Borrowing it
Nothing to install: this file belongs to audrey-560/bookkeeper-starter. 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/audrey-560/bookkeeper-starter/main/.claude/skills/bk-onboard/SKILL.mdgit clone --depth 1 https://github.com/audrey-560/bookkeeper-starterWrote 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/audrey-560/bookkeeper-starter/bk-onboard)<a href="https://agentmods.dev/skills/audrey-560/bookkeeper-starter/bk-onboard"><img src="https://agentmods.dev/badge/skills/audrey-560/bookkeeper-starter/bk-onboard/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/audrey-560/bookkeeper-starter/bk-onboard"><img src="https://agentmods.dev/badge/skills/audrey-560/bookkeeper-starter/bk-onboard.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 | $0.00074 | $0.01034 |
| Opus 5 | $0.00037 | $0.00517 |
| Sonnet 5 | $0.00015 | $0.00207 |
| Haiku 4.5 | $0.00007 | $0.00103 |
Grade A, and why
bk-onboard 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What This Skill Does
Interviews the user about a business's financial environment, then generates
clients/<slug>/ in the bookkeeper project: profile.json, secrets template,
customer registry, statement inbox with per-institution instructions, and (on
confirmation) a fresh Google Sheets ledger with COA + tabs initialized from the
jurisdiction pack. ~15 minutes of questions, then the system is ready for its
first /bk-import.
Context
cdto the project root first.- Reference shapes:
clients/sandbox-demo/profile.json(complete example),jurisdictions/*/pack.json(available packs),institutions/registry.json(supported institutions),docs/ONBOARDING.md(full question rationale). - The interview fills an answers JSON (same shape as profile.json + optional
seed_customers/opening_balances);tools/new_client.pydoes the generation.
The Interview (1–2 questions at a time, adapt to what they've already told you)
1. Entity & jurisdiction
- Legal/display name, entity type (corp / sole prop / partnership)
- Country + province/state → pick the
jurisdiction_pack(ca-onis production;us-federalandgeneric-vatare stubs — warn that a stub means their accountant must review tax treatment) - Fiscal year end (MM-DD), sales-tax registration + number + filing frequency, accountant (name + what they need: GIFI? plain statements?)
2. Money map — for EVERY account money moves through:
- Institution, account nickname, currency, kind (bank / card / processor)
- How data gets out: API (Wise), CSV download (which institution → check
institutions/registry.json; unlisted →generic_csvand capture a sample CSV to build the column mapping NOW, not later) - Statement cadence, opening balance + as-of date
- Assign GLs: banks 1010, 1015, 1020… / cards 2010, 2015… (unique, stable)
3. Revenue
- Do they invoice? → prefix, starting number, payment terms, remittance details (bank transfer blocks for each currency they bill in)
- Agencies/platforms that pay them (name, match substrings for deposit detection, commission %, gross-vs-net method)
- Seed customers: name, currency, domestic-or-foreign (drives sales-tax treatment)
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 · 83 lines · 74 tokens per session scan A 8230856b5a0e
bk-onboard is a skill published in the GitHub repository audrey-560/bookkeeper-starter (13 stars, last pushed 1mo ago), licensed MIT. It adds 74 tokens to every session and 1,034 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 2026-08-30.
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