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ai-debugger-inc AI Skills

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Explorez les skills IA publiés de ai-debugger-inc et consultez leurs instructions source.

Statistiques de l’auteur

Skills indexés

8

Étoiles des dépôts des skills indexés

88

Forks du dépôt

8

Moyenne des étoiles par skill indexé

11

Les étoiles d’un dépôt peuvent se répéter entre ses skills.

8 skills

Explorer

GitHub

skill-developer

ai-debugger-inc

Create and manage Claude Code skills following Anthropic best practices. Use when creating new skills, modifying skill-rules.json, understanding trigger patterns, working with hooks, debugging skill activation,...

GitHub

testing-strategy

ai-debugger-inc

Comprehensive guide for implementing AIDB tests following E2E-first philosophy, DebugInterface abstraction, and MCP response health standards

GitHub

dev-cli-development

ai-debugger-inc

Guide for developing AIDB dev-cli commands and services. Covers Click framework patterns, service architecture, command development, decorators, error handling, CommandExecutor, CliOutput, BaseService, BaseMana...

GitHub

aidb-architecture

ai-debugger-inc

Comprehensive architectural reference for AIDB core and MCP integration. Covers 6-layer architecture (MCP, Service, Session, Adapter, DAP Client, Protocol), component organization, data flow patterns, and desig...

GitHub

adapter-development

ai-debugger-inc

Comprehensive guide for AIDB debug adapter development. Covers component-based architecture, language-specific patterns (Python/debugpy, JavaScript/vscode-js-debug, Java/java-debug), lifecycle hooks, process ma...

GitHub

ci-cd-workflows

ai-debugger-inc

Guide for GitHub Actions workflows, test orchestration, parallel testing, adapter builds, releases, and CI/CD configuration. Use when working with .github/workflows/, versions.json, or troubleshooting CI issues...

GitHub

code-reuse-enforcement

ai-debugger-inc

CRITICAL guardrail for preventing code duplication and magic strings in the AIDB codebase. Enforces discovery of existing constants, enums, and utilities BEFORE writing new code.

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.