p-stack
Official@practical-stack
Standardized architectural scaffolding and metadata validation for repository-based feature engineering and technical documentation management.
Agent Skills by p-stack
Showing 12 vetted skills indexed across 2 GitHub repositories.
practical-stackllm-repo-analysis
Analyze LLM agent and plugin repositories to extract architecture, patterns, and insights.
practical-stackmeta-llm-type
Diagnose AI features into Skill, Agent, or Command component types.
practical-stacklearning-content-creator
Transform multi-model research outputs into structured bilingual English and Korean learning content.
practical-stackmeta-structure-organizer
Organize AI feature concepts into Command, Skill, or Agent components.
practical-stackmeta-skill
Generate AI agent skills from standardized templates with validation and packaging workflows.
practical-stackmeta-session-wrapper
Extract reusable patterns from completed session transcripts into formal feature requests.
practical-stacktest-master
Document and apply standardized unit testing guidelines with factories, time mocks, and parameterized tests.
practical-stackmeta-agent
Scaffold specialized AI agents with validated configurations for OpenCode and Claude Code.
practical-stackmeta-command
Create and validate Claude Code slash commands with structured frontmatter and safety checks.
practical-stackcode-quality-reviewer
Analyze Astro Blog Kit code for cohesion, duplication, and SRP issues.
practical-stackmeta-prompt-engineer
Generate structured prompts with ROLE, TASK, CONTEXT, and OUTPUT sections.
practical-stackdoc-frontmatter
Generate and validate YAML frontmatter metadata for Markdown documents in docs folders.
Frequently Asked Questions About p-stack
FAQPage SchemaWhat specific tasks are enabled by these technical capabilities?▼
These capabilities enable the systematic extraction of repository architecture, the generation of structured YAML frontmatter for documentation, the creation of validated slash commands, and the synthesis of bilingual learning content from research outputs.
Which personas benefit most from these technical engineering skills?▼
Technical architects, repository maintainers, and documentation engineers benefit from these skills. They are designed for professionals managing complex project structures, enforcing code quality standards, and requiring consistent metadata management across large-scale technical documentation sets.
What are the primary prerequisites for implementing these repository management skills?▼
Implementation requires an existing repository environment, specifically supporting Astro Blog Kit or Claude Code configurations. Users must have established project directories and a need for standardized unit testing, YAML metadata validation, or structured component scaffolding.