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.
git 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/commands/kemetra/seshat-bi/help)<a href="https://agentmods.dev/commands/kemetra/seshat-bi/help"><img src="https://agentmods.dev/badge/commands/kemetra/seshat-bi/help/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/commands/kemetra/seshat-bi/help"><img src="https://agentmods.dev/badge/commands/kemetra/seshat-bi/help.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 | $0.00015 | $0.00661 |
| Opus 5.5 | $0.00006 | $0.00264 |
| Sonnet 5.5 | $0.00003 | $0.00132 |
| Haiku 4.5 | $0.00002 | $0.00066 |
Grade A, and why
help 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.
What it actually says
Report the installed Seshat BI surface truthfully; never advertise anything absent from this list.
Slash commands (Claude Code namespaces them by plugin, so invoke as
/seshat-bi:<name>, e.g. /seshat-bi:next):
help-- this command map.init-- initialize or inspect a fresh project safely.check-- run and interpret the static governance check.status-- report the truthful per-table readiness status.next-- return the one truthful next readiness action.doctor-- run and interpret the workspace health check.review-- review readiness evidence and stop at the human gate.auto-- run the governed autonomous loop until the next human gate.dbt-doctor-- check governed dbt prerequisites without a database query.dbt-plan-- validate Mapping Ready and prepare an immutable execution plan.dbt-build-- execute the fixed shadow graph under an accepted plan digest.dbt-review-- review normalized dbt evidence and stop at the human gate.powerbi-design-- guarded dashboard/page design from approved metric contracts.powerbi-review-- screenshot review, dashboard QA, blueprint validation, PBIR review.powerbi-theme-- theme JSON, palette, typography, filter-pane defaults, backgrounds, canvas.powerbi-format-- formatting plans and governed PBIR formatting/geometry.powerbi-adopt-- adopt an existing PBIP project through assess/scaffold.dagster-doctor-- read-only orchestration preflight (environment, pinned dagster, gates).dagster-run-- execute one governed orchestration job, fail-closed behind every gate.dagster-evidence-- list runs or render a run's committed derived evidence.
The former names seshat-init, seshat-check, seshat-next, and
seshat-review remain as deprecated aliases for one release cycle and behave
identically to their bare forms.
Bundled skills: seshat-bi (readiness router), dbt-workflows (governed dbt
routing), powerbi-workflows (guarded Power BI routing), and the knowledge
skills bi-sql-knowledge,
bi-dax-knowledge, bi-python-knowledge, bi-bigdata-knowledge, and
retail-kpi-knowledge.
Slash commands and terminal CLI verbs are different surfaces: a slash command
is a reviewed prompt inside this agent session, while seshat is a separately
installed Python package (pipx install seshat-bi). If seshat is not
installed, say so instead of simulating its output. Useful CLI-only verbs with
no slash wrapper include validate, drift, semantic-check, generate,
value-check, evidence-pack, approvals, pack, and watch; list
everything with seshat --help.
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 · 49 lines · 15 tokens per session scan A 27cf6b752471
help is a command published in the GitHub repository Kemetra/Seshat-BI (2 stars, last pushed 6d ago), licensed Apache-2.0. It adds 15 tokens to every session and 661 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 commands, from other repositories
snowflake-demo
Dev mode — run the whole migration pipeline against an emulated Snowflake estate and an emulated AIDP. No credentials, no network, nothing real is touched; writes every real artifact plus a narrated DEMO.md.
onboarding-flow-optimizer
Optimize user onboarding to reduce time-to-value and increase activation rates. Design clear paths to the "aha moment" through checklists, product tours, educational content, and personalized flows. Generate actionable HTML reports with funnel analysis, email sequences, and A/B testing plans.
ts-glossary
TS bilingual-courseware glossary mode — course terminology glossary.
learning-path
Get personalized learning recommendations based on your goals, experience level, and learning style.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.