hotdata-dev/hotdata-search
skills/hotdata-search/SKILL.md
Use this skill when the user wants full-text search, BM25 keyword search, vector similarity search, semantic search, embeddings, or retrieval indexes in Hotdata. Activate for "hotdata search", "BM25", "full-text", "vector search", "semantic search", "similarity", "embedding", "embedding provider", "create an index" (bm25 or vector), "list indexes" for search, or SQL using bm25_search or vector_distance. Do not load for general SQL analytics (aggregations, GROUP BY) or geospatial work — use hotdata-analytics or hotdata-geospatial instead. Requires the core hotdata skill for auth and workspace basics.
$ install --global
skillsauthnpx skillsauth add hotdata-dev/hotdata-cli hotdata-searchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- hotdata-search
- description:
- Use this skill when the user wants full-text search, BM25 keyword search, vector similarity search, semantic search, embeddings, or retrieval indexes in Hotdata. Activate for "hotdata search", "BM25", "full-text", "vector search", "semantic search", "similarity", "embedding", "embedding provider", "create an index" (bm25 or vector), "list indexes" for search, or SQL using bm25_search or vector_distance. Do not load for general SQL analytics (aggregations, GROUP BY) or geospatial work — use hotdata-analytics or hotdata-geospatial instead. Requires the core hotdata skill for auth and workspace basics.
- version:
- 0.4.0
Hotdata Search Skill
Retrieval workloads in Hotdata: BM25 full-text, vector similarity, and the indexes and embedding providers that power them.
Prerequisites: Authenticate and select a workspace (see the hotdata skill). Use fully qualified table names: <connection>.<schema>.<table>.
Related skills: hotdata-analytics (OLAP SQL, query history, materialized chains), hotdata-geospatial (PostGIS-style functions).
Search CLI
Both run server-side. --type and --column are optional when the table has exactly one search index — they are inferred automatically. Specify them when multiple indexes exist.
# BM25 (requires a BM25 index on the column)
hotdata search "<query>" --table <connection.schema.table> [--type bm25] [--column <column>] \
[--select <columns>] [--limit <n>] [--workspace-id <workspace_id>] [--output table|json|csv]
# Vector (requires a vector index; server auto-embeds the query text)
hotdata search "<query>" --table <connection.schema.table> [--type vector] [--column <source_text_column>] \
[--select <columns>] [--limit <n>] [--workspace-id <workspace_id>] [--output table|json|csv]
| Type | Behavior |
|------|----------|
| bm25 | Server generates bm25_search(table, col, 'text'). Results sort by score (descending). |
| vector | Pass plain-text query; name the source text column (e.g. title). Server embeds using the same provider/metric/dimensions as the index. SQL uses vector_distance(col, 'text'). Results sort by distance (ascending). |
- Inference: when
--typeor--columnare omitted, the CLI fetches the table's indexes and selects the only BM25/vector index. If multiple exist, you must specify both flags. - No vector index, or custom embedding model? Use raw SQL via
hotdata query(e.g.cosine_distance(col, [<vec>])). The removed--model/ stdin-vector paths hardcodedl2_distanceand are not supported. - Before search: create the right index (
indexes create --type bm25or--type vector). See references/INDEXES.md. - Default
--limitis 10.
Indexes (BM25 and vector)
Indexes attach to a connection table (--connection-id + --schema + --table) or a dataset (--dataset-id). Scopes are mutually exclusive for create/delete.
# List — workspace scan on connection tables (filter with -c / --schema / --table)
hotdata indexes list [--connection-id <id>] [--schema <schema>] [--table <table>] [--workspace-id <ws>] [--output table|json|yaml]
hotdata indexes list --dataset-id <dataset_id> [--workspace-id <ws>] [--output table|json|yaml]
# Managed database (catalog alias — uses the active database when the catalog matches)
hotdata indexes create --catalog <alias> --schema <schema> --table <table> \
--column <col> --type bm25|vector \
[--name <name>] [--metric l2|cosine|dot] [--async] \
[--embedding-provider-id <id>] [--dimensions <n>] [--output-column <name>] [--description <text>]
# Connection table (raw connection ID)
hotdata indexes create --connection-id <id> --schema <schema> --table <table> \
--column <col> --type bm25|vector [--name <name>] ...
hotdata indexes delete --connection-id <id> --schema <schema> --table <table> --name <name>
# Dataset
hotdata indexes create --dataset-id <dataset_id> --column <col> --type bm25|vector [--name <name>] ...
hotdata indexes delete --dataset-id <dataset_id> --name <name>
--typeis required on create:bm25(one text column) orvector(exactly one column; often embeddings or auto-embedded text).sortedindexes (range/equality for OLAP filters) are documented inhotdata-analytics— this skill focuses on retrieval types.--async: poll withhotdata jobs <job_id>(seehotdataskill Jobs).- Auto-embedding:
--type vectoron a text column generates embeddings server-side. Optional--embedding-provider-id; default output column{column}_embedding(override with--output-column).
Full workflow (gather workload → compare existing → create → verify): references/INDEXES.md.
Embedding providers
hotdata embedding-providers list [--workspace-id <workspace_id>] [--output table|json|yaml]
hotdata embedding-providers get <id> [--workspace-id <workspace_id>] [--output table|json|yaml]
hotdata embedding-providers create --name <name> --provider-type service|local \
[--config '<json>'] [--provider-api-key <key> | --secret-name <name>] [--workspace-id <workspace_id>]
hotdata embedding-providers update <id> [--name <name>] [--config '<json>'] [--provider-api-key <key> | --secret-name <name>] [--workspace-id <workspace_id>] [--output table|json|yaml]
hotdata embedding-providers delete <id> [--workspace-id <workspace_id>]
- System providers (e.g.
sys_emb_openai) are pre-configured; uselistfor IDs to pass to--embedding-provider-id. --provider-api-keyis the embedding service key (not Hotdata--api-key).--secret-namereferences an existing secret.
Quick workflow
hotdata tables list --connection-id <id>— confirm column types.hotdata indexes list— avoid duplicate indexes.hotdata indexes create --catalog <alias> --table <table> --column <col> --type bm25|vector(add--asyncif large).hotdata search "..." --table <catalog.table>—--typeand--columnare inferred when there is one search index.- Record what exists in context:DATAMODEL (core skill) when the workspace should remember index choices.
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