Live Database Ingest
Import live database schemas and create semantic layers from snapshot files.
Installation
- Make sure Claude is on your device and in your terminal.
Skills load from
~/.claude/skills/when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then runclaudein any terminal to verify.One-time setupnpm i -g @anthropic-ai/claude-codeAlready have it? Skip ahead.
- Paste into Claude Code or into your terminal.
This copies the whole skill folder into
~/.claude/skills/live-database-ingest-kaelio/— the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.Faster alternative (instruction-only skills)
Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.
Quick install (SKILL.md only)Sign up to copy - Restart Claude Code.
Quit and reopen Claude Code (or any other agent that loads from
~/.claude/skills/). New skills are picked up on startup. - Just ask Claude.
Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.
Prefer to read the source first? Open on GitHub.
When Claude uses it
Capture semantic-layer and knowledge updates from a live database schema snapshot.
What this skill does
Live Database Ingest
Use this skill when the ingest work unit contains raw files under
raw-sources/<connectionId>/live-database/<syncId>/.
Workflow
- Read the table JSON file listed in the work unit.
- Read
connection.jsonto understand the snapshot metadata. - Read
foreign-keys.jsonwhen the table has a foreign key or when joins are needed for the semantic-layer source. - Create or update one semantic-layer source for the table with
sl_write_source. - Use the physical table name from the raw JSON as the source
tablefield. - Preserve database comments as
descriptions.dbon tables and columns. - Add joins only when the foreign key index names both sides.
- Write wiki pages only for durable business meaning that is present in table or column comments.
- Run
sl_validatefor the table source before the work unit completes.
Sample values come from the scan record; do not invent values not present in relationship-profile.json.
Identifier Verification Protocol
Before writing a wiki page or SL source on any topic:
discover_data({query: "<topic>"})- see what wikis, SL sources, and raw tables already exist. Prefer updating existing pages over creating new ones.
Before emitting any schema.table or schema.table.column into a wiki body,
SL source, tables: frontmatter, sl_refs, or emit_unmapped_fallback:
entity_details({connectionId, targets: [{display: "<identifier>"}]})- confirm the identifier resolves; inspect native types, FK/PK, and sampleValues.- For literal values from the source, such as status codes or plan tiers,
check whether they appear in
entity_detailssampleValues for the relevant column. If sampleValues is short or the sample may have missed real values, run asql_executionprobe with the same warehouse connection id:sql_execution({connectionId, sql: "SELECT DISTINCT <col> FROM <ref> LIMIT 50"}). - If the candidate identifier still does not resolve, do one of:
- Use
sql_execution({connectionId, sql: "SELECT 1 FROM <ref> LIMIT 0"}). If it errors, the identifier is fictional. - Wrap the identifier in
[unverified - from <rawPath>]in the wiki body, citing the exact raw path that mentioned it. - When recording
emit_unmapped_fallbackwithno_physical_table, include the failing probe error inclarification.
- Use
- Never copy
<schema>.<table>placeholder strings from these instructions into output.
Source shape
For a raw table with this shape:
{
"name": "orders",
"db": "public",
"columns": [
{ "name": "id", "type": "integer", "nullable": false, "primaryKey": true }
]
}
Write a semantic-layer source with this shape:
name: orders
table: public.orders
grain: id
columns:
- name: id
type: number
Use string, number, time, or boolean for column types. When a database
type is ambiguous, use string.
Boundaries
The raw snapshot is structural evidence. Do not invent measures, segments, business definitions, or joins that are not present in the snapshot files.
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