Borrowing it
Nothing to install: this file belongs to Kemetra/Seshat-BI. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Kemetra/Seshat-BI/main/.claude/skills/retail-control-room/SKILL.mdgit 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/retail-control-room)<a href="https://agentmods.dev/skills/kemetra/seshat-bi/retail-control-room"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/retail-control-room/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/retail-control-room"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/retail-control-room.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 | $0.00168 | $0.01870 |
| Opus 5 | $0.00084 | $0.00935 |
| Sonnet 5 | $0.00034 | $0.00374 |
| Haiku 4.5 | $0.00017 | $0.00187 |
Grade A, and why
retail-control-room 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 11d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
retail-control-room
The per-table scorecard answers "where is THIS table"; the control room answers "where
is the WHOLE portfolio, and which table do I touch next". It is a read-only JOIN over
evidence that already exists per table -- the portfolio-level sibling of
readiness-scorecard.md. It introduces no new validator and no new gate (roadmap rule
8; Principle VIII); it aggregates and presents, then STOPS.
Scope boundary (read first)
- Aggregates, never re-derives. The only evidence shown is evidence already
committed:
seshat checkWARNs,retail validateERRORs (V-RC2/V-RC15/V-RC16), and the per-tabledata-issues.md/blocking-reasons.md/readiness-status.yamlrows. It runs NO new check. - Read-only. It never edits a per-table artifact, never clears a blocker, never
writes a
pass, never runs SQL, never opens a DB connection. Clearing a blocker stays a per-table action by its named owner (Principle V). - No fake confidence. Every line carries a MEASURED NUMBER as evidence (a row count, an orphan count, a penny delta, an open-blocker count, a finding-id) -- never an adjective, never a fabricated health score (roadmap rule #9). A numeric score is OPTIONAL and DEFERRED; the control room MUST NOT emit one.
- Every cell traces to a committed source. A number with no traceable source path (and row/line where applicable) is a defect.
- Generic. No worked-example specifics (billing codes, segments, PII column names, per-table grain keys). C086 is a filled instance cited as a reference, never baked in.
- ASCII only, UTF-8 no BOM.
Aggregates, never re-derives (the evidence chain)
Every cell traces back to an existing committed source -- a JOIN, not a measurement:
| Control-room column | Source it aggregates | Severity |
|---|---|---|
| static WARNs per table | recorded seshat check exit + WARN lines |
warning |
| live findings per table | recorded retail validate V-RC2/V-RC15/V-RC16 ERRORs |
error |
| data-quality issues | the table's data-issues.md rows |
as recorded |
| open blockers | the table's blocking-reasons.md "Open blockers" rows |
blocking |
| stage + status | the table's readiness-status.yaml (current_stage, per-stage status) |
the four statuses |
| next action | the table's readiness-status.yaml next_action |
-- |
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.
- 11d ago First seen · 128 lines · 168 tokens per session scan A f3109f894cc4
retail-control-room is a skill published in the GitHub repository Kemetra/Seshat-BI (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 168 tokens to every session and 1,870 once invoked, about $0.0008 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 2026-08-31.
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