obsidian
claudecodexObsidian vault workflows (notes/markdown/diagrams/canvas) + LLM wiki layer (defuddle needs CLI).
23 skills · 1 agent
Local-only two-layer knowledge base for dbt projects — semantic Q&A over manifest + column lineage.
Plugin dbt-wiki from marketplace monkey-skills in kouko/monkey-skills. Commands read from the repo's manifest — 6 days ago.
ingestRecord dbt tribal knowledge not in manifest/schema.yml (sort_key rationale, dialect gotchas, incident links) into a model's User Notes (survives rescan). Use for 'remember that fct_orders…', 'add note to <model>', '備註 fct_X'. To query, use query.
initFirst-time setup: scaffold .dbt-wiki/ from manifest.json + compiled SQL (sqlglot column lineage) + inline comments — pages, index, lineage DAG, CLAUDE.md. Needs dbt parse && compile first. Use for 'init dbt-wiki' or '初始化'. Later updates→rescan.
packPackage .dbt-wiki/ into a portable, warehouse-agnostic analytics Agent Skill a teammate can use with their own warehouse tool — knowledge + SQL guidance, not an executor. Use for 'package the dbt-wiki knowledge' or 'export for a teammate'.
queryAnswer any dbt question from .dbt-wiki/: model structure, column lineage, config, schema.yml, refactor impact, ingested notes — before reading dbt/ files. Use for 'trace column', 'what feeds X', 'rename impact', '依賴什麼'. Setup→init, updates→rescan.
redistillRe-distill the stale knowledge pages rescan flagged — LLM rewrites entities/metrics/concepts whose derived_from evidence changed, grouped by domain, skipping mature (human-certified) pages. Use for 'redistill', 're-distill stale knowledge', 'knowledge pages are stale', '重蒸餾知識頁'. This is the LLM half
rescanEvidence-layer-only refresh (advanced, 0 LLM): re-scan .dbt-wiki/ evidence — diff manifest md5, reprocess only changed resources, re-run sqlglot lineage, preserve User Notes, flag stale knowledge pages. Use ONLY when the ask is explicitly the cheap evidence half: 'rescan dbt-wiki', 'evidence only, 0
reviewHuman certification loop for dbt-wiki pages — lists pages needing review (developing or mature-but-stale), prioritizes by risk, certifies each → mature. Use for 'review pages', 'certify', 'what needs review', '審核'. Query → query.
updateTHE maintenance verb for dbt-wiki — one full pass: (optional) ingest new tribal knowledge → rescan evidence → gated redistill of stale knowledge → phantom-column lint gate → review handoff → scorecard. Runs every mechanical step, then hands the human-judgment part to review. Use for 'update dbt-wiki
using-dbt-wikiFamily-entry router for dbt-wiki — the knowledge base distilled from a dbt project (manifest + compiled SQL + column lineage) into .dbt-wiki/. Use when unsure which dbt-wiki skill applies: first-time setup, bringing the wiki up to date, asking a dbt question, or certifying pages. Triggers: 'dbt wiki
Obsidian vault workflows (notes/markdown/diagrams/canvas) + LLM wiki layer (defuddle needs CLI).
23 skills · 1 agent
Google Workspace toolkit on the official gws CLI (drive/docs/sheets/gmail; Claude Code CLI only).
18 skills · 1 command
Pipeline copywriting toolkit — 14 skills from intake to audit, grounded in PASONA/Cialdini/FTC.
14 skills · 2 agents
Three-layer investing research toolkit — data, analysis, report skills.
15 skills · 1 agent
Domain-expert team skills (planning/code/design/research/copywriting) with quality-gate checkpoints.
11 skills · 2 agents
Multi-scope coach for the 4 Disciplines of Execution — Socratic coach + single-artifact audit modes.
12 skills
RVF format for portable agent memory, session persistence, and cross-platform transfer
2 skills · 1 command · 1 agent
This plugin provides a specialized suite of skills for data engineers and database practitioners working on Google Cloud. It acts as an expert assistant, allowing you to use natural language prompts in your preferred coding agent to architect complex data pipelines, transform data with dbt, write Spark and BigQuery SQL notebooks, and orchestrate end-to-end workflows across GCP's data ecosystem.
37 skills
Atlan data catalog plugin for Claude Code. Search, explore, govern, and manage your data assets through natural language. Powered by the Atlan MCP server with semantic search, lineage traversal, glossary management, data quality rules, and more.
1 skill · 1 MCP server
Snowflake SQL, data pipelines (Dynamic Tables, Streams+Tasks), Cortex AI functions, Snowpark Python, and dbt integration. Includes query helper script, reference guides, and troubleshooting.
1 skill
This plugin provides a specialized suite of skills for data engineers and database practitioners working on Google Cloud. It acts as an expert assistant, allowing you to use natural language prompts in your preferred coding agent to architect complex data pipelines, transform data with dbt, write Spark and BigQuery SQL notebooks, and orchestrate end-to-end workflows across GCP's data ecosystem.
37 skills
Analytics engineering skills for warehouse exploration, dbt and semantic modeling, and schema-drift maintenance. Three skills (explore, transform, maintain) drive a local engine: warehouse reads are read-only and cost-gated, and project edits come back as reviewable diffs. Requires a local shell and uv; first use downloads the pinned engine from PyPI. No hooks, no MCP servers.
3 skills
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