claude

knowledge-base-setup

Markdown knowledge base init and retrofit. Creates .kb/ meta directory plus preset top-level directories (team-docs, research, product, custom, career). Every .md file carries required frontmatter (title, created, updated, summary, tags, status, relations). Phase 0.5 verifies tool dependencies (yq or python+PyYAML, gh for career, optional ripgrep/gitleaks/lychee) with OS-aware install on opt-in. Installs a pre-commit secret-scan hook, and for the career preset (roles, resumes, projects, skills, brag, learning, reviews, goals) also a pre-push hook that blocks pushing to a public repository. Bundles a companion kb-validator skill that syncs timestamps from git log, prunes broken relations, rebuilds .tag-index, enforces README per directory, and flags length recommendations. Use whenever the user wants to initialize a repo as a shared knowledge base, set up a personal career portfolio, retrofit existing docs, prepare docs as a submodule, or make markdown AI-navigable - even if they say 'docs init', 'career portfolio', 'set up wiki', or 'validate kb'.

0 on GitHubby bbaktaehov1.0.0updated 6 months agoproductivity
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Plugin knowledge-base-setup from marketplace bbaktaeho-agent-skills in bbaktaeho/bbaktaeho-agent-skills. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (2)

  • kb-validator

    Validate and auto-fix a markdown knowledge base set up by the knowledge-base-setup skill. Checks every .md against the frontmatter schema (title, created, updated, summary, tags, status, relations), syncs timestamps from git log, prunes relations pointing at deleted files, rebuilds .kb/.tag-index, v

  • knowledge-base-setup

    Markdown knowledge base init and retrofit. Creates .kb/ meta dir (AI entry point, schema, conventions, tag-index) plus preset top- level dirs (team-docs, research, product, custom, career). Every .md file carries required frontmatter (title, created, updated, summary, tags, status, relations). Phase

View source on GitHub

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AI coding agent instruction file init and retrofit. Builds a single routing chain so every AI tool reads the same source: tool symlink -> AGENTS.md -> .agents/README.md (overview plus top-level directory routing table) -> each top-level <dir>/README.md -> detail files. Sets up AGENTS.md, idempotent symlinks across major AI tools (Claude Code, Cursor, Copilot, Windsurf, Cline, Roo Code, Gemini CLI, Codex, Zed, Antigravity, Amp, Aider, Continue), and a .agents/ meta directory (README, schema, conventions, preset.json, hooks/pre-commit-secrets.sh, local). No agents/ content directory and no team or hub mode branching - the chain is single-mode and AI-first. Bundles a meta-validator companion skill that auto-fixes frontmatter / relations / git timestamps, rebuilds .agents/.tag-index, scans for secrets, and enforces tight length recommendations (AGENTS.md 50/80/120, README.md 80/120/200). Use whenever the user wants to initialize a project, bootstrap AGENTS.md, unify instruction files across AI tools, retrofit an existing project, validate routing READMEs, or make a repo AI-navigable - even if they say 'AI rules', 'agent config', or 'check AGENTS.md'.

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Elasticsearch best practices covering mapping, query DSL, index settings, bulk indexing, analyzers, shard sizing, aggregations, pagination, ILM, aliases, and cluster monitoring. Use when designing or changing index mappings, writing or tuning search queries, configuring analyzers, planning shards, building bulk indexing pipelines, or diagnosing Elasticsearch performance issues.

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Postgres performance optimization and best practices. Use when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.

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Programming principles and philosophy based on Rob Pike's 5 Rules of Programming, with related wisdom from Tony Hoare, Ken Thompson, and Fred Brooks. Make sure to use this skill whenever the user is making optimization decisions, choosing between simple and complex algorithms, designing data structures, evaluating performance tuning approaches, reviewing code for unnecessary complexity, or pushing back on premature optimization and over-engineering - even if they do not explicitly mention Pike, principles, or philosophy.

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