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 powerbi-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/powerbi-workflows)<a href="https://agentmods.dev/skills/kemetra/seshat-bi/powerbi-workflows"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/powerbi-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/powerbi-workflows"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/powerbi-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 | $0.00053 | $0.02426 |
| Opus 5 | $0.00026 | $0.01213 |
| Sonnet 5 | $0.00011 | $0.00485 |
| Haiku 4.5 | $0.00005 | $0.00243 |
Grade A, and why
powerbi-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 7d 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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Power BI workflows
Read ../../portable-operating-contract.md before acting. These routes never
replace readiness gates: no invented metric, measure, KPI, or DAX meaning; no
numeric readiness/confidence score; no self-granted approval; no
dashboard-ready claim without committed evidence.
One front door, explicit execution owners
This skill is the broad Power BI front door. It owns intent classification and
Seshat's pre/post gates; it does not reproduce Microsoft execution behavior.
For execution-shaped requests, use seshat pbi-mcp doctor as the canonical
machine-checkable selector even when the selected owner is an official skill
rather than an MCP server.
| User intent | Seshat pre-gate | Execution owner | Seshat after execution |
|---|---|---|---|
| Business/report intent and metric meaning | approved decisions and contracts | Seshat knowledge/governance | readiness and evidence |
| Dashboard/page design | approved metrics, semantic evidence, narrative brief | Microsoft powerbi-report-design |
Seshat human-review and evidence gates |
| Native PBIR page/visual/filter/slicer/binding authoring | exact target semantic pass, named-human dashboard_ready approval, official skill discoverable |
Microsoft powerbi-report-authoring |
binding, blueprint, and static validation |
| Bounded theme/format/background/geometry edits | exact target semantic pass, named-human dashboard_ready approval, and command allow-list |
temporary Seshat PBIR gap adapter | binding-preservation and static validation |
| Semantic-model edit | exact target semantic pass; F016 policy | BLOCKED while F016 is parked | no execution |
| Published semantic-model query | governed target and tenant prerequisites | Microsoft remote Power BI MCP | evidence interpretation |
| PBIP inspection/adoption | repository target | Seshat read-only tools | findings and next action |
For native report authoring run:
seshat pbi-mcp doctor --repo . --intent report-authoring --target <table> --harness <claude-code|codex>
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.
- 7d ago First seen · 183 lines · 53 tokens per session scan A 1938d71b7cc2
powerbi-workflows is a skill published in the GitHub repository Kemetra/Seshat-BI (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 53 tokens to every session and 2,426 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
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.
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/.
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…
lookml_ingest
Map a LookML view/model/explore into ktx semantic layer sources. Covers the LookML to ktx primitive table, provenance tagging, and three worked examples (overlay, standalone from derivedtable, standalone with sqlalwayswhere). Load when the turn contains .lkml content.