E2E sub-agent finding: `da query --remote "SELECT * FROM <id>"` against a
materialized table that hasn't yet been rebuilt in the server's
analytics.duckdb returns a confusing DuckDB "Table does not exist"
message even though the table is in the registry. Materialized rows
produce parquets at `${DATA_DIR}/extracts/<source>/data/<id>.parquet`,
but the orchestrator's master-view creation is `_meta`-driven — fresh
instances or pre-tick states have the registry row without a
corresponding view, so analysts hit the bare "does not exist" with no
path forward.
Improve the error rendering in `app/api/query.py:execute_query`. When
DuckDB raises a "table does not exist" error, scan the registry for any
`query_mode='materialized'` row whose id or name appears in the failed
SQL. On a hit, return a 400 whose detail names the table, explains the
materialize state, and offers two concrete next steps:
1. Run `da sync` (or wait for the scheduler tick / hit
POST /api/sync/trigger) to materialize the parquet, OR
2. Query the source directly via the catalog alias when the registry row
carries bucket+source_table (e.g. `bq."dataset"."table"` for BigQuery,
`kbc."bucket"."table"` for Keboola).
Detection is bounded — the registry round-trip only fires when DuckDB's
error mentions a missing table, so happy-path queries pay no cost.
Non-materialized unknowns fall through to DuckDB's raw error.
2 new tests: materialized id surfaces the hint with the bucket+source_table
payload; unknown table falls back to the generic error path with no false
positive on the new hint.
Replaces the BigQuery wrap-view pattern with a discovery + scoped-fetch toolkit driven by the analyst's Claude session. Adds /api/v2/{catalog,schema,sample,scan,scan/estimate}, da catalog/schema/describe/fetch/snapshot/disk-info CLI commands, sqlglot-backed WHERE validator, process-local quota tracker, agent rails skill (cli/skills/agnes-data-querying.md). BREAKING: BQ wrap views off by default — set data_source.bigquery.legacy_wrap_views=true for one cycle. Backward-compat field_validator on primary_key. Catalog cache now matches documented 300s TTL with RBAC fresh per request. Cuts release v0.14.0.
Add information_schema, duckdb_* introspection functions, pragma_* functions,
and relative path traversal patterns to the SQL blocklist so users cannot
enumerate schema metadata regardless of RBAC. Add six corresponding tests.
Replace substring matching with word-boundary regex in query endpoint's
table access validation. Prevents false positives where short table names
like 'id' would block any query containing the word. Uses re.escape() to
safely handle special characters in table names.
- Import re module at top
- Use regex pattern with word boundaries (\b) for matching
- Add tests to verify no false positives and proper blocking
Expand blocked keywords to cover parquet_scan, read_csv_auto, query_table,
iceberg_scan, delta_scan, call, URL schemes (http/https/s3/gcs), and
additional file-scan functions. Set enable_external_access=false on the
non-read-only analytics connection path. Add three new tests covering
parquet_scan, read_csv_auto, and query_table blocking.
Schema v3: add is_public column to table_registry (default true).
src/rbac.py: can_access_table() checks admin bypass, public flag,
explicit permissions, wildcard bucket permissions.
API enforcement:
- manifest: filters tables by user access
- download: 403 if no access
- catalog: filters table list
- query: validates referenced tables against allowed list
New admin permissions API (/api/admin/permissions) for grant/revoke.
28 access control tests + 733 total tests passing.
