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-discover-portfolio/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-discover-portfolio)<a href="https://agentmods.dev/skills/kemetra/seshat-bi/retail-discover-portfolio"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/retail-discover-portfolio/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-discover-portfolio"><img src="https://agentmods.dev/badge/skills/kemetra/seshat-bi/retail-discover-portfolio.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 | $0.00086 | $0.01371 |
| Opus 5 | $0.00043 | $0.00685 |
| Sonnet 5 | $0.00017 | $0.00274 |
| Haiku 4.5 | $0.00009 | $0.00137 |
Grade A, and why
retail-discover-portfolio 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 12d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
retail-discover-portfolio
Use this skill when the owner has an unfamiliar database schema or file folder and needs a governed route from portfolio discovery to the business interview.
Boundary
This is an agent-conducted flow, not a new state engine or CLI workflow:
portfolio discovery -> domain -> scope -> selected-table onboarding -> interview handoff -> STOP
- Layer A is the metadata-only portfolio survey in templates/portfolio-survey.md.
- Layer B is the existing value-backed, per-table Source Ready profile owned by retail-onboard-table.
- Never create a second profiler or author mappings//source-profile.md here.
- Never select a scale-out route. Record scale evidence for the existing silver_gold_model_planning boundary to decide later.
- Read the existing stage contracts and committed artifacts to derive exactly one next action. Create no run-state, projection, or routing file.
The golden reference shapes are:
- tests/fixtures/portfolio-survey/db-schema/survey.md
- tests/fixtures/portfolio-survey/file-folder/survey.md
1. Produce the Layer-A survey
For a database schema:
- Call seshat.portfolio_enumerate.enumerate_tables(schema). This helper is the only DB table-enumeration path. Do not issue a raw information_schema.tables query, and do not catch raw config, driver, or connection exceptions.
- If it returns an error, show only that redacted error. If no metadata is readable, STOP and name the unblock: configure the gitignored .env, install the matching retail DB extra, or grant metadata permission.
- For every returned table, read information_schema.columns plus declared PK/FK and catalog-estimate metadata through the same read-only boundary.
For a file folder, list every reachable CSV and Excel file and inspect only format/schema metadata. Do not read source values.
Fill one committed survey from templates/portfolio-survey.md:
- include every reachable table; never choose a table-count or time cap;
- include declared types, declared PK/FK metadata, catalog row estimates, and name/type-based date, PII-suspicion, grain, and structural-role hints;
- label every inference candidate/hint, never a ruling;
- for unavailable metadata, record [PENDING LIVE PROFILE] or needs_sample, the exact reason, and the enabling step;
- never measure uniqueness, missingness, date spans, or returns population;
- never include raw or masked samples, suspected-PII values, credentials, DSNs, or connection strings.
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.
- 12d ago First seen · 142 lines · 86 tokens per session scan A 065d3d002ace
retail-discover-portfolio is a skill published in the GitHub repository Kemetra/Seshat-BI (2 stars, last pushed 3d ago), licensed Apache-2.0. It adds 86 tokens to every session and 1,371 once invoked, about $0.0004 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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