De la autor
Use this whenever you need to know what is actually in a database, warehouse, or DuckDB file before you trust it: inventory, column profiles, PII detection, grain and data-quality problems, verified joins, ER diagrams, ad-hoc SQL probes, segmentation, and the semantic layer a repo declares (dbt, Apache Ossie, or SLayer). Trigger it on an unmet precondition, not on phrasing: if you are about to write or fix SQL against tables whose columns, types, grain, or join keys you have not verified in this session, use this FIRST. That includes dbt work (building a model, fixing one, debugging wrong numbers) whenever the ticket names source tables without spelling out their schema. It applies mid-task too: on reaching a table you have not inspected, stop and use this rather than guess column names. Also for "what's in my duckdb", "is this data any good", "how do these tables relate". Read-only; writes only the .dex/ cache. It does not author the model: transform does, and maintain reconciles a project that has drifted.
Instalare
npx skills add hashgraph-online/awesome-codex-plugins --skill explore -a claude-code
Se instalează în .claude/skills/explore/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Verificări de siguranță pe SKILL.md
- Include scripturi pe care nu le-am verificatScăzut
De ce 82
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- transformhashgraph-online/awesome-codex-pluginsUse this to author and change a dbt project or a semantic layer: bootstrap a project (`transform init`), write or refactor models from staging to marts, add tests and docs, and define semantic models, entities, dimensions, and metrics in MetricFlow, Apache Ossie or SLayer YAML. Reach for it instead of editing model files by hand whenever a change spans more than one file or must stay consistent with the project: it validates the edit against the real schema, returns a reviewable diff with a plan id, and catches what otherwise fails at `dbt run`, such as wrong columns or broken refs. Bug-fix tickets count: "this model returns wrong numbers, fix it" is a transform task. Also for "build a staging model for this table", "define a revenue metric", "add a dimension to this entity". Warehouse builds are dev-target only, gated, and cost-surfaced first. If you have not verified the source tables' columns or grain, use explore first. For a project that drifted from the warehouse, use maintain.Testare★ 1.4K
- maintainhashgraph-online/awesome-codex-pluginsUse this to find out whether an existing dbt project or semantic layer (dbt, Ossie or SLayer) is correct against its warehouse, and if not, why. `maintain verify` checks the project as it stands; against a .dex/ snapshot, `maintain check` finds schema, volume, grain, and semantic drift and `maintain reconcile` proposes the fix. Reach for it whenever an existing project is suspected wrong, whether or not anything is known to have changed: "this model is wrong, work out why", "the numbers look too high", "some rows are missing", "this column is empty", "duplicates in my fact table", "the project is broken", "diagnose why this test fails", "a test fails and nobody changed the model", "the dashboard moved but the code did not", "did anything drift", "the row count dropped", "the metric definition changed". Read-only; fixes come back as reviewable diffs and never overwrite hand-written work. Writing the fix, or repairing a model you just edited, is transform's; a data question with no project is explore's.Testare★ 1.4K
- explore-dataanthropics/knowledge-work-pluginsProfile and explore a dataset to understand its shape, quality, and patterns. Use when encountering a new table or file, checking null rates and column distributions, spotting data quality issues like duplicates or suspicious values, or deciding which dimensions and metrics to analyze.OficialAltele★ 31.9K
- schema-explorationtimescale/pg-aiguideExplore an existing PostgreSQL database before answering questions about its data or writing SQL. Use this skill whenever a user asks for a query or a data-backed answer against an unfamiliar schema (counts, missing or failed records, recent changes), asks where a business concept lives, or asks how tables, joins, views, routines, triggers, RLS, or extensions work. Find the relevant objects with read-only pg_catalog queries, then request approval before inspecting data-derived statistics or rows. Not a schema-design or migration guide.Date★ 1.9K
- database-scoutzebbern/claude-code-guideExplore SQLite and PostgreSQL databases: list tables, inspect schemas (columns/types/constraints), preview data, generate Mermaid ER diagrams, and run safe read-only queries. Triggered by requests to explore a database, view table structures, describe tables, generate diagrams, or query data, and by keywords like database exploration, schema, ER diagram, or SQL query.Date★ 4.7K
- sql-proJeffallan/claude-skillsOptimizes SQL queries, designs database schemas, and troubleshoots performance issues. Use when a user asks why their query is slow, needs help writing complex joins or aggregations, mentions database performance issues, or wants to design or migrate a schema. Invoke for complex queries, window functions, CTEs, indexing strategies, query plan analysis, covering index creation, recursive queries, EXPLAIN/ANALYZE interpretation, before/after query benchmarking, or migrating queries between database dialects (PostgreSQL, MySQL, SQL Server, Oracle).Date★ 12K
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