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 Kemetra/Seshat-BI --skill dbt-workflowsgit clone --depth 1 https://github.com/Kemetra/Seshat-BIWrote 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/kemetra/seshat-bi/dbt-workflows)<a href="https://agentmods.dev/skills/kemetra/seshat-bi/dbt-workflows"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/dbt-workflows/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/kemetra/seshat-bi/dbt-workflows"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/dbt-workflows.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00035 | $0.01903 |
| Opus 5.5 | $0.00014 | $0.00761 |
| Sonnet 5.5 | $0.00007 | $0.00381 |
| Haiku 4.5 | $0.00003 | $0.00190 |
Grade A, and why
dbt-workflows 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 1mo 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Governed dbt workflows
Read ../../portable-operating-contract.md before acting. For a governed
Seshat shadow workflow, use only the installed seshat dbt helpers; never
bypass their fixed selector, target, profile, lock, redaction, or artifact
checks with raw dbt commands.
Intent ownership
| User intent | Seshat pre-gate | Execution owner | Seshat afterward |
|---|---|---|---|
| Decide whether dbt fits the current BI stage | Readiness and approved-mapping context | Seshat selection policy | State one truthful next action |
| Scaffold governed shadow models | Approved committed source map | Seshat source-map-derived scaffold | Validate citations and the meta.seshat contract |
| Governed compile, build, test, or parity | Mapping Ready, exact selector, shadow target, and accepted immutable plan | dbt Core through seshat dbt |
Normalize artifacts into derived evidence, blockers, and parity findings |
| Generic dbt model authoring, test design, syntax, docs, or troubleshooting | Prove the official skill is activated and discoverable | Official dbt Labs agent skills | If the work enters Seshat's governed project, return through the Seshat gates above |
| Native dbt MCP configuration or tool use | Prove the exact MCP registration is activated and discoverable | Official dbt MCP and its official configuration skill | Do not infer a readiness effect; route governed execution back through seshat dbt |
| Switch from migrations to dbt | Passing parity evidence plus a named-human approval | Named human | Retain migrations as parity oracle and rollback path |
Spec 148 provides the read-only harness proof for the official dbt Labs agent
skills. Before routing generic competence, run
seshat integrations setup --profile analytics-full --harness <claude-code|codex>
and require the dbt-agent-skills result to be discoverable. MCP liveness remains
a separate preflight fact. Report the exact blocker for either surface; do not
copy official guidance into this router, claim an installed payload is usable,
or execute raw dbt commands against the governed project as a fallback.
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.
- 1mo ago First seen · 152 lines · 35 tokens per session scan A c21009b2c6cc
dbt-workflows is a skill published in the GitHub repository Kemetra/Seshat-BI (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 35 tokens to every session and 1,903 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
Other skills, from other repositories
powerbi-te-cli
The cross-platform Tabular Editor CLI (te) — a single self-contained binary for Windows, macOS and Linux that inspects, edits, validates, deploys, refreshes and tests Power BI and Analysis Services semantic models, with structured JSON/CSV/TMDL output and safe-by-default preview diffs. Distinct from Tabular Editor 2's…
ktx-analytics
Use when answering a question that needs data from a ktx-connected database - investigating, analyzing, "how many", "show me", "what's the breakdown of", finding records by value, exploring tables, comparing periods, explaining metrics, or any data-analysis request. Triggers even when the user does not say…
metabase_ingest
Convert Metabase questions, models, and metrics into ktx Semantic Layer source definitions. Covers result-metadata to KSL column type mapping, FK/PK detection, near-duplicate deduplication, pre-aggregation decomposition, join-graph connectivity, and how to react to priorProvenance from earlier ingest syncs. Load when…
sl_capture
How to capture new reusable patterns into ktx's semantic layer - when a measure, segment, or join belongs in the catalog and how to write it generically so it stays small and useful over time. Loaded by the post-turn memory-agent only. The research agent does not write to the SL.
metricflow_ingest
Map a MetricFlow semanticmodel or metric into ktx semantic layer sources. Covers the MetricFlow to ktx primitive table, extends: inheritance flattening, metric-type handling (simple / derived / ratio / cumulative / conversion), model: ref('x') resolution, and four worked examples. Load when the turn contains…
looker_ingest
Extract durable ktx knowledge and semantic-layer contribution proposals from staged Looker runtime dashboard, Look, and explore JSON. Load for WorkUnits whose raw files are under explores/, dashboards/, or looks/.