obsidian-vault
๐ฏSkillfrom mattpocock/skills
Searches, creates, and manages notes in Matt Pocock's Obsidian vault at `/mnt/d/Obsidian Vault/AI Research/` โ Title Case filenames, flat layout, `[[wikilinks]]`, and Index notes that aggregate related topics.
Same repository
mattpocock/skills(28 items)
Installation
npx vibeindex add mattpocock/skills --skill obsidian-vaultnpx skills add mattpocock/skills --skill obsidian-vault~/.claude/skills/obsidian-vault/SKILL.mdSKILL.md
More from this repository10
Interviews the user relentlessly about every aspect of a plan or design until reaching shared understanding, resolving each branch of the decision tree one by one. Provides recommended answers for each question and explores the codebase when answers can be found there.
Enforces test-driven development with a strict red-green-refactor loop using vertical slices (one test then one implementation at a time), emphasizing behavior verification through public interfaces rather than implementation-coupled testing.
Skill
A meta-skill that guides the process of creating new agent skills with proper SKILL.md structure, progressive disclosure, and bundled resources. It helps gather requirements, draft skill files, and write effective descriptions.
Guides the creation of a PRD (Product Requirements Document) through a structured interview process covering problem definition, solution options, scope negotiation, deep module extraction, and user story generation, then submits the result as a GitHub issue.
A skill that turns the current conversation context and codebase understanding into a structured PRD (Product Requirements Document) and submits it as a GitHub issue, with modular architecture and user story generation.
Breaks a plan, spec, or PRD into independently-grabbable GitHub issues using tracer-bullet vertical slices. Each issue is a thin end-to-end path through every integration layer that can be demoed or verified on its own.
Instructs the AI agent to step back from detailed code and provide a higher-level perspective, mapping all relevant modules and callers to help developers understand how a section of code fits into the broader architecture.
Ultra-compressed communication mode that reduces token usage by approximately 75% by dropping filler words, articles, and pleasantries while preserving full technical accuracy in responses.
A skill that runs a grilling session to challenge your plan against an existing domain model, sharpen terminology by building a shared language in CONTEXT.md, and document architectural decisions in ADRs before coding begins.