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chore: sync generated registry files [ci skip]

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2026-03-16 14:57:23 +00:00
parent 469c9f45af
commit e76fbb6405
5 changed files with 142 additions and 25 deletions
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4
data/bundles.json
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@@ -31,6 +31,7 @@
"async-python-patterns",
"audit-skills",
"aws-serverless",
"awt-e2e-testing",
"azure-ai-agents-persistent-java",
"azure-ai-anomalydetector-java",
"azure-ai-contentsafety-java",
@@ -320,6 +321,7 @@
"007",
"accessibility-compliance-accessibility-audit",
"agentic-actions-auditor",
"ai-engineering-toolkit",
"ai-md",
"antigravity-workflows",
"api-endpoint-builder",
@@ -349,6 +351,7 @@
"codebase-audit-pre-push",
"codebase-cleanup-deps-audit",
"comfyui-gateway",
"comprehensive-review-pr-enhance",
"constant-time-analysis",
"convex",
"cred-omega",
@@ -631,6 +634,7 @@
"007",
"acceptance-orchestrator",
"agent-evaluation",
"ai-engineering-toolkit",
"airflow-dag-patterns",
"api-testing-observability-api-mock",
"apify-brand-reputation-monitoring",

102
data/catalog.json
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@@ -1,6 +1,6 @@
{
"generatedAt": "2026-02-08T00:00:00.000Z",
"total": 1259,
"total": 1262,
"skills": [
{
"id": "00-andruia-consultant",
@@ -809,6 +809,35 @@
],
"path": "skills/ai-engineer/SKILL.md"
},
{
"id": "ai-engineering-toolkit",
"name": "ai-engineering-toolkit",
"description": "6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.",
"category": "security",
"tags": [
"prompt-engineering",
"rag",
"security",
"evaluation",
"ai-engineering",
"llm"
],
"triggers": [
"prompt-engineering",
"rag",
"security",
"evaluation",
"ai-engineering",
"llm",
"ai",
"engineering",
"toolkit",
"prompt",
"dimension",
"scoring"
],
"path": "skills/ai-engineering-toolkit/SKILL.md"
},
{
"id": "ai-md",
"name": "ai-md",
@@ -859,6 +888,32 @@
],
"path": "skills/ai-ml/SKILL.md"
},
{
"id": "ai-native-cli",
"name": "ai-native-cli",
"description": "Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.",
"category": "data-ai",
"tags": [
"ai",
"native",
"cli"
],
"triggers": [
"ai",
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"spec",
"98",
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"safely",
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"structured",
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],
"path": "skills/ai-native-cli/SKILL.md"
},
{
"id": "ai-product",
"name": "ai-product",
@@ -2828,6 +2883,31 @@
],
"path": "skills/aws-skills/SKILL.md"
},
{
"id": "awt-e2e-testing",
"name": "awt-e2e-testing",
"description": "AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g",
"category": "data-ai",
"tags": [
"awt",
"e2e"
],
"triggers": [
"awt",
"e2e",
"testing",
"ai",
"powered",
"web",
"eyes",
"hands",
"coding",
"declarative",
"yaml",
"scenarios"
],
"path": "skills/awt-e2e-testing/SKILL.md"
},
{
"id": "azd-deployment",
"name": "azd-deployment",
@@ -8732,8 +8812,8 @@
{
"id": "comprehensive-review-pr-enhance",
"name": "comprehensive-review-pr-enhance",
"description": "You are a PR optimization expert specializing in creating high-quality pull requests that facilitate efficient code reviews. Generate comprehensive PR descriptions, automate review processes, and e...",
"category": "general",
"description": "Generate structured PR descriptions from diffs, add review checklists, risk assessments, and test coverage summaries. Use when the user says \"write a PR description\", \"improve this PR\", \"summarize my changes\", \"PR review\", \"pull request\", or asks to document a diff for reviewers.",
"category": "security",
"tags": [
"comprehensive",
"pr",
@@ -8744,14 +8824,14 @@
"pr",
"enhance",
"review",
"optimization",
"specializing",
"creating",
"high",
"quality",
"pull",
"requests",
"facilitate"
"generate",
"structured",
"descriptions",
"diffs",
"add",
"checklists",
"risk",
"assessments"
],
"path": "skills/comprehensive-review-pr-enhance/SKILL.md"
},