Kaelio/ktx is a context layer that helps AI agents query analytical databases using company knowledge, approved metrics, table metadata, and relationships between columns. Data teams use it to make warehouse queries more accurate and consistent with their organization's definitions. Its catalogue add-ons teach agents how to use ktx and its data-querying interfaces.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Kaelio/ktx --skill ingest_triagegit clone --depth 1 https://github.com/Kaelio/ktxWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kaelio/ktx/ingest_triage)<a href="https://agentmods.dev/skills/kaelio/ktx/ingest_triage"><img src="https://agentmods.dev/badge/skills/kaelio/ktx/ingest_triage/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kaelio/ktx/ingest_triage"><img src="https://agentmods.dev/badge/skills/kaelio/ktx/ingest_triage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.01243 |
| Opus 5 | $0.00018 | $0.00622 |
| Sonnet 5 | $0.00007 | $0.00249 |
| Haiku 4.5 | $0.00004 | $0.00124 |
Grade A, and why
ingest_triage scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ingest Triage - conflict classification and resolution
This skill is loaded in two contexts:
- By a Stage 3 WorkUnit agent when
sl_discover, deterministic projection output, existing project memory, or prior provenance overlaps with what the current WorkUnit is about to write. - By the Stage 4 reconciliation agent for cross-WorkUnit sweeps, accepted patch overlap, and eviction decisions.
Apply the rules below before every write that could collide with an existing artifact.
Decision tree
-
Is this the same artifact I'm producing now, or a different one with the same name? Read both. If names match and content matches (modulo whitespace): no conflict - skip the write, the prior one stands.
-
If content differs, is it an expression-only change (e.g. a different
sql:body for the same measure name, same grain, same columns)? Re-ingest change (expression-only): silently replace viasl_edit_source. No flag. -
If the difference is structural - grain, columns, filter, join shape - is the current bundle the re-ingest of a previously-ingested bundle (i.e.
priorProvenancehas a row for this raw file and artifact)? Re-ingest change (semantic break): replace + flag. Record in the IngestReport'sconflicts_resolvedlist withflagged_for_human: true. -
If reconciliation sees accepted patches from this same job with no prior-sync row, check for same-ingest contradictions:
Kind Detection Resolution Structural duplicate Same name, near-identical expression Elect canonical by: (a) highest inbound-ref count from other sources; tiebreak: (b) lexicographically first unit key; (c) lexicographically first source name. Subsume losers into <canonical>-variants.mdwiki page. Do NOT flag unless ambiguous.Near-duplicate cluster Different names, overlapping shape (same table, similar formulas) Same as structural; one canonical, others subsumed. Flag only if no canonical emerges. Definitional contradiction Same name, substantively different formulas (different aggregation, different filters, different columns) Rename + capture: disambiguate ALL variants with suffix derived from the domain ( churn_risk_engagement_based,churn_risk_billing_based) and write a unified wiki page listing every variant with provenance. The contested name does NOT land in the SL. Always flag.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 82 lines · 36 tokens per session scan A fafaf880c4d6
ingest_triage is a skill published in the GitHub repository Kaelio/ktx (1,581 stars, last pushed 6d ago), licensed Apache-2.0. It adds 36 tokens to every session and 1,243 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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