{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm_npm-agile-teamwl-skills-kit","slug":"npm-agile-teamwl-skills-kit","name":"@agile-team/wl-skills-kit","type":"repo","url":"https://www.npmjs.com/package/@agile-team/wl-skills-kit","page_url":"https://unfragile.ai/npm-agile-teamwl-skills-kit","categories":["app-builders"],"tags":["ai","skills","copilot","vue3","template","codegen","cursor","windsurf","kiro","agents"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm_npm-agile-teamwl-skills-kit__cap_0","uri":"capability://code.generation.editing.ai.skill.template.scaffolding.with.coding.standards.enforcement","name":"ai skill template scaffolding with coding standards enforcement","description":"Provides 9 pre-built AI Skill templates that enforce 13 coding standards through a single npm install command. Templates are structured as reusable patterns for Vue 3 projects, with built-in linting rules and code style guidelines that automatically apply to imported skills. The framework uses a convention-over-configuration approach where each skill template includes standardized folder structures, naming conventions, and TypeScript/Vue 3 type definitions.","intents":["I want to quickly scaffold new AI skills in my Vue 3 project without writing boilerplate","I need my team's AI integrations to follow consistent coding standards across all skills","I want to enforce linting and style rules automatically when importing new skills"],"best_for":["Vue 3 development teams building AI-powered features","organizations standardizing AI skill development across multiple projects","teams using Cursor, Windsurf, or Kiro AI editors"],"limitations":["Vue 3 only — no support for React, Angular, or vanilla JavaScript projects","13 coding standards are fixed and not customizable per project","No built-in migration path for existing non-standard AI skills"],"requires":["Vue 3 project (version 3.0+)","Node.js 16+","npm or yarn package manager"],"input_types":["project configuration (package.json)","Vue 3 component files"],"output_types":["scaffolded skill directories","TypeScript type definitions","linting configuration files"],"categories":["code-generation-editing","template-scaffolding"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_1","uri":"capability://tool.use.integration.mcp.tool.integration.registry.with.14.pre.configured.tools","name":"mcp tool integration registry with 14 pre-configured tools","description":"Exposes 14 pre-configured Model Context Protocol (MCP) tools that integrate with AI editors (Cursor, Windsurf, Kiro) through a standardized tool registry. Each tool is pre-wired with schema definitions, input/output validation, and error handling. The framework manages tool discovery, schema serialization, and protocol-level communication without requiring developers to write MCP boilerplate.","intents":["I want to use pre-built MCP tools in my Cursor/Windsurf editor without configuring schemas manually","I need my AI editor to have access to domain-specific tools for my Vue 3 project","I want to add new MCP tools to my AI editor without understanding the MCP protocol"],"best_for":["developers using Cursor, Windsurf, or Kiro AI editors","teams building AI agents that need structured tool access","projects requiring standardized tool interfaces across multiple AI models"],"limitations":["Limited to 14 pre-configured tools — extending with custom tools requires manual MCP schema definition","Tool schemas are immutable after installation — no runtime schema modification","No built-in tool versioning or deprecation management"],"requires":["Cursor, Windsurf, or Kiro AI editor (latest version)","MCP client support in editor","Node.js 16+"],"input_types":["tool invocation parameters (JSON)","context from AI editor"],"output_types":["tool execution results (JSON)","structured responses"],"categories":["tool-use-integration","ai-editor-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_10","uri":"capability://automation.workflow.skill.performance.monitoring.and.metrics.collection","name":"skill performance monitoring and metrics collection","description":"Collects performance metrics for skill execution including latency, error rates, and resource usage. The framework automatically instruments skills to measure execution time, token usage (for AI models), and error frequency. Metrics are exposed via a metrics API and can be exported to monitoring systems like Prometheus or DataDog for dashboarding and alerting.","intents":["I want to monitor the performance of my AI skills in production","I need to track which skills are slow or failing frequently","I want to set up alerts when skill performance degrades"],"best_for":["teams running AI skills in production","projects with SLA requirements for AI features","organizations needing observability into AI skill execution"],"limitations":["Metrics collection adds ~50ms overhead per skill invocation","No built-in support for distributed tracing across skill chains","Metrics export is limited to Prometheus format — no native support for other formats"],"requires":["@agile-team/wl-skills-kit installed","Vue 3 project","Optional: Prometheus or DataDog for metrics export"],"input_types":["skill execution events"],"output_types":["performance metrics (latency, error rate, token usage)","Prometheus-formatted metrics"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_11","uri":"capability://text.generation.language.skill.documentation.generation.from.definitions","name":"skill documentation generation from definitions","description":"Automatically generates documentation for skills from their TypeScript definitions, including parameter descriptions, return types, and usage examples. The framework extracts JSDoc comments, type information, and error handling patterns from skill code and generates Markdown documentation that can be published to a documentation site. 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The framework maintains a context object that persists across skill calls, allowing skills to access previous results, user preferences, and conversation history. Context can be serialized and stored for resuming interrupted workflows, with built-in support for context isolation and cleanup.","intents":["I want skills to have access to previous results in a multi-turn conversation","I need to persist context across skill invocations for resuming workflows","I want to isolate context between different users or workflows"],"best_for":["developers building conversational AI workflows with multiple skills","teams requiring stateful skill execution across multiple turns","projects where workflow state must be persisted and resumed"],"limitations":["Context is in-memory only — no built-in persistence to database or file system","Context size is limited by available memory — no automatic compression or archiving","No built-in support for context versioning or rollback"],"requires":["@agile-team/wl-skills-kit installed","Vue 3 project","Optional: external storage for context persistence"],"input_types":["skill invocation parameters","previous skill results","user context"],"output_types":["skill results with context","serialized context for storage"],"categories":["memory-knowledge","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_2","uri":"capability://planning.reasoning.ai.skill.composition.and.chaining.framework","name":"ai skill composition and chaining framework","description":"Enables developers to compose multiple AI Skills into workflows where outputs from one skill feed into inputs of another. The framework manages skill state, error propagation, and context passing between skills using a pipeline pattern. Skills are registered in a skill registry and can be invoked sequentially or conditionally based on runtime logic, with built-in support for skill dependency resolution.","intents":["I want to chain multiple AI skills together to create complex workflows","I need to pass data between skills while maintaining type safety","I want to conditionally execute skills based on previous skill outputs"],"best_for":["developers building multi-step AI workflows in Vue 3","teams creating AI agents that require skill orchestration","projects where AI skills need to be reused across multiple workflows"],"limitations":["No built-in async/await support for long-running skill chains — requires manual promise handling","Skill composition is declarative only — no visual workflow builder","No built-in skill versioning or rollback mechanisms"],"requires":["Vue 3 project with @agile-team/wl-skills-kit installed","TypeScript 4.5+ for type-safe skill composition","Understanding of skill input/output contracts"],"input_types":["skill definitions (TypeScript/JavaScript)","skill parameters (JSON)"],"output_types":["composed workflow results","error states with stack traces"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_3","uri":"capability://code.generation.editing.typescript.first.skill.definition.with.runtime.validation","name":"typescript-first skill definition with runtime validation","description":"Enforces TypeScript-based skill definitions where input/output types are declared at definition time and validated at runtime. Each skill is a TypeScript class or function with strict type signatures, and the framework performs schema validation on skill invocation using the declared types. This enables IDE autocomplete, compile-time type checking, and runtime safety without requiring separate schema files.","intents":["I want type safety when defining and calling AI skills","I need my IDE to provide autocomplete for skill parameters","I want runtime validation to catch type mismatches before they reach the AI model"],"best_for":["TypeScript-first development teams","projects where type safety is critical for AI integrations","developers using VS Code or other TypeScript-aware editors"],"limitations":["Requires TypeScript compilation — adds build step overhead (~500ms per build)","Type definitions must be manually maintained if skill contracts change","No automatic type inference from AI model responses — requires explicit type casting"],"requires":["TypeScript 4.5+","Vue 3 with TypeScript support","TypeScript compiler in build pipeline"],"input_types":["TypeScript skill definitions","runtime parameters (JSON)"],"output_types":["validated skill results","type-safe responses"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_4","uri":"capability://tool.use.integration.ai.editor.integration.cursor.windsurf.kiro.with.skill.auto.discovery","name":"ai editor integration (cursor, windsurf, kiro) with skill auto-discovery","description":"Automatically exposes installed AI Skills to Cursor, Windsurf, and Kiro editors through a standardized plugin interface. The framework scans the skill registry at editor startup and registers each skill as an available action in the editor's command palette and context menus. Skills are discoverable without manual configuration, and editor context (selected code, file path, project structure) is automatically passed to skills.","intents":["I want my AI editor to automatically discover and use my custom AI skills","I need my skills to have access to editor context like selected code and file information","I want to invoke skills from the editor's command palette without leaving my workflow"],"best_for":["developers using Cursor, Windsurf, or Kiro as primary editor","teams building editor-integrated AI workflows","projects where AI skills should be accessible from the IDE"],"limitations":["Auto-discovery only works with supported editors — no support for VS Code extensions or JetBrains IDEs","Editor context passing is limited to code selection and file metadata — no access to editor state like open tabs or scroll position","Skill invocation from editor is synchronous only — long-running skills block editor UI"],"requires":["Cursor, Windsurf, or Kiro (latest version with plugin support)","@agile-team/wl-skills-kit installed in project","Editor plugin configuration in project root"],"input_types":["editor context (selected code, file path, project metadata)","user input from command palette"],"output_types":["skill results displayed in editor","code insertions or replacements"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_5","uri":"capability://safety.moderation.coding.standards.enforcement.with.linting.rules","name":"coding standards enforcement with linting rules","description":"Bundles 13 pre-defined coding standards as ESLint/Prettier rules that are automatically applied to all AI Skills in the project. Standards cover naming conventions, file structure, error handling patterns, and TypeScript usage. The framework integrates with the project's existing linting pipeline and can be configured to run on pre-commit hooks or CI/CD pipelines, with detailed violation reports.","intents":["I want to enforce consistent code style across all AI skills in my team","I need linting to catch common mistakes in skill definitions automatically","I want to fail CI/CD builds if skills don't meet coding standards"],"best_for":["teams with multiple developers contributing AI skills","projects with strict code quality requirements","organizations standardizing AI skill development across repositories"],"limitations":["13 standards are fixed and cannot be customized or extended without forking the package","Linting rules are ESLint/Prettier only — no support for other linters like Biome or Rome","Standards are opinionated and may conflict with existing project linting configurations"],"requires":["ESLint 8.0+","Prettier 2.8+","Node.js 16+","Vue 3 project"],"input_types":["skill source files (TypeScript/JavaScript)","linting configuration"],"output_types":["linting violation reports","auto-fixed code (if Prettier is configured)"],"categories":["safety-moderation","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_6","uri":"capability://data.processing.analysis.skill.parameter.validation.and.schema.generation","name":"skill parameter validation and schema generation","description":"Automatically generates JSON Schema definitions from TypeScript skill parameter types, enabling runtime validation and AI model prompt generation. When a skill is defined with TypeScript types, the framework introspects those types and generates corresponding JSON Schemas that describe valid inputs. These schemas are used to validate skill invocations at runtime and can be passed to AI models to guide parameter generation.","intents":["I want to validate skill parameters before passing them to the AI model","I need to generate JSON Schemas from my TypeScript skill definitions automatically","I want the AI model to understand what parameters my skills accept"],"best_for":["developers building AI agents that invoke skills","teams using AI models to generate skill parameters","projects requiring strict input validation for AI skills"],"limitations":["Schema generation only works with TypeScript types — no support for runtime-only JavaScript","Complex types (unions, generics) may not generate valid schemas without manual annotation","Generated schemas are static — no support for dynamic schema generation based on runtime state"],"requires":["TypeScript 4.5+","TypeScript compiler in build pipeline","Skill definitions with explicit type annotations"],"input_types":["TypeScript skill parameter types"],"output_types":["JSON Schema definitions","validation results"],"categories":["data-processing-analysis","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_7","uri":"capability://safety.moderation.skill.error.handling.and.recovery.patterns","name":"skill error handling and recovery patterns","description":"Provides built-in error handling patterns for skills including retry logic, fallback skills, and error recovery strategies. Skills can define error handlers that execute when a skill fails, with support for exponential backoff, circuit breaker patterns, and fallback skill invocation. Error context (including the original error, skill parameters, and execution state) is passed to error handlers for intelligent recovery decisions.","intents":["I want my skills to automatically retry on transient failures","I need to define fallback skills that execute if the primary skill fails","I want detailed error context when a skill fails for debugging"],"best_for":["developers building resilient AI workflows","teams requiring high availability for AI skill execution","projects where skill failures should not block entire workflows"],"limitations":["Retry logic is limited to exponential backoff — no support for custom backoff strategies","Circuit breaker pattern requires manual configuration per skill","Error recovery is skill-level only — no cross-skill error propagation or compensation"],"requires":["@agile-team/wl-skills-kit installed","Vue 3 project","Understanding of error handling patterns"],"input_types":["skill definitions with error handlers","error context (error object, parameters, state)"],"output_types":["recovery results","error logs with context"],"categories":["safety-moderation","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_8","uri":"capability://code.generation.editing.skill.testing.utilities.and.mock.framework","name":"skill testing utilities and mock framework","description":"Provides testing utilities for skills including mock AI model responses, skill invocation simulators, and assertion helpers. Developers can write unit tests for skills without calling real AI models, using pre-recorded or synthetic responses. The framework includes helpers for asserting skill behavior, validating parameter validation, and testing error handling paths.","intents":["I want to unit test my skills without calling real AI models","I need to mock AI model responses for deterministic testing","I want to test error handling paths in my skills"],"best_for":["developers writing unit tests for AI skills","teams with CI/CD pipelines that need fast skill tests","projects where AI model costs are a concern for testing"],"limitations":["Mock responses are static — no support for dynamic response generation based on input","Testing utilities are Jest-only — no support for Vitest, Mocha, or other test runners","No built-in support for testing skill composition or multi-skill workflows"],"requires":["Jest 27.0+","@agile-team/wl-skills-kit installed","Vue 3 project"],"input_types":["skill definitions","test cases with mock responses"],"output_types":["test results","coverage reports"],"categories":["code-generation-editing","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm_npm-agile-teamwl-skills-kit__cap_9","uri":"capability://automation.workflow.skill.versioning.and.backward.compatibility.management","name":"skill versioning and backward compatibility management","description":"Manages skill versions and ensures backward compatibility when skill definitions change. Skills can be versioned independently, and the framework tracks which version of a skill is being used in workflows. When a skill is updated, the framework can detect breaking changes and warn developers, or automatically adapt old skill invocations to new signatures using adapter patterns.","intents":["I want to update a skill without breaking existing workflows that use it","I need to track which version of a skill is being used in production","I want to deprecate old skill versions gradually"],"best_for":["teams with long-lived AI workflows that depend on skills","projects where skill updates are frequent and need careful coordination","organizations managing multiple versions of skills across environments"],"limitations":["Versioning is manual — no automatic semantic versioning based on changes","Backward compatibility adapters must be written manually for each breaking change","No built-in support for A/B testing different skill versions"],"requires":["@agile-team/wl-skills-kit installed","Vue 3 project","Manual version annotation in skill definitions"],"input_types":["skill definitions with version metadata","workflow definitions referencing skills"],"output_types":["version compatibility reports","migration warnings"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":27,"verified":false,"data_access_risk":"high","permissions":["Vue 3 project (version 3.0+)","Node.js 16+","npm or yarn package manager","Cursor, Windsurf, or Kiro AI editor (latest version)","MCP client support in editor","@agile-team/wl-skills-kit installed","Vue 3 project","Optional: Prometheus or DataDog for metrics export","TypeScript 4.5+","JSDoc comments in skill definitions"],"failure_modes":["Vue 3 only — no support for React, Angular, or vanilla JavaScript projects","13 coding standards are fixed and not customizable per project","No built-in migration path for existing non-standard AI skills","Limited to 14 pre-configured tools — extending with custom tools requires manual MCP schema definition","Tool schemas are immutable after installation — no runtime schema modification","No built-in tool versioning or deprecation management","Metrics collection adds ~50ms overhead per skill invocation","No built-in support for distributed tracing across skill chains","Metrics export is limited to Prometheus format — no native support for other formats","Documentation generation requires JSDoc comments in skill definitions","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.35,"ecosystem":0.5000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.3,"quality":0.2,"ecosystem":0.15,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.903Z","last_scraped_at":"2026-05-03T14:24:06.907Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=npm-agile-teamwl-skills-kit","compare_url":"https://unfragile.ai/compare?artifact=npm-agile-teamwl-skills-kit"}},"signature":"fqvOFTcAMrZH5aJjP4/cEO+HoN4pa1vMdQf9l5xZPVN7gHbVVH6kardlsr0CC82+0tYTl7+eiHLy7UhuyDH8BQ==","signedAt":"2026-06-20T11:09:46.981Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/npm-agile-teamwl-skills-kit","artifact":"https://unfragile.ai/npm-agile-teamwl-skills-kit","verify":"https://unfragile.ai/api/v1/verify?slug=npm-agile-teamwl-skills-kit","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}