scan_enabled:false promised the connection is 'never used as a scan/ingest
target,' but the predicate only gated automatic selection — explicit
ktx scan <id> / ktx ingest <id> still resolved the connection id and reached the
live-database introspection path, so an execute-only connection could still be
scanned or ingested.
Guard runKtxScan and runKtxIngest at entry: if the target connection is
execute-only, refuse with an actionable error (remove the flag to scan, or use
ktx sql to query) before doing any work. This makes the flag a single declaration
honored on every scan/ingest entry point, not just auto-selection.
A configured warehouse was always a scan/ingest target. The only way to use a
connection purely for SQL execution (ktx sql / sql_execution) was the leaky
workaround of an empty setup.database_connection_ids — which actually re-includes
every warehouse via the 'fall back to all' branch — so e.g. a BigQuery connection
meant only for read-only queries triggered a full-billing-project scan.
- Add a per-connection scan_enabled flag (default true) to warehouse connections.
scan_enabled: false registers the connection for execution only and never as a
scan target.
- Route every scan-target selection path through one predicate
(isScanTargetWarehouse): both ingest (primaryWarehouseConnectionIds, including
the all-warehouses fallback) and setup (configuredPrimaryConnectionIds) now
exclude execute-only connections. Setup validates the credential but skips
scope discovery and scan for them. Execution paths are untouched — the warehouse
descriptor still resolves, so ktx sql / sql_execution keep working.
- Scripted setup with no --database-schema no longer silently scopes the scan to
every discovered schema/dataset: it warns with the count and names how to narrow
(--database-schema) or opt out (scan_enabled: false).
Both documented flags were read only for status display; every ingest path
squash-committed to main unconditionally, so setting either to false was a
silent no-op (the reported symptom: 'Memory ingest (external_ingest): ...'
commits despite memory.auto_commit: false).
Gate the commit at the squash-merge onto main — the one point where ingest work
becomes a permanent commit (intermediate session-worktree commits must still
happen for the squash to collapse). When auto-commit is off, apply the squash to
main's working tree and leave it staged instead of committing, so the run is
never silently discarded:
- GitService.stageSquashMergeIntoMain: shares the merge core with
squashMergeIntoMain but stops before committing and returns the staged tree
SHA (a valid diff/read ref).
- memory.auto_commit gates MemoryAgentService (its DB writes are eager, so the
staged files stay consistent); the commit-message job is skipped.
- storage.git.auto_commit gates IngestBundleRunner; the wiki index is reconciled
from the staged tree via the existing syncFromCommit (git diff/show accept a
write-tree ref), and SL reindex already reads from files.
Config descriptions now state precisely what each flag gates and the staged
semantics when false.
* feat(setup): write per-role llm model presets
* feat(setup): remove llm model setup flag
* chore(setup): update llm preset guidance
* docs(setup): document llm model presets
* chore(release): sync uv.lock to 0.9.0
* fix(cli): make sl query --execute work on secret-backed connections
sl query --execute used a parallel SQL executor (createDefaultLocalQueryExecutor)
that passed connection.url verbatim into pg, so file:/env: secret references
failed with "SASL: SCRAM-SERVER-FIRST-MESSAGE: client password must be a string".
Collapse onto the connector-based executor already used by MCP and ingest
(createKtxCliIngestQueryExecutor), which resolves secret references and supports
every driver. Delete the now-dead local/postgres/sqlite query executors, their
tests, and the orphaned hasLocalQueryExecutor driver flag.
* docs(agents): require one implementation per capability
Add a design-reasoning default and a matching self-check question telling agents
to route callers through a single shared implementation of a capability rather
than forking a parallel one, and to fix the shared layer rather than patch one
branch. Encodes the lesson from a divergent SQL-execution-path bug, stated
generally.
CLAUDE.md is a symlink to AGENTS.md, so both agent-instruction files are covered.
* feat(cli): add ingest rate limit governor
* feat(cli): wire ingest rate-limit config
* feat(cli): report provider rate-limit signals
* feat(cli): show ingest rate-limit waits
* fix(cli): complete rate-limit event coverage
* fix(cli): abort ingest provider calls cleanly
* fix(cli): propagate ingest cancellation
* fix(cli): reject pre-aborted ingest rate-limit waits
* fix(cli): honor Claude rate-limit reset waits
* fix(cli): retry thrown Codex rate-limit failures
* fix(cli): type Claude rate-limit result details
* fix(cli): emit ingest rate-limit countdowns from rejected signals
* fix(cli): report ai sdk rate-limit header utilization
* fix(cli): gate LLM rate-limit retries on the governor budget
The AI SDK and Codex runtimes retried 429 / opaque rate-limit failures up
to 6-7 times with no backoff when constructed without a RateLimitGovernor
(scan, memory, setup) or with pacing disabled, ignoring Retry-After and
worsening the limit. The outer retry loop only cooperates with the
governor's pause, so without active pacing there is no backoff to apply.
Route the retry bound through a single source: RateLimitGovernor
.maxRetryAttempts(), which returns retry.maxAttempts when enabled and 1
(no outer retry) when absent or disabled. All three runtimes (ai-sdk,
codex, claude-code) now use it, so ingest.rateLimit.retry.maxAttempts
genuinely controls attempts and the hard-coded 6 (plus Codex's off-by-one
extra attempt) is gone. Backend-native retry (e.g. the AI SDK's maxRetries)
still handles transient 429s.
Also correct the ktx.yaml docs for maxWaitMs (caps each wait, not the whole
run) and maxAttempts, and sync uv.lock ktx-sl/ktx-daemon to 0.9.0.
* feat: add codex sdk runner foundation
* feat: parse codex runtime events
* feat: expose codex runtime mcp tools
* feat: add codex llm runtime
* feat: wire codex llm backend
* test: avoid Array.fromAsync in codex runner test
* docs: document codex llm backend
* fix: tighten codex runtime config ownership
* fix: use codex sdk env and thread options
* fix: parse codex sdk event shapes
* test: add codex backend live smoke
* docs: clarify codex backend isolation
* fix: drive codex loop metrics from mcp events
* fix: enforce codex local step budget
* docs: disclose codex isolation limits
* fix: count all codex agent steps and stream step callbacks live
The agent-loop step budget only counted completed mcp_tool_call items, so
built-in command_execution steps (which the public Codex SDK/CLI surface can
still expose) never decremented the budget, letting ingest/reconciliation run
past stepBudget until Codex stopped on its own. onStepFinish was also replayed
only after the whole stream drained, so live work_unit_step / reconciliation
progress appeared stuck until the Codex process exited.
collectEvents is now the single live step accumulator: it counts every
completed agent-action item via a shared isCompletedAgentStep predicate
(command_execution, mcp_tool_call, file_change, web_search), fires onStepFinish
as each step completes, and enforces the budget on that broader count. A
no-tool turn still counts as one step. toolFailures stays MCP-specific, since a
non-zero command exit is normal agent exploration, not a loop failure.
* test: align ingest llm-guard assertions with codex backend
The skip-llm ingest guard message now lists codex as a valid backend and
mentions a Claude Code/Codex session plus a codex setup hint, but this slow
suite test still asserted the pre-codex wording. Update it to match the
production message (already covered by the local-bundle-runtime unit test) and
add the codex setup-line assertion.
* fix: treat codex error:null tool calls as success
The Codex SDK serializes error: null on successful mcp_tool_call items, so
the failure check (item.error !== undefined) flagged every successful tool
call as failed with the empty-payload default "Codex turn failed". This
killed every ingest work unit under the codex backend before it could
produce a patch.
Key on status === 'failed' (authoritative, always set) and only treat a
populated error object as a failure. Add a regression test built from a
verbatim real-SDK event capture.
* fix: default codex backend to gpt-5.5 and report real probe errors
The previous default gpt-5.3-codex is an API-key-only model that the OpenAI
API rejects under ChatGPT-account (subscription) auth, so codex status/setup
failed with a misleading "authentication is not usable" message even though
auth was fine.
- Default codex model is now gpt-5.5 (works on both subscription and API-key
auth); the curated setup picker offers gpt-5.5 / gpt-5.4 / gpt-5.4-mini and
keeps free-form entry for account-specific ids (e.g. gpt-5.3-codex-spark).
- runCodexAuthProbe now distinguishes "model not available" from an auth
failure and surfaces the real API error: collectEvents retains stream
events when the SDK throws on a non-zero exit, and the API error JSON
envelope is unwrapped to its human-readable message.
- The Codex isolation warning now renders inside the clack setup frame.
- Docs updated to gpt-5.5 with a note that *-codex ids require API-key auth.
* fix: require llm.models.default in status and match codex probe remediation
Status reported a project ready when a non-none LLM backend was configured
without llm.models.default, but the runtime (resolveModelSlots) hard-requires
it, so ingest/scan/memory threw after `ktx status` said the project was usable.
buildLlmStatus now fails for any non-none backend missing models.default and no
longer invents a fallback model for claude-code/codex.
Codex probe failures now carry a category-matched fix: a model-access failure
steers the user at llm.models.default instead of the auth/install remediation.
runCodexAuthProbe returns the fix and status consumes it; the message stays
self-sufficient so setup output is unchanged.
Docs: README now lists the codex backend and local Codex auth; ktx-setup.mdx
states --llm-model only accepts codex/default or gpt-*/codex-* ids.
Repaired four doctor fixtures that configured a backend without models.default
(the now-correctly-blocked config) and added coverage for the new behavior.
Fast mode (the ktx ingest --fast/--deep database-ingest depth toggle) is removed.
ktx ingest now always builds the full enriched ("deep") context. There is no
structural fallback: a database connection without a configured model and
embeddings fails the enrichment-readiness preflight before any work runs, with
a 'Run ktx setup to configure a model and embeddings' hint.
- Remove --fast/--deep flags, the per-connection context.depth field, and the
ktx setup depth prompt (delete setup-database-context-depth.ts).
- Rename ingest-depth.ts -> connection-drivers.ts; ingest always requests scan
mode 'enriched'; readiness gate (enrichmentReadinessGaps) runs for every
database target.
- Drop the database-context-depth telemetry step (Node + Python schema mirrors
regenerated).
- Update CLI, setup, context-build view, docs, the public ktx skill, and the
release-smoke / artifacts scripts (now assert the no-LLM guard failure).
ktx status --fast (a separate network-probe flag) is unchanged.
Follow-ups: KLO-726 (live progress for ktx ingest --all), KLO-727 (restore
credentialed successful-ingest release smoke coverage).
* feat(setup): drop redundant Snowflake schema prompt; fall back to free-text on listSchemas failure
Snowflake setup previously asked for a single schema as free text, then
ran a multiselect against the discovered schemas — two schema questions
back-to-back, with the first being only a session bootstrap. The SDK's
`schema` is optional, so the bootstrap step is unnecessary.
- Remove the free-text Snowflake schema prompt; only pass `schema` to
snowflake-sdk when one is configured.
- When `listSchemas()` fails (e.g. role lacks SHOW SCHEMAS), prompt the
user for a comma-separated list, persist it as `schema_names`, and use
it as both the table-list filter and the multiselect default. Applies
to every driver with a scope-discovery spec, not just Snowflake.
- Update docs to lead with `schema_names`; keep `schema_name` as a
documented single-schema shorthand.
* fix(snowflake): keep introspecting when primary-key discovery is denied
The PK query joins INFORMATION_SCHEMA.TABLE_CONSTRAINTS and
INFORMATION_SCHEMA.KEY_COLUMN_USAGE, which require grants the
connection role may not have. Previously a 'SQL compilation error:
Object ANALYTICS.INFORMATION_SCHEMA.KEY_COLUMN_USAGE does not exist
or not authorized' aborted the entire introspect — schemas, columns,
and row counts were all discarded over a missing nice-to-have.
Wrap the constraint query in try/catch, log a one-line warning per
schema, and return an empty PK map. Columns end up with
primaryKey=false; relationship inference still has FK and profiling
to fall back on.
* fix(scan): unblock relationship discovery on Snowflake
Two adjacent bugs prevented the scan's relationship pipeline from producing
any joins on a Snowflake warehouse:
- relationship-profiling.ts fell through to a default `GROUP_CONCAT` branch
for unknown drivers. Snowflake has no GROUP_CONCAT, so every per-table
profile query failed with "Unknown function GROUP_CONCAT". Add an explicit
Snowflake branch that uses LISTAGG with a literal '\x1f' delimiter
(Snowflake requires the delimiter to be a constant, so CHR(31) is rejected).
- description-generation.ts destructured `connector.sampleTable` and
`connector.sampleColumn` into bare locals, losing the `this` binding when
the class-method connectors (Snowflake, Postgres, MySQL) were invoked.
Every sample call threw "Cannot read properties of undefined (reading
'assertConnection')" and degraded LLM descriptions to metadata-only
prompts. Call the methods through the connector instead.
Without these, even after the primary-key probe is allowed to fail softly,
the scan ends up with 0 validated relationships and an empty `joins:` block
in every shard YAML.
* test(scan): cover table-ref helpers
* feat(scan): plumb tableScope through live-database introspection port
* feat(scan): apply tableScope during metadata fetch
* feat(scan): enforce table scope at fetch boundary
* feat(scan): pool Snowflake sessions and batch enrichment for faster ingest (#206)
* feat(cli): add RSA key-pair auth option to Snowflake setup wizard
Extends the interactive Snowflake setup flow with an authentication-method
prompt (password vs RSA/JWT key-pair). The RSA branch collects a private-key
path (env/file/absolute) and an optional passphrase; the resulting connection
config records `authMethod: 'rsa'` with `privateKey` and `passphrase` instead
of `password`.
* feat(scan): pool Snowflake sessions
* fix(scan): reuse structural snapshots and cleanup connectors
* feat(scan): parallelize relationship profiling
* feat(scan): batch table description generation
* docs: document Snowflake ingest concurrency knobs
* fix(scan): close Snowflake ingest perf verification gaps
* fix(scan): keep batched description failure bounded
* feat(scan): dispatch query-history probes by connection driver
Extract historic-sql dialect resolution into a shared helper so the
status-project readiness check and the local ingest factory agree on
which connections enable query history and which probe to run. The
status command now picks the postgres/snowflake/bigquery probe based on
the connection's driver instead of always reporting against postgres,
which previously caused snowflake connections with queryHistory.enabled
to surface a misleading "driver is snowflake" failure.
Also drops a noisy console.warn from Snowflake primary-key discovery —
INFORMATION_SCHEMA.KEY_COLUMN_USAGE is commonly ungranted for read-only
roles and the FK + profiling paths handle the empty PK map already.
* fix(llm): allow StructuredOutput tool and raise maxTurns for generateObject
The Claude Code agent SDK announces an internal pseudo-tool named
StructuredOutput in the system/init message whenever outputFormat is set
to { type: 'json_schema' }. The runtime's isolation check built its
allowedToolIds set only from MCP tool ids and treated StructuredOutput
as an unexpected host-injected tool, so every generateObject call threw
"Claude Code runtime isolation failed: tools=StructuredOutput ..." and
the table-descriptions and relationship-LLM-proposal enrichment stages
recorded null output across the board.
Whitelist StructuredOutput specifically in generateObject's
allowedToolIds — the check also enforces missing_tools symmetry, so
generateText and runAgentLoop, which do not see StructuredOutput, must
not require it.
generateObject also ran with maxTurns: 1, which the model intermittently
breached when it emitted thinking text before the structured response.
Raised to 5 to give the schema-bound call enough headroom without
allowing unbounded loops. The existing tests now exercise the path with
an init message that announces StructuredOutput so the regression cannot
slip back in.
* chore(scripts): add ktx-reset.sh project-cleanup helper
Convenience script for repeatable ingest testing: takes a project
directory and prunes everything except ktx.yaml and .ktx/secrets/, so
the next ktx setup or ktx ingest run starts from a known-clean state.
Adds a new Configuration section to the docs with a reference page that
covers every top-level block of ktx.yaml: connections, setup, storage,
llm, ingest, scan, agent, and memory. Each block lists fields, defaults,
accepted values, and a short YAML example, with a leading schematic that
groups blocks into inputs, compute, and persistence.
