debugging
Standardized debugging and diagnostic guidelines for AI coding agents.
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170 skills found
Standardized debugging and diagnostic guidelines for AI coding agents.
Orchestrates Change Request Document workflows for brownfield projects, managing codebase context, impact analysis, and CRD document generation.
Automated runtime observability changelog for Claude Code development sessions, tracking file changes, test results, and git commits.
An autonomous AI-powered task management system with Kanban boards, git worktree isolation, and pluggable executors like Claude Code, Gemini, and OpenAI Codex.
Standardized guidelines for Dart package maintenance, covering semantic versioning, CHANGELOG management, and publishing workflows.
Generates standardized metadata, including git/jj version info and timestamps, for research docs, handoffs, and implementation plans.
Mandatory execution-based validation for all software implementation tasks. Ensures code works through empirical verification before confirmation.
Rigorous, non-performative code review reception for AI agents, prioritizing technical verification and YAGNI over passive agreement.
Write, structure, and maintain technical documentation like READMEs, API docs, runbooks, and architecture specs to keep your team aligned and informed.
Test-driven development (TDD) workflow for Spring Boot applications using JUnit 5, Mockito, MockMvc, and Testcontainers.
Perform automated security audits, bug detection, and code quality assessments on local branch diffs using a structured, checklist-driven verification process.
Maintains a detailed, step-by-step implementation diary for coding sessions with docmgr integration to track changes, rationale, commands, and failures.