From sqlfluff
Use when running SQLFluff lint on SQL or dbt-style projects and summarizing violations without immediately editing files.
How this skill is triggered — by the user, by Claude, or both
Slash command
/sqlfluff:sqlfluff-lint-triageThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Run SQLFluff lint in a way that is scoped, repeatable, and useful to an agent. Use this when the user asks what is failing, wants a lint summary, is introducing SQLFluff to a large project, or needs violations grouped into actionable next steps.
Run SQLFluff lint in a way that is scoped, repeatable, and useful to an agent. Use this when the user asks what is failing, wants a lint summary, is introducing SQLFluff to a large project, or needs violations grouped into actionable next steps.
Choose the smallest useful scope
Use agent-readable output
--format json for local triage.--format yaml when humans will inspect the output directly.--format sarif, github-annotation, or github-annotation-native for CI and PR annotations.Keep exploratory runs non-blocking
--nofail when collecting violations during rollout or diagnosis.--disable-progress-bar to keep logs parseable.--processes 0 only for large runs when full CPU parallelism is acceptable.Group findings by failure type
Recommend the next action
sqlfluff lint models/staging/orders.sql --format json --nofail --disable-progress-bar
sqlfluff lint models/staging/orders.sql --format yaml --nofail
sqlfluff lint models --format sarif --write-output sqlfluff.sarif --nofail
Return:
--ignore unless the user only wants a temporary rollout report.--nofail as success; it is only a reporting mode.references/output-formats.mdnpx claudepluginhub yu-iskw/sqlfluff-agent-plugins --plugin sqlfluffSearches MemPalace before answering questions about past work, people, projects, or prior decisions. Returns verbatim stored content instead of guessing from model memory.
Guides Payload CMS config (payload.config.ts), collections, fields, hooks, access control, APIs. Debugs validation errors, security, relationships, queries, transactions, hook behavior.
Implements vector databases with Pinecone, Weaviate, Qdrant, Milvus, pgvector for semantic search, RAG, recommendations, and similarity systems. Optimizes embeddings, indexing, and hybrid search.