An onboarding skill for the Seshat BI Compass-Driven kit, a toolkit for analyzing data tables. It sets up the project and guides a new user toward a first visible result using their own table.

Use it when setting up Seshat, initializing the kit, or helping someone get started with their first table analysis.

It removes the uncertainty of starting a newly installed data-analysis toolkit. It creates the needed setup and routes the user through the appropriate onboarding steps.

How Kemetra/Seshat-BI configures Claude Code

Reuse

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.

Copy the file

curl -O https://raw.githubusercontent.com/Kemetra/Seshat-BI/main/.claude/skills/retail-init/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/Kemetra/Seshat-BI

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/kemetra/seshat-bi/retail-init/github.svg)](https://agentmods.dev/skills/kemetra/seshat-bi/retail-init)

Your own site

<a href="https://agentmods.dev/skills/kemetra/seshat-bi/retail-init"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/retail-init/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/kemetra/seshat-bi/retail-init"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/retail-init.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 193 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,448 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00193	$0.01448
Opus 5	$0.00097	$0.00724
Sonnet 5	$0.00039	$0.00290
Haiku 4.5	$0.00019	$0.00145

Measured 9d ago against content hash 00c15c167bfe, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

retail-init 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.

.claude/skills/retail-init/SKILL.md · 96 lines

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-init

The install-time front door for the Compass-Driven kit. Its one job is to turn a fresh pip install into a first visible result on the user's own table — leading with analyst value, keeping the substrate backstage. You (the agent) perform this flow; the retail init CLI only writes substrate and prints the next step. This is Phase-1 Step 1-2 of docs/roadmap/distribution-ideas.md.

Scope + non-negotiables (read first)

Agent-first, not a wizard (Principle I). The retail init CLI is substrate-writing ONLY — it writes .seshat/ + the fenced regions and prints the next step. It never prompts, shows a menu, or emits a profile. The delegate → route → profile flow is YOU performing this skill over the existing prose verbs.
Delegate, never fork (anti-fork). The worked-example offer, the human-seam list, and the single-table orientation card belong to first-hour-compass — its single source. The Stage-1 profile belongs to retail-onboard-table. Do NOT restate any of them here; route into them.
No run-state (FR-005). compass.yaml declares the orientation protocol and points at per-table readiness-status.yaml; it stores no current_stage. There is no repo-level stage.
Fence-only writes (FR-006/FR-007). The substrate write touches only the … region of AGENTS.md / CLAUDE.md; everything outside is hand-authored / constitution-owned and stays byte-identical.
Stop at judgment (Principle V). Grain, PII publish-safety, business rollup/segment, product identity are the human's — surfaced (via first-hour-compass) and STOPPED on, never self-granted.
ASCII only, UTF-8 no BOM.

The flow (what you perform)

Bootstrap the substrate. Run retail init (or retail init --repo <path>). It writes .seshat/compass.yaml + manifests and projects the SESHAT-KIT fenced regions of AGENTS.md / CLAUDE.md, then prints the next step. Do NOT narrate the substrate as steps — it is backstage.
Set expectations honestly (FR-009). State up front: the agent handles the sequence and the plumbing; you still own the judgment seams. Surface the seam wording from first-hour-compass (its single source) — do not re-type a divergent list.
Delegate the worked-example offer. Route into first-hour-compass, which presents retail-store-sales (full seven-stage spine, docs/worked-examples/ retail-store-sales.md) and takes the user's pick as a narrative pattern to steer by (not a file template).
Route into the profile. Hand the user's named table to retail-onboard-table (the Source → Mapping front door, which owns the Stage-1 read-only profile). The agent-visible first result is the grain candidates + column types it returns.
Degrade honestly when there's no DB. The Stage-1 profile is DB-backed (profile.py over a QueryRunner). If no db extra / DSN is configured, report the boundary and the enable steps (pipx inject seshat-bi psycopg2-binary or pip install "seshat-bi[db]"; set DATABASE_URL or ANALYTICS_DB_* in the gitignored .env), mark profile numbers [PENDING LIVE PROFILE], author the source-map / orientation structure, and STAY USEFUL — never traceback, never fake a pass. There is no CSV/Excel profiler (YAGNI).

Read the full file on GitHub · 96 lines

Changes

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 · 193 tokens per session scan A 00c15c167bfe

Subscribe to this mod's changes

retail-init is a skill published in the GitHub repository Kemetra/Seshat-BI (2 stars, last pushed 6d ago), licensed Apache-2.0. It adds 193 tokens to every session and 1,448 once invoked, about $0.0010 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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