live_database_ingest — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited live_database_ingest (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Use this skill when the ingest work unit contains raw files under raw-sources/<connectionId>/live-database/<syncId>/.
connection.json to understand the snapshot metadata.foreign-keys.json when the table has a foreign key or when joins areneeded for the semantic-layer source.
sl_write_source.
table field.descriptions.db on tables and columns.or column comments.
sl_validate for 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.
Before writing a wiki page or SL source on any topic:
discover_data({query: "<topic>"}) - see what wikis, SL sources, and rawtables 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.
check whether they appear in entity_details sampleValues for the relevant column. If sampleValues is short or the sample may have missed real values, run a sql_execution probe with the same warehouse connection id: sql_execution({connectionId, sql: "SELECT DISTINCT <col> FROM <ref> LIMIT 50"}).
sql_execution({connectionId, sql: "SELECT 1 FROM <ref> LIMIT 0"}).If it errors, the identifier is fictional.
[unverified - from <rawPath>] in the wiki body,citing the exact raw path that mentioned it.
emit_unmapped_fallback with no_physical_table, includethe failing probe error in clarification.
<schema>.<table> placeholder strings from these instructionsinto output.
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: numberUse string, number, time, or boolean for column types. When a database type is ambiguous, use string.
The raw snapshot is structural evidence. Do not invent measures, segments, business definitions, or joins that are not present in the snapshot files.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.