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.
git clone --depth 1 https://github.com/CPUtester5465/countbean-pluginWrote 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/commands/cputester5465/countbean-plugin/status)<a href="https://agentmods.dev/commands/cputester5465/countbean-plugin/status"><img src="https://agentmods.dev/badge/commands/cputester5465/countbean-plugin/status/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/commands/cputester5465/countbean-plugin/status"><img src="https://agentmods.dev/badge/commands/cputester5465/countbean-plugin/status.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 | $0.00022 | $0.00142 |
| Opus 5.5 | $0.00009 | $0.00057 |
| Sonnet 5.5 | $0.00004 | $0.00028 |
| Haiku 4.5 | $0.00002 | $0.00014 |
Grade A, and why
status 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 1mo 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.
What it actually says
Call the book_status tool and present the result to the user clearly: book name and location,
operating currency, number of accounts, net worth (assets + liabilities), net income, and the
list of recent commits. If no book exists yet, tell them to run /countbean:init.
If the user asked a specific question in $ARGUMENTS (e.g. "how much did I spend on food?"),
answer it by calling run_query or balances with an appropriate BQL filter rather than only
showing the summary.
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.
- 1mo ago First seen · 12 lines · 22 tokens per session scan A 5e61028b63dd
status is a command published in the GitHub repository CPUtester5465/countbean-plugin (34 stars, last pushed 18d ago), licensed MIT. It adds 22 tokens to every session and 142 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
audit
Scan for non-kernel money math. Rebuild critical flows as JournalEntrys. Replay and prove. Complements /ledger-verify.
reconcile
Assumptions → Money.from → cited, balanced JournalEntry → Ledger.apply. Output entries + proof.
review
Kernel first (/ledger-verify or /ledger-audit), then host TDD/review/security if present. See skills/ledger-review/SKILL.md.
sim
Seeded scenario on the kernel. Log assumptions. Prove equation. Replay with the same seed must match.
setup
An interactive setup wizard for configuring a Japanese tax accountant's office. It asks about the firm, clients, accounting software, expense rules, overseas services, invoices, payroll, and report sharing.
classify
A command that classifies one Japanese business transaction into an accounting category and tax type. It checks exclusions, past corrections, known keywords, and uses AI when needed.