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-validate/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-validate)<a href="https://agentmods.dev/skills/kemetra/seshat-bi/retail-validate"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/retail-validate/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-validate"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/retail-validate.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 | $0.00112 | $0.01272 |
| Opus 5 | $0.00056 | $0.00636 |
| Sonnet 5 | $0.00022 | $0.00254 |
| Haiku 4.5 | $0.00011 | $0.00127 |
Grade A, and why
retail-validate 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 9d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
retail-validate
seshat check proves everything provable from committed text. retail validate
proves the four things only a running database can show, on the MATERIALIZED rows
(constitution Principle VIII). This skill runs it and
maps each finding to the one place to fix it -- the live sibling of
retail-govern.
Scope boundary (read first)
Invoke-and-interpret only. This skill runs the live checks and explains findings; it does NOT write or fix silver/gold SQL, does NOT call pbi-cli, and does NOT auto-loop. The live run needs a DB and is the user's call; you report and stop.
Prerequisites
- silver + gold are materialized for the table.
- A reviewed
mappings/<table>/source-map.yamlexists (the targets are derived from it -- table, PK, FK, measures). - The optional
dbextra is installed (pipx inject seshat-bi psycopg2-binary, orpip install "seshat-bi[db]") and a DSN is configured (DATABASE_URLor theANALYTICS_DB_*vars in the gitignored.env). Never commit a real DSN.
Run it
retail validate --source-map mappings/<table>/source-map.yaml
The connection is host-agnostic (any Postgres: local / remote / DigitalOcean / other) and READ-ONLY (the session is opened read-only; the checks only SELECT). Exit is non-zero iff any check finds a defect.
Read a finding
Each is a Finding(rule_id, severity, message, locator). Live findings are
ERROR (proven defects -- a real PK duplicate, a real orphan, a real penny
mismatch), unlike the static rules' WARNING (suspect patterns). Start at the
locator; the id tells you which fix applies.
Finding id -> meaning -> where to fix
| Finding | Means | Fix at |
|---|---|---|
V-RC2 |
PK not unique, or has a NULL, on the materialized silver table (RC2). | Fix the grain or dedup in the silver SQL; re-verify the map's PK on the TRANSFORMED output (landed uniqueness is not enough). |
V-RC15 |
The date dimension does not span every fact date -- the calendar has gaps (RC15 coverage; the live half of static rule S7). |
Widen the generate_series bounds in the date-dim build to cover min..max fact date. |
V-RC16 (orphan) |
A fact FK points outside its dimension (RC16; 0 orphans required). | Fix the FK COALESCE to the -1 unknown member, or fix the dimension load so the key exists. |
V-RC16 (reconcile) |
A measure total differs between silver and gold (RC16; must reconcile to the penny). | Fix the gold aggregation (a join fan-out or filter is dropping/duplicating rows) until silver and gold totals match exactly. |
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.
- 9d ago First seen · 96 lines · 112 tokens per session scan A a1bf65f3d3a2
retail-validate is a skill published in the GitHub repository Kemetra/Seshat-BI (2 stars, last pushed 7d ago), licensed Apache-2.0. It adds 112 tokens to every session and 1,272 once invoked, about $0.0006 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.
Other skills, from other repositories
postgres
Query and manage PostgreSQL databases -- run SQL, inspect schemas, manage tables, and perform database administration.
sl
Skill "sl" from Kaelio/ktx, covering semantic layer, part 1 - schema reference, overlay sources, standalone table sources and standalone sql sources.
historic_sql_patterns
Identify recurring cross-table historic-SQL analytical intents from a bounded pattern shard and emit typed pattern evidence for deterministic wiki projection.
historic_sql_table_digest
Convert one changed historic-SQL table usage bucket into typed table usage evidence for deterministic schema projection.
live_database_ingest
Capture semantic-layer and knowledge updates from a live database schema snapshot.
ktx
Installs and configures ktx, the open-source context layer for data agents — runs ktx setup non-interactively with hidden CLI flags, configures database connections and embeddings, installs agent integration, and verifies readiness. Use when the user asks an agent to add ktx to a project, connect data sources, install…