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marketplace-ai
marketplace-ai contains 66 collected skills from chaseoneillrnd, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Record browser-based feature demos as GIFs via Playwright and optionally document them in docs/features/index.md. Trigger with "Demo <feature>" or "Demo and Document <feature>".
Use when creating service modules in apps/api/skillhub/services/
Use when writing API tests in apps/api/tests/
Use when implementing division-based access control on any endpoint
Use when adding services to docker-compose.yml or creating Dockerfiles
Use when implementing error handling across the API, frontend, or MCP server
Use when creating new Flask blueprints in apps/api/skillhub_flask/blueprints/
Use when generating or managing the OpenAPI spec and TypeScript types
Use when generating or managing TypeScript types in libs/shared-types/
Use when reviewing or implementing accessibility in the React frontend
Use when building admin endpoints requiring platform_team or security_team roles
Use when creating or managing database migrations with Alembic
Use when implementing pagination for API endpoints
Use when making API changes that affect versioning or backward compatibility
Use when adding audit log entries for any mutation or security event
Create, regenerate, and maintain codebase maps as Tier 1 project context files. Use when "create a codebase map", "regenerate the codebase map", "sync the codebase map", "update my project's navigation index", or need a living navigational index to help agents quickly find code. Supports smart detection of tech stack and domain boundaries, socratic probing for discrepancies, user editing with intelligent sync, and post-creation updates to CLAUDE.md and related project docs. Handles monorepos, microservices, traditional single-repo layouts, and language-agnostic projects.
Use when building or extending the comment/reply system
Use when building shared React components in libs/ui/ or apps/web/src/components/
Council of Experts — dispatch parallel subagents as expert roles to debate, discuss, or collaboratively improve something. Use when '/council' is invoked. Supports natural language input to infer mode, agent count, specific skills, and goal.
Use when writing data migrations (backfills, counter updates) with Alembic
Use when optimizing SQLAlchemy queries or addressing N+1 problems
Use when managing environment variables and configuration
Use when adding new feature flags or gating features behind flags
Use when working with the skill fork system
Use when adding CI pipeline stages to .gitlab-ci.yml
Use when implementing install/uninstall tracking
Use when integrating LLM calls via LiteLLM/Bedrock for evaluation or content generation
Use when adding new MCP tools in apps/mcp-server/skillhub_mcp/tools/
Use when adding mise tasks in mise.toml
Use when implementing structured logging, health checks, or observability
Use when configuring NX monorepo projects and dependency rules
Use when implementing OAuth provider flows for production auth
Use when optimizing React rendering, API response times, or bundle size
Use when adding pre-commit hooks to .pre-commit-config.yaml
Use when creating Pydantic v2 schemas in apps/api/skillhub/schemas/
Use when building shared Python utilities in libs/python-common/
Use when adding quality checks to the CI/local quality gate
Use when creating custom React hooks in apps/web/src/hooks/
Use when creating new React views in apps/web/src/views/
Comprehensive repository visualization, analysis, and observatory for Benefitly. Use when "visualize the repo", "show me bottlenecks", "where are test gaps", "what are the scaling concerns", "generate repo report", "update observatory", "show dependency graph", "identify antipatterns", "dead code scan", "repo health dashboard", "infrastructure topology", "concern map", "action plan for improvements", "what needs attention", "repo overview", or any request to analyze, visualize, or report on codebase health, architecture, test coverage, data flows, or areas of concern. Operates in three modes: dashboard (full scan), analyst (targeted query), observatory (persistent docs). Orchestrates via subagent dispatch to codebase-health-check, codebase-map-generator, observability-master, and other existing skills. Produces Mermaid diagrams, scored reports, and action plans with file:line citations.