Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cynco-labs/ai-accounting-skills --skill smart-intakegit clone --depth 1 https://github.com/cynco-labs/ai-accounting-skillsWrote 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/cynco-labs/ai-accounting-skills/smart-intake)<a href="https://agentmods.dev/skills/cynco-labs/ai-accounting-skills/smart-intake"><img src="https://agentmods.dev/badge/skills/cynco-labs/ai-accounting-skills/smart-intake/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/cynco-labs/ai-accounting-skills/smart-intake"><img src="https://agentmods.dev/badge/skills/cynco-labs/ai-accounting-skills/smart-intake.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 | $0.00047 | $0.02062 |
| Opus 5.5 | $0.00019 | $0.00825 |
| Sonnet 5.5 | $0.00009 | $0.00412 |
| Haiku 4.5 | $0.00005 | $0.00206 |
Grade A, and why
smart-intake 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 2mo 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 — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/smart-intake
Purpose
Make folder-dump accounting feel seamless.
The user is not responsible for knowing MPERS, FYE, or form codes. We read the folder, normalize context, and ask only smart questions.
Load first
shared/runtime-brief.md(one screen — default)- Firm profile if present (defaults only — do not re-interview the firm)
- On demand:
shared/shelf-first.md·shared/smart-intake.md·shared/user-questions.md·shared/operator-lens.md
When called from full-engagement-pipeline, you are the intake half of one pass — do not re-run setup/source as separate ceremonies after this.
Operator + depth (write on state)
Resolve operator before or with soft-confirm (shared/operator-lens.md):
| Signal | operator |
|---|---|
| “my books / my company” · personal account · no firm profile | owner |
| “bookkeeper for …” | bookkeeper |
| Firm profile real + “the client” | firm |
| Unclear | one structured ask (counts toward ≤3) |
Default engagement_type on folder dump: bookkeeping_only (period on disk).
Classify depth (after extract)
Do not decide deep standards work during the first three questions.
After banks are extracted, set classify_depth when starting classify:
- year end / compilation / proper classifications →
standards_aware(shared/classify-substance.md) - just code / bookkeeping only →
bookkeeping
When to use
- User points at a folder / drops files and says do accounting / year end / books
- Company name, country, or FY not stated
- First contact for this client
If engagement_state.json already exists → use resume-engagement instead.
Workflow
Step 0 — Scope the ask (silent default)
Period truth first: whatever bank months exist → that is the books period. Work it deeply.
| User vibe | Default engagement_type | Say once |
|---|---|---|
| “Do the accounting / sort my books” / folder dump | bookkeeping_only for period on disk |
“I’ll fully book the months you gave (extract→TB→ledger). Full-year FS only if you want it and coverage is complete.” |
| Explicit “year end / prepare FS” + complete months | year_end |
Proceed toward FS after books |
| Explicit “year end” + partial months | bookkeeping_only + AMBER |
Finish available months; offer upgrade when more banks arrive — do not stall |
| “Tax only” | tax path later | — |
| “Just categorise” | bookkeeping_only | — |
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.
- 2mo ago First seen · 214 lines · 47 tokens per session scan A 01abbd3eb3ac
smart-intake is a skill published in the GitHub repository cynco-labs/ai-accounting-skills (4 stars, last pushed 3mo ago), licensed MIT. It adds 47 tokens to every session and 2,062 once invoked, about $0.0002 per session on Opus 5.5. 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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