\n| `induct-research` | Quality audit should auto-run after batch induction |\n| `corpus-snapshot` | Gates on stub rate > 10% (#814) |\n| `research-lint` | `ref-frontmatter` rule catches incomplete metadata; quality-audit catches shallow content |\n| `research-status` | Doc depth is a component of corpus health scoring |\n| `research-acquire` | For stubs with missing PDFs, triggers acquisition before expansion |\n\n## Distinction from Other Tools\n\n| Tool | What it checks |\n|------|---------------|\n| `research-lint` | **Structural** — frontmatter fields, naming, references resolve |\n| `research-quality-audit` | **Depth** — is the content substantive? Was the source actually read? |\n| `research-quality` | **Evidence** — GRADE assessment of the source's research quality |\n| `corpus-health` | **Aggregate** — overall corpus metrics including depth, structure, coverage |\n\n## Examples\n\n```bash\n# Full corpus audit\n\u002Fresearch-quality-audit\n\n# Audit specific range\n\u002Fresearch-quality-audit --range REF-253:372\n\n# Auto-expand stubs (batch of 10)\n\u002Fresearch-quality-audit --fix\n\n# Strict threshold (120 lines minimum)\n\u002Fresearch-quality-audit --threshold 120\n\n# Check source file availability\n\u002Fresearch-quality-audit --pdf-check\n\n# JSON for programmatic use\n\u002Fresearch-quality-audit --format json\n```\n\n## References\n\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Finduct-research\u002FSKILL.md — Source of stubs when acquisition is skipped\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-acquire\u002FSKILL.md — Acquires PDFs for stub expansion\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-lint\u002FSKILL.md — Structural validation (complementary)\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-quality\u002FSKILL.md — GRADE evidence assessment (complementary)\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-status\u002FSKILL.md — Health scoring includes depth metrics\n","# Research Quality Audit\n\nAudit the research corpus for shallow stubs, incomplete documentation, and missing source files. Detects analysis docs written from abstracts alone (the root cause of the 88-stub incident) and reports doc depth metrics across the corpus.\n\n## Triggers\n\n- \"audit research quality\"\n- \"check for stubs\"\n- \"find shallow docs\"\n- \"research quality audit\"\n- \"how deep are the analysis docs?\"\n- `\u002Fresearch-quality-audit`\n\n## Parameters\n\n### `--range REF-XXX:YYY` (optional)\nAudit a specific range of REF identifiers. Default: entire corpus.\n\n### `--fix` (optional)\nAuto-dispatch expansion agents to deepen stubs. Each stub gets a focused agent that reads the full PDF\u002Fsource and rewrites the analysis doc.\n\n### `--threshold N` (optional)\nMinimum line count for a doc to be considered non-stub. Default: 80.\n\n### `--format` (optional)\nOutput format: `full` (default), `summary`, or `json`.\n\n### `--pdf-check` (optional)\nAlso verify that each REF has an actual PDF or source file, not just metadata.\n\n## Execution Flow\n\n### Phase 1: Corpus Scan\n\n1. **Glob** all finding docs: `.aiwg\u002Fresearch\u002Ffindings\u002FREF-*.md`\n   (and\u002For `documentation\u002Freferences\u002FREF-*.md` depending on corpus layout)\n2. For each doc, collect:\n   - **Line count** (total lines)\n   - **Content lines** (non-empty, non-frontmatter, non-heading lines)\n   - **Section count** (number of `##` headings)\n   - **Key quote count** (blockquotes or inline quotes)\n   - **Source availability** — does the PDF exist at the referenced `pdf_location`?\n   - **Full text available** — does `sources\u002Ftext\u002FREF-XXX.txt` exist?\n   - **Frontmatter completeness** — required fields present?\n\n### Phase 2: Classification\n\nClassify each doc into quality tiers:\n\n| Tier | Content Lines | Sections | Quotes | Verdict |\n|------|-------------|----------|--------|---------|\n| **Full** | >= 150 | >= 8 | >= 3 | Comprehensive analysis |\n| **Adequate** | 80-149 | >= 5 | >= 1 | Meets minimum depth |\n| **Stub** | 40-79 | >= 3 | 0 | Written from abstract — needs expansion |\n| **Skeleton** | \u003C 40 | any | 0 | Placeholder only — needs full rewrite |\n\nAdditional flags:\n- **No PDF**: analysis exists but source PDF is missing\n- **No full text**: PDF exists but text extraction was not run\n- **Abstract-only indicators**: doc mentions \"abstract\" but no methodology\u002Fresults sections\n\n### Phase 3: Report\n\n```\nResearch Quality Audit\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\nCorpus: 372 documents\nThreshold: 80 content lines\n\nQuality Distribution:\n  Full (150+):      124 (33%)  ████████████████░░░░░░░░░░\n  Adequate (80-149): 89 (24%)  ████████████░░░░░░░░░░░░░░\n  Stub (40-79):      98 (26%)  █████████████░░░░░░░░░░░░░\n  Skeleton (\u003C40):    61 (16%)  ████████░░░░░░░░░░░░░░░░░░\n\nStatistics:\n  Mean content lines:  112\n  Median:              94\n  Min:                 12 (REF-299)\n  Max:                 591 (REF-018)\n\nSource Availability:\n  PDF present:         348 \u002F 372 (94%)\n  Full text extracted:  201 \u002F 372 (54%)\n  Missing PDF:          24 papers\n  Missing text:        171 papers\n\nStubs Requiring Expansion (159):\n━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n\n  REF-253  22 lines  skeleton  No PDF    \"Agentic Design Patterns\"\n  REF-254  35 lines  skeleton  Has PDF   \"Multi-Agent Debate\"\n  REF-255  45 lines  stub      Has PDF   \"Language Agent Tree Search\"\n  REF-256  48 lines  stub      No text   \"ReAct: Synergizing Reasoning\"\n  ...\n\nTop 10 Shallowest (candidates for immediate expansion):\n  1. REF-299  12 lines  skeleton  \"Toolformer: Language Models Can...\"\n  2. REF-312  15 lines  skeleton  \"WebArena: A Realistic Web...\"\n  3. REF-253  22 lines  skeleton  \"Agentic Design Patterns...\"\n  ...\n```\n\n### Phase 4: Auto-Fix (if --fix)\n\nWhen `--fix` is specified:\n\n1. **Filter fixable stubs** — only expand docs that have a PDF or full text available\n2. **Batch by priority** — shallowest docs first, batch into groups of 10\n3. **Dispatch expansion agents** — each agent:\n   - Reads the full PDF\u002Fextracted text for the source\n   - Rewrites the analysis doc with comprehensive content\n   - Target: 150+ content lines with methodology, findings, limitations, key quotes\n4. **Re-audit after expansion** — run Phase 1-3 again to verify improvements\n5. **Report** — docs expanded, mean line improvement, remaining stubs\n\n```\nAuto-Fix Results:\n  Dispatched: 10 expansion agents (batch 1 of 16)\n  Expanded: 10 \u002F 10\n  Mean improvement: 77 → 161 lines (+109%)\n  Remaining stubs: 149\n\n  Run again with --fix to process next batch.\n```\n\n## Integration Points\n\n| Component | Relationship |\n|-----------|-------------|\n| `induct-research` | Quality audit should auto-run after batch induction |\n| `corpus-snapshot` | Gates on stub rate > 10% (#814) |\n| `research-lint` | `ref-frontmatter` rule catches incomplete metadata; quality-audit catches shallow content |\n| `research-status` | Doc depth is a component of corpus health scoring |\n| `research-acquire` | For stubs with missing PDFs, triggers acquisition before expansion |\n\n## Distinction from Other Tools\n\n| Tool | What it checks |\n|------|---------------|\n| `research-lint` | **Structural** — frontmatter fields, naming, references resolve |\n| `research-quality-audit` | **Depth** — is the content substantive? Was the source actually read? |\n| `research-quality` | **Evidence** — GRADE assessment of the source's research quality |\n| `corpus-health` | **Aggregate** — overall corpus metrics including depth, structure, coverage |\n\n## Examples\n\n```bash\n# Full corpus audit\n\u002Fresearch-quality-audit\n\n# Audit specific range\n\u002Fresearch-quality-audit --range REF-253:372\n\n# Auto-expand stubs (batch of 10)\n\u002Fresearch-quality-audit --fix\n\n# Strict threshold (120 lines minimum)\n\u002Fresearch-quality-audit --threshold 120\n\n# Check source file availability\n\u002Fresearch-quality-audit --pdf-check\n\n# JSON for programmatic use\n\u002Fresearch-quality-audit --format json\n```\n\n## References\n\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Finduct-research\u002FSKILL.md — Source of stubs when acquisition is skipped\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-acquire\u002FSKILL.md — Acquires PDFs for stub expansion\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-lint\u002FSKILL.md — Structural validation (complementary)\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-quality\u002FSKILL.md — GRADE evidence assessment (complementary)\n- @$AIWG_ROOT\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-status\u002FSKILL.md — Health scoring includes depth metrics\n",{"name":5,"namespace":57,"platforms":58,"commandHint":60,"description":7},"aiwg",[59],"all",{"model":37,"category":61,"modelRole":45,"modelTier":62,"allowedTools":63,"argumentHint":64},"research-validation","standard","Read, Write, Glob, Grep, Bash, Agent","[--range REF-XXX:YYY] [--fix] [--threshold N] [--format full|summary|json]","main","6754967c344ccb087a8de06972f55a41067b291b","agentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-quality-audit",36,"https:\u002F\u002Fgithub.com\u002Fjmagly\u002Faiwg","https:\u002F\u002Faiwg.io","https:\u002F\u002Fgithub.com\u002Fjmagly","https:\u002F\u002Fintegrolabs.io","ml\u002Fai, industrial automation, safety\u002Fsecurity, ssi\r\n\r\nmagly.net\r\nintegrolabs.io\r\naiwg.io\r\nfortemi.com\r\npagenary.com\r\nbytecask.com","2026-11-12 00:33:10",{"source":8,"skillName":5,"commands":76,"prompt":86,"zipAvailable":87},[77,80,83],{"tool":78,"command":79},"npx","npx skills add jmagly\u002Faiwg --skill research-quality-audit",{"tool":81,"command":82},"bunx","bunx skills add jmagly\u002Faiwg --skill research-quality-audit",{"tool":84,"command":85},"pnpm","pnpm dlx skills add jmagly\u002Faiwg --skill research-quality-audit","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fjmagly\u002Faiwg\u002Fblob\u002Fmain\u002Fagentic\u002Fcode\u002Fframeworks\u002Fresearch-complete\u002Fskills\u002Fresearch-quality-audit\u002FSKILL.md",true,[],[90,115,138,144,151,165],{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":94,"categories":95,"keywords":97,"publishedAt":52},"01M70QA0BSYJ49EES9V4RE8QH1","host-hardening","Read-only system hardening baseline and plan-first host hardening recommendations for SSH, Docker bind addresses, firewall persistence, datastores, exporters and audit retention.","https:\u002F\u002Fgithub.com\u002Fjmagly\u002Faiwg\u002Fblob\u002Fmain\u002Fagentic\u002Fcode\u002Fplugins\u002Fsecurity-engineering\u002Fskills\u002Fhost-hardening\u002FSKILL.md",[96],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[98,99,100,43,101,102,103,104,105,106,48,107,108,109,29,110,111,112,113,114],"host","host hardening","hardening","re","recommendations","remediation","plan","port","verification","access","only","retention","never","firewall","bind","secrets","request",{"skillNo":116,"name":117,"nameZh":6,"description":118,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":119,"categories":120,"keywords":125,"publishedAt":52},"01M70PNT2Z4HMZPRBTAF6073NN","exposure-analysis","Read-only firewall analysis and effective host exposure reconstruction for Docker published ports, UFW bypass, stale rules, CDN scope, IPv6 asymmetry and external probe allowlists.","https:\u002F\u002Fgithub.com\u002Fjmagly\u002Faiwg\u002Fblob\u002Fmain\u002Fagentic\u002Fcode\u002Fplugins\u002Fforensics\u002Fskills\u002Fexposure-analysis\u002FSKILL.md",[121,124],{"categoryNo":122,"categoryName":123,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[126,127,128,43,129,105,130,131,48,132,98,133,108,134,135,110,111,136,137,42],"exposure analysis","analysis","unknown","credentials","collection","ufw","ports","internet","local","scope","reconstruction","operator",{"skillNo":139,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":143,"publishedAt":52},"01M70P8QATMPKA78E4FT5D2TNA","https:\u002F\u002Fgithub.com\u002Fjmagly\u002Faiwg\u002Fblob\u002Fmain\u002Fagentic\u002Fcode\u002Fframeworks\u002Fsecurity-engineering\u002Fskills\u002Fhost-hardening\u002FSKILL.md",[142],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[100,98,99,107,43,114,103,102,29,104,105,106,48,113,108,109,101,110,111,112],{"skillNo":145,"name":117,"nameZh":6,"description":118,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":146,"categories":147,"keywords":150,"publishedAt":52},"01M70NMPVJ5H0JH131P60FW4R8","https:\u002F\u002Fgithub.com\u002Fjmagly\u002Faiwg\u002Fblob\u002Fmain\u002Fagentic\u002Fcode\u002Fframeworks\u002Fforensics-complete\u002Fskills\u002Fexposure-analysis\u002FSKILL.md",[148,149],{"categoryNo":122,"categoryName":123,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[127,126,110,129,105,130,48,128,98,133,108,134,135,43,111,132,131,136,137,42],{"skillNo":152,"name":153,"nameZh":6,"description":154,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":155,"categories":156,"keywords":158,"publishedAt":52},"01M6CB4DDR0B4NNCFK7ZK7449H","fixture-skill","Exercise rule delivery.","https:\u002F\u002Fgithub.com\u002Fjmagly\u002Faiwg\u002Fblob\u002Fmain\u002Ftest\u002Ffixtures\u002Frule-delivery\u002Fskills\u002Ffixture-skill\u002FSKILL.md",[157],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[159,160,161,162,163,164],"fixture skill","fixture","rule","delivery","true","exercise",{"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":15,"licenseFileUrl":6,"sourceHtmlUrl":169,"categories":170,"keywords":172,"publishedAt":52},"01M6CB4AVK1W76MFMPP0JP32CJ","pi-local","Pi-local duplicate-precedence fixture.","https:\u002F\u002Fgithub.com\u002Fjmagly\u002Faiwg\u002Fblob\u002Fmain\u002Ftest\u002Ffixtures\u002Fproviders\u002Fpi\u002Fproject\u002F.pi\u002Fskills\u002Fpi-local\u002FSKILL.md",[171],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[173,174,134,175,160],"pi","pi local","duplicate"]