[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71NKB63G3NQMJG27CCK0D7D":3,"skill-same:01M71NKB63G3NQMJG27CCK0D7D":86},{"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":41,"linkOnly":42,"markdownContent":43,"markdownBody":44,"frontMatter":45,"refName":46,"commitSha":47,"skillDirectory":48,"forksCount":49,"repositoryHtmlUrl":50,"repositoryHomepageUrl":6,"ownerHtmlUrl":51,"ownerBlogUrl":6,"ownerDescription":52,"updatedAt":53,"install":54,"resources":67},"01M71NKB63G3NQMJG27CCK0D7D","ln-723-seed-data-generator",null,"Generates seed data from ORM schemas or entity definitions to any target format. Use when populating databases for development.","vitalikpestov\u002FSkills-Catalog","vitalikpestov","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F13882997?v=4","01M71N4QG0CWRXX4R24JQZXDDQ","Vitalik Pestov","01M71N4QGMSYRW607DDSE0CQMM",2,"MIT","https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog\u002Fblob\u002Fmain\u002F_AI-Automation\u002Fclaude-code-skills-levnikolaevich\u002Fplugins\u002Fproject-bootstrap\u002Fskills\u002Fln-723-seed-data-generator\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],"ln","generator","seed data","seed","data","ln 723 seed data generator","seed data generator","data generator","entity","format","when","use","for","orm","development","target","databases","2026-11-10 10:56:23",false,"---\nname: ln-723-seed-data-generator\ndescription: \"Generates seed data from ORM schemas or entity definitions to any target format. Use when populating databases for development.\"\nlicense: MIT\n---\n\n> **Paths:** File paths (`references\u002F`, `..\u002Fln-*`) are relative to this skill directory.\n\n# ln-723-seed-data-generator\n\n**Type:** L3 Worker\n**Category:** 7XX Project Bootstrap\n\nUniversal seed data generator with two modes: MIGRATE (parse existing ORM schemas) or GENERATE (create from entity definitions). Outputs to any target format (C#, TypeScript, Python, JSON, SQL).\n\n---\n\n## Purpose & Scope\n\n| Aspect | Description |\n|--------|-------------|\n| **Input** | ORM schema files (MIGRATE) or entity list (GENERATE) |\n| **Output** | Seed data files in target format |\n| **Modes** | MIGRATE: parse existing ORM → seed data. GENERATE: entity definitions → seed data |\n\n**Scope boundaries:**\n- Parses ORM schema definitions or accepts entity lists\n- Generates seed data in requested target format\n- Creates realistic sample data using faker libraries\n- Does not generate database migrations, EF Core configs, or ORM models\n\n---\n\n## Mode Selection\n\n| Mode | When | Input | Source |\n|------|------|-------|--------|\n| **MIGRATE** | TRANSFORM pipeline — existing ORM schemas found | ORM schema files | Drizzle, Prisma, TypeORM, EF Core, SQLAlchemy, Django ORM |\n| **GENERATE** | CREATE pipeline — no existing schemas | Entity list from ln-700 Phase 0 | User-provided or starter template (User, Role) |\n\nIf GENERATE mode receives no entity list, generate starter template with `User` (id, name, email, role, createdAt) and `Role` (id, name, description).\n\n---\n\n## Target Formats\n\n| Format | Output File | Faker Library | Use Case |\n|--------|-------------|---------------|----------|\n| C# MockData | `MockData.cs` | Bogus | .NET projects |\n| TypeScript fixtures | `seed.ts` | Faker.js | Node\u002FReact projects |\n| Python factories | `factories.py` | Faker (Python) | Django\u002FFlask projects |\n| JSON | `seed.json` | — | API testing, import scripts |\n| SQL | `seed.sql` | — | Direct DB seeding |\n\n---\n\n## Workflow\n\n| Phase | Name | Actions | Output |\n|-------|------|---------|--------|\n| 1 | Parse\u002FDefine | 1A: Parse ORM schema (MIGRATE) or 1B: Accept entity list (GENERATE) | Entity model |\n| 2 | Map Types | Apply universal type mapping to target format | Target type definitions |\n| 3 | Generate Seed Data | Create seed files with faker-based realistic data | Seed data files |\n| 4 | Verify | Validate relationships, check syntax | Valid seed files |\n\n---\n\n## Phase 1: Parse\u002FDefine\n\n### 1A: MIGRATE Mode — Parse ORM Schema\n\n| Step | Action | Reference |\n|------|--------|-----------|\n| 1A.1 | Locate schema file(s) | — |\n| 1A.2 | Auto-detect ORM type | `orm_patterns.md` — ORM Auto-Detection table |\n| 1A.3 | Extract table\u002Fmodel definitions | `orm_patterns.md` — per-ORM parsing section |\n| 1A.4 | Extract column definitions with types | `orm_patterns.md` |\n| 1A.5 | Identify constraints (PK, FK, nullable, unique) | `orm_patterns.md` |\n| 1A.6 | Extract enum definitions | `orm_patterns.md` |\n\n### 1B: GENERATE Mode — Accept Entity Definitions\n\n| Step | Action | Reference |\n|------|--------|-----------|\n| 1B.1 | Receive entity list from orchestrator (or use starter template) | — |\n| 1B.2 | Parse entity definitions (name, fields, types) | — |\n| 1B.3 | Infer relationships from field names (`userId` → FK to User) | `relationship_mapping.md` |\n| 1B.4 | Apply default constraints (id = PK, `*Id` = FK) | — |\n\n**Output:** Entity model with columns, types, and constraints.\n\n---\n\n## Phase 2: Map Types\n\nConvert entity types to target format types.\n\n| Step | Action | Reference |\n|------|--------|-----------|\n| 2.1 | Select target format (from orchestrator params) | — |\n| 2.2 | Map column types to target format | `type_mapping.md` — Universal Type Mapping table |\n| 2.3 | Determine nullable status per target | `type_mapping.md` |\n| 2.4 | Map foreign keys and relationships | `relationship_mapping.md` |\n| 2.5 | Transform names to target convention | See Name Conventions table below |\n\n**Name Conventions by Target:**\n\n| Target | Class\u002FModel | Property\u002FField | File |\n|--------|-------------|----------------|------|\n| C# | PascalCase singular | PascalCase | PascalCase.cs |\n| TypeScript | PascalCase singular | camelCase | camelCase.ts |\n| Python | PascalCase singular | snake_case | snake_case.py |\n| JSON | camelCase | camelCase | kebab-case.json |\n| SQL | snake_case plural | snake_case | snake_case.sql |\n\n---\n\n## Phase 3: Generate Seed Data\n\nCreate seed files with realistic data using faker libraries.\n\n| Step | Action | Reference |\n|------|--------|-----------|\n| 3.1 | Determine generation order (parents → children) | `relationship_mapping.md` |\n| 3.2 | Generate IDs (GUIDs\u002FUUIDs) for all entities | `data_generation.md` |\n| 3.3 | Generate field values using faker | `data_generation.md`, `type_mapping.md` — Faker Integration |\n| 3.4 | Ensure FK relationships valid (child references existing parent ID) | `relationship_mapping.md` |\n| 3.5 | Write seed file in target format | — |\n\n**Faker integration rule:** All generated seed files MUST use faker libraries for realistic data with **deterministic seeding** (fixed seed value for reproducibility).\n\n| Target | Faker Setup |\n|--------|-------------|\n| C# | `var faker = new Bogus.Faker(); Randomizer.Seed = new Random(42);` |\n| TypeScript | `import { faker } from '@faker-js\u002Ffaker'; faker.seed(42);` |\n| Python | `from faker import Faker; fake = Faker(); Faker.seed(42)` |\n\n**Generation order by dependency:**\n\n| Order | Entity Type | Generate After |\n|-------|-------------|----------------|\n| 1 | Root entities (no FK) | First |\n| 2 | First-level children | Parents exist |\n| 3 | Second-level children | Grandparents exist |\n| N | Deepest children | All ancestors exist |\n\n---\n\n## Phase 4: Verify\n\n| Check | Method | Expected |\n|-------|--------|----------|\n| Syntax valid | Language-specific check | No syntax errors |\n| FKs valid | Cross-reference | All FKs point to existing IDs |\n| Types correct | Type analysis | Proper types for target format |\n| Names follow convention | Pattern check | Per-target naming convention |\n| Faker deterministic | Re-run with same seed | Identical output |\n\n---\n\n## Supported ORM Detection\n\n| ORM | Detection Pattern | Ecosystem |\n|-----|-------------------|-----------|\n| Drizzle | `pgTable()`, `mysqlTable()`, `sqliteTable()` | Node.js |\n| Prisma | `model X {` syntax in `.prisma` files | Node.js |\n| TypeORM | `@Entity()`, `@Column()` decorators | Node.js |\n| EF Core | `DbContext`, `DbSet\u003C>`, `[Table]` attributes | .NET |\n| SQLAlchemy | `Base = declarative_base()`, `Column()` | Python |\n| Django ORM | `models.Model`, `models.CharField()` | Python |\n\n---\n\n## Entity Transformation Rules\n\n| Source | Target | Transformation |\n|--------|--------|----------------|\n| Table name (plural, snake) | Class name (singular, Pascal) | `user_profiles` → `UserProfile` |\n| Column name (snake) | Property name (target convention) | `created_at` → `CreatedAt` \u002F `createdAt` \u002F `created_at` |\n| Enum name | Enum type (Pascal) | `status_enum` → `StatusEnum` |\n| FK column | Navigation property | `user_id` → `UserId` \u002F `userId` |\n\n---\n\n## Sample Data Guidelines\n\n| Field Type | Sample Count | Distribution |\n|------------|--------------|--------------|\n| Root entities | 3-5 items | Varied status\u002Fpriority |\n| Child entities | 5-10 items | Distributed across parents |\n| Leaf entities | 10-20 items | Realistic variety |\n\n---\n\n## Critical Rules\n\n- **Single Responsibility:** Generate only seed data, no ORM models or migrations\n- **Idempotent:** Can re-run with same seed to produce identical output\n- **Valid Relationships:** All FKs must reference existing parent IDs\n- **Faker Required:** Use faker libraries for realistic data, never random strings\n- **Deterministic Seeding:** Fixed seed value (42) for reproducibility across re-runs\n- **Generation Order:** Parents before children, always\n- **Mode Awareness:** MIGRATE parses files; GENERATE accepts definitions — never mix\n\n---\n\n## Definition of Done\n\n- [ ] Mode determined (MIGRATE or GENERATE)\n- [ ] Entity model extracted\u002Fdefined with all fields and constraints\n- [ ] Target format selected and type mappings applied\n- [ ] Seed data files generated with faker-based realistic values\n- [ ] Deterministic seeding verified (re-run produces identical output)\n- [ ] Foreign keys reference valid parent IDs\n- [ ] Names follow target format conventions\n- [ ] Sample data includes 5-10 items per entity\n\n---\n\n## Risk Mitigation\n\n| Risk | Detection | Mitigation |\n|------|-----------|------------|\n| Unknown ORM type | Auto-detection fails | Log warning, ask orchestrator for ORM hint |\n| Invalid type mapping | Unknown column type | Use string as fallback, log warning |\n| FK mismatch | FK references non-existent ID | Generate parents first, validate after |\n| No entity list in GENERATE | Empty input | Use starter template (User, Role) |\n| Name collision | Duplicate class\u002Ftable names | Prefix with feature name |\n| Circular references | Self-referencing with cycles | Limit depth, validate graph |\n\n---\n\n## Reference Files\n\n| File | Purpose |\n|------|---------|\n| `references\u002Form_patterns.md` | ORM auto-detection and schema parsing patterns (Drizzle, Prisma, TypeORM, EF Core, SQLAlchemy, Django) |\n| `references\u002Ftype_mapping.md` | Universal type mapping (ORM-agnostic → C#, TypeScript, Python) + Faker integration |\n| `references\u002Fdata_generation.md` | Realistic sample data patterns and generation rules |\n| `references\u002Frelationship_mapping.md` | FK handling, generation order, relationship inference |\n\n---\n\n**Version:** 3.0.0\n**Last Updated:** 2026-02-07\n","> **Paths:** File paths (`references\u002F`, `..\u002Fln-*`) are relative to this skill directory.\n\n# ln-723-seed-data-generator\n\n**Type:** L3 Worker\n**Category:** 7XX Project Bootstrap\n\nUniversal seed data generator with two modes: MIGRATE (parse existing ORM schemas) or GENERATE (create from entity definitions). Outputs to any target format (C#, TypeScript, Python, JSON, SQL).\n\n---\n\n## Purpose & Scope\n\n| Aspect | Description |\n|--------|-------------|\n| **Input** | ORM schema files (MIGRATE) or entity list (GENERATE) |\n| **Output** | Seed data files in target format |\n| **Modes** | MIGRATE: parse existing ORM → seed data. GENERATE: entity definitions → seed data |\n\n**Scope boundaries:**\n- Parses ORM schema definitions or accepts entity lists\n- Generates seed data in requested target format\n- Creates realistic sample data using faker libraries\n- Does not generate database migrations, EF Core configs, or ORM models\n\n---\n\n## Mode Selection\n\n| Mode | When | Input | Source |\n|------|------|-------|--------|\n| **MIGRATE** | TRANSFORM pipeline — existing ORM schemas found | ORM schema files | Drizzle, Prisma, TypeORM, EF Core, SQLAlchemy, Django ORM |\n| **GENERATE** | CREATE pipeline — no existing schemas | Entity list from ln-700 Phase 0 | User-provided or starter template (User, Role) |\n\nIf GENERATE mode receives no entity list, generate starter template with `User` (id, name, email, role, createdAt) and `Role` (id, name, description).\n\n---\n\n## Target Formats\n\n| Format | Output File | Faker Library | Use Case |\n|--------|-------------|---------------|----------|\n| C# MockData | `MockData.cs` | Bogus | .NET projects |\n| TypeScript fixtures | `seed.ts` | Faker.js | Node\u002FReact projects |\n| Python factories | `factories.py` | Faker (Python) | Django\u002FFlask projects |\n| JSON | `seed.json` | — | API testing, import scripts |\n| SQL | `seed.sql` | — | Direct DB seeding |\n\n---\n\n## Workflow\n\n| Phase | Name | Actions | Output |\n|-------|------|---------|--------|\n| 1 | Parse\u002FDefine | 1A: Parse ORM schema (MIGRATE) or 1B: Accept entity list (GENERATE) | Entity model |\n| 2 | Map Types | Apply universal type mapping to target format | Target type definitions |\n| 3 | Generate Seed Data | Create seed files with faker-based realistic data | Seed data files |\n| 4 | Verify | Validate relationships, check syntax | Valid seed files |\n\n---\n\n## Phase 1: Parse\u002FDefine\n\n### 1A: MIGRATE Mode — Parse ORM Schema\n\n| Step | Action | Reference |\n|------|--------|-----------|\n| 1A.1 | Locate schema file(s) | — |\n| 1A.2 | Auto-detect ORM type | `orm_patterns.md` — ORM Auto-Detection table |\n| 1A.3 | Extract table\u002Fmodel definitions | `orm_patterns.md` — per-ORM parsing section |\n| 1A.4 | Extract column definitions with types | `orm_patterns.md` |\n| 1A.5 | Identify constraints (PK, FK, nullable, unique) | `orm_patterns.md` |\n| 1A.6 | Extract enum definitions | `orm_patterns.md` |\n\n### 1B: GENERATE Mode — Accept Entity Definitions\n\n| Step | Action | Reference |\n|------|--------|-----------|\n| 1B.1 | Receive entity list from orchestrator (or use starter template) | — |\n| 1B.2 | Parse entity definitions (name, fields, types) | — |\n| 1B.3 | Infer relationships from field names (`userId` → FK to User) | `relationship_mapping.md` |\n| 1B.4 | Apply default constraints (id = PK, `*Id` = FK) | — |\n\n**Output:** Entity model with columns, types, and constraints.\n\n---\n\n## Phase 2: Map Types\n\nConvert entity types to target format types.\n\n| Step | Action | Reference |\n|------|--------|-----------|\n| 2.1 | Select target format (from orchestrator params) | — |\n| 2.2 | Map column types to target format | `type_mapping.md` — Universal Type Mapping table |\n| 2.3 | Determine nullable status per target | `type_mapping.md` |\n| 2.4 | Map foreign keys and relationships | `relationship_mapping.md` |\n| 2.5 | Transform names to target convention | See Name Conventions table below |\n\n**Name Conventions by Target:**\n\n| Target | Class\u002FModel | Property\u002FField | File |\n|--------|-------------|----------------|------|\n| C# | PascalCase singular | PascalCase | PascalCase.cs |\n| TypeScript | PascalCase singular | camelCase | camelCase.ts |\n| Python | PascalCase singular | snake_case | snake_case.py |\n| JSON | camelCase | camelCase | kebab-case.json |\n| SQL | snake_case plural | snake_case | snake_case.sql |\n\n---\n\n## Phase 3: Generate Seed Data\n\nCreate seed files with realistic data using faker libraries.\n\n| Step | Action | Reference |\n|------|--------|-----------|\n| 3.1 | Determine generation order (parents → children) | `relationship_mapping.md` |\n| 3.2 | Generate IDs (GUIDs\u002FUUIDs) for all entities | `data_generation.md` |\n| 3.3 | Generate field values using faker | `data_generation.md`, `type_mapping.md` — Faker Integration |\n| 3.4 | Ensure FK relationships valid (child references existing parent ID) | `relationship_mapping.md` |\n| 3.5 | Write seed file in target format | — |\n\n**Faker integration rule:** All generated seed files MUST use faker libraries for realistic data with **deterministic seeding** (fixed seed value for reproducibility).\n\n| Target | Faker Setup |\n|--------|-------------|\n| C# | `var faker = new Bogus.Faker(); Randomizer.Seed = new Random(42);` |\n| TypeScript | `import { faker } from '@faker-js\u002Ffaker'; faker.seed(42);` |\n| Python | `from faker import Faker; fake = Faker(); Faker.seed(42)` |\n\n**Generation order by dependency:**\n\n| Order | Entity Type | Generate After |\n|-------|-------------|----------------|\n| 1 | Root entities (no FK) | First |\n| 2 | First-level children | Parents exist |\n| 3 | Second-level children | Grandparents exist |\n| N | Deepest children | All ancestors exist |\n\n---\n\n## Phase 4: Verify\n\n| Check | Method | Expected |\n|-------|--------|----------|\n| Syntax valid | Language-specific check | No syntax errors |\n| FKs valid | Cross-reference | All FKs point to existing IDs |\n| Types correct | Type analysis | Proper types for target format |\n| Names follow convention | Pattern check | Per-target naming convention |\n| Faker deterministic | Re-run with same seed | Identical output |\n\n---\n\n## Supported ORM Detection\n\n| ORM | Detection Pattern | Ecosystem |\n|-----|-------------------|-----------|\n| Drizzle | `pgTable()`, `mysqlTable()`, `sqliteTable()` | Node.js |\n| Prisma | `model X {` syntax in `.prisma` files | Node.js |\n| TypeORM | `@Entity()`, `@Column()` decorators | Node.js |\n| EF Core | `DbContext`, `DbSet\u003C>`, `[Table]` attributes | .NET |\n| SQLAlchemy | `Base = declarative_base()`, `Column()` | Python |\n| Django ORM | `models.Model`, `models.CharField()` | Python |\n\n---\n\n## Entity Transformation Rules\n\n| Source | Target | Transformation |\n|--------|--------|----------------|\n| Table name (plural, snake) | Class name (singular, Pascal) | `user_profiles` → `UserProfile` |\n| Column name (snake) | Property name (target convention) | `created_at` → `CreatedAt` \u002F `createdAt` \u002F `created_at` |\n| Enum name | Enum type (Pascal) | `status_enum` → `StatusEnum` |\n| FK column | Navigation property | `user_id` → `UserId` \u002F `userId` |\n\n---\n\n## Sample Data Guidelines\n\n| Field Type | Sample Count | Distribution |\n|------------|--------------|--------------|\n| Root entities | 3-5 items | Varied status\u002Fpriority |\n| Child entities | 5-10 items | Distributed across parents |\n| Leaf entities | 10-20 items | Realistic variety |\n\n---\n\n## Critical Rules\n\n- **Single Responsibility:** Generate only seed data, no ORM models or migrations\n- **Idempotent:** Can re-run with same seed to produce identical output\n- **Valid Relationships:** All FKs must reference existing parent IDs\n- **Faker Required:** Use faker libraries for realistic data, never random strings\n- **Deterministic Seeding:** Fixed seed value (42) for reproducibility across re-runs\n- **Generation Order:** Parents before children, always\n- **Mode Awareness:** MIGRATE parses files; GENERATE accepts definitions — never mix\n\n---\n\n## Definition of Done\n\n- [ ] Mode determined (MIGRATE or GENERATE)\n- [ ] Entity model extracted\u002Fdefined with all fields and constraints\n- [ ] Target format selected and type mappings applied\n- [ ] Seed data files generated with faker-based realistic values\n- [ ] Deterministic seeding verified (re-run produces identical output)\n- [ ] Foreign keys reference valid parent IDs\n- [ ] Names follow target format conventions\n- [ ] Sample data includes 5-10 items per entity\n\n---\n\n## Risk Mitigation\n\n| Risk | Detection | Mitigation |\n|------|-----------|------------|\n| Unknown ORM type | Auto-detection fails | Log warning, ask orchestrator for ORM hint |\n| Invalid type mapping | Unknown column type | Use string as fallback, log warning |\n| FK mismatch | FK references non-existent ID | Generate parents first, validate after |\n| No entity list in GENERATE | Empty input | Use starter template (User, Role) |\n| Name collision | Duplicate class\u002Ftable names | Prefix with feature name |\n| Circular references | Self-referencing with cycles | Limit depth, validate graph |\n\n---\n\n## Reference Files\n\n| File | Purpose |\n|------|---------|\n| `references\u002Form_patterns.md` | ORM auto-detection and schema parsing patterns (Drizzle, Prisma, TypeORM, EF Core, SQLAlchemy, Django) |\n| `references\u002Ftype_mapping.md` | Universal type mapping (ORM-agnostic → C#, TypeScript, Python) + Faker integration |\n| `references\u002Fdata_generation.md` | Realistic sample data patterns and generation rules |\n| `references\u002Frelationship_mapping.md` | FK handling, generation order, relationship inference |\n\n---\n\n**Version:** 3.0.0\n**Last Updated:** 2026-02-07\n",{"name":5,"license":15,"description":7},"main","fbfb242f793fdf040f3a1a6b100896c188c228c8","_AI-Automation\u002Fclaude-code-skills-levnikolaevich\u002Fplugins\u002Fproject-bootstrap\u002Fskills\u002Fln-723-seed-data-generator",1,"https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog","https:\u002F\u002Fgithub.com\u002Fvitalikpestov","Listing on crypto exchanges","2026-06-15 22:12:56",{"source":8,"skillName":5,"commands":55,"prompt":65,"zipAvailable":66},[56,59,62],{"tool":57,"command":58},"npx","npx skills add vitalikpestov\u002FSkills-Catalog --skill ln-723-seed-data-generator",{"tool":60,"command":61},"bunx","bunx skills add vitalikpestov\u002FSkills-Catalog --skill 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when user asks to \"build a Solana dapp\", \"write an Anchor program\", \"create a token\", \"debug Solana errors\", \"set up wallet connection\", \"test my Solana program\", \"deploy to devnet\", or \"explain Solana concepts\" (rent, accounts, PDAs, CPIs, etc.). End-to-end Solana development playbook covering wallet connection, Anchor\u002FPinocchio programs, Codama client generation, LiteSVM\u002FMollusk\u002FSurfpool testing, and security checklists. Integrates with the Solana MCP server for live documentation search. Prefers framework-kit (@solana\u002Fclient + @solana\u002Freact-hooks) for UI, wallet-standard-first connection (incl. ConnectorKit), @solana\u002Fkit for client\u002FRPC code, and @solana\u002Fweb3-compat for legacy boundaries.","https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog\u002Fblob\u002Fmain\u002F_Web3\u002Fsolana-dev\u002Fskill\u002FSKILL.md",[93,98,101,104],{"categoryNo":94,"categoryName":95,"taxonomyType":96,"taxonomyTypeDesc":97},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",{"categoryNo":99,"categoryName":100,"taxonomyType":96,"taxonomyTypeDesc":97},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":102,"categoryName":103,"taxonomyType":96,"taxonomyTypeDesc":97},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":105,"categoryName":106,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师",[108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127],"dev","solana dev","solana","Wallet","search","testing","solana cli","kit","MCP","web3","react","create","server","write","playbook","live","security","ui","concepts","toolchain","2026-11-10 13:02:02",{"skillNo":130,"name":131,"nameZh":6,"description":132,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":133,"categories":134,"keywords":135,"publishedAt":128},"01M71TYQPHE2YGKTT7DG9QCW3K","generating-trading-signals","Generate trading signals using technical indicators (RSI, MACD, Bollinger Bands, etc.).\nCombines multiple indicators into composite signals with confidence scores.\nUse when analyzing assets for trading opportunities or checking technical indicators.\nTrigger with phrases like \"get trading signals\", \"check indicators\", \"analyze for entry\",\n\"scan for opportunities\", \"generate buy\u002Fsell signals\", or \"technical analysis\".","https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog\u002Fblob\u002Fmain\u002F_Trading-Finance\u002Fgenerating-trading-signals\u002FSKILL.md",[],[136,137,138,139,140,141,36,142,143,144,145,146,35,34,147,148,149,150,151,152],"generating trading signals","signals","trading signals","trading","get","technical indicators","scan","rsi","trigger","python","technical","Bash","analysis","code","io","check","analyze",{"skillNo":154,"name":155,"nameZh":6,"description":156,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":157,"categories":158,"keywords":159,"publishedAt":128},"01M71TY4CR3GKGQ3M12X9WN95Y","prediction-monitor","Prediction Monitor - Auto-activating skill for ML Deployment.\nTriggers on: prediction monitor, prediction monitor\nPart of the ML Deployment skill category.","https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog\u002Fblob\u002Fmain\u002F_Trading-Finance\u002FAI Predictions\u002Fprediction-monitor\u002FSKILL.md",[],[160,161,162,36,163,164,121,165,166,167,168,169,147],"prediction","monitor","prediction monitor","deployment","read","edit","triggers","grep","auto","ml",{"skillNo":171,"name":172,"nameZh":6,"description":173,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":174,"categories":175,"keywords":176,"publishedAt":128},"01M71TXD9MYXZC39HCPP909HTZ","strategy-advisor","High-level strategic thinking and business decision guidance for planning and direction-setting.\nUse when: making strategic decisions, evaluating business options, setting direction, analyzing\ntrade-offs, or when user mentions strategy, business planning, competitive analysis, or long-term planning.","https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog\u002Fblob\u002Fmain\u002F_Product-Apps\u002Fstrategy-advisor\u002FSKILL.md",[],[177,178,179,180,181,182,183,184,185,36,186,187,188,35,189,190,34,191,148,192],"strategy advisor","strategy","advisor","competitive","setting","thinking","planning","direction","trade-offs","long","decision","strategic","business","apps","decisions","trade",{"skillNo":194,"name":195,"nameZh":6,"description":196,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":197,"sourceHtmlUrl":198,"categories":199,"keywords":206,"publishedAt":128},"01M71TWHBT2R1P1FNWTW67ZREP","app-paywall-pilot","Design, audit, debug, and implement App Store-compliant mobile paywalls, subscription flows, pricing screens, trials, offers, feature gates, and subscription lifecycle UX. Use when the user asks to audit my paywall, fix App Store 3.1.2 rejection, improve trial-to-paid, choose plans\u002Fprices\u002Ftrials, review RevenueCat\u002FAdapty\u002FApphud\u002FSuperwall setup, calculate LTV\u002FROAS, or build paywall implementation.","https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog\u002Fblob\u002Fmain\u002F_Product-Apps\u002Ffrom-dosesync\u002Fapp-paywall-pilot\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog\u002Fblob\u002Fmain\u002F_Product-Apps\u002Ffrom-dosesync\u002Fapp-paywall-pilot\u002FSKILL.md",[200,203],{"categoryNo":201,"categoryName":202,"taxonomyType":96,"taxonomyTypeDesc":97},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":204,"categoryName":205,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000032","设计师",[207,208,209,210,211,212,213,214,215,216,217,218,34,219,220,221,222,223,224,225],"app","paywall","app paywall pilot","paid","paywalls","prices","choose","flows","fix","improve","design","app store","review","audit","ux","subscription","mobile","my","calculate",{"skillNo":227,"name":228,"nameZh":6,"description":229,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":230,"licenseFileUrl":231,"sourceHtmlUrl":232,"categories":233,"keywords":236,"publishedAt":128},"01M71TWET8GFKEB7ZHJPMQX29V","figma","Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog\u002Fblob\u002Fmain\u002F_Product-Apps\u002Ffigma\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fvitalikpestov\u002FSkills-Catalog\u002Fblob\u002Fmain\u002F_Product-Apps\u002Ffigma\u002FSKILL.md",[234,235],{"categoryNo":102,"categoryName":103,"taxonomyType":96,"taxonomyTypeDesc":97},{"categoryNo":204,"categoryName":205,"taxonomyType":21,"taxonomyTypeDesc":22},[228,237,238,239,240,144,217,116,35,34,241,242,149,243,120,244,245,246,247,248],"fetch","ids","mcp setup","translate","mcp server","Variables","task","Nodes","figma mcp","code implementation","node","assets"]