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 unrealandychan/clean-code-skill --skill finance-billing-opsgit clone --depth 1 https://github.com/unrealandychan/clean-code-skillWrote 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/unrealandychan/clean-code-skill/finance-billing-ops)<a href="https://agentmods.dev/skills/unrealandychan/clean-code-skill/finance-billing-ops"><img src="https://agentmods.dev/badge/skills/unrealandychan/clean-code-skill/finance-billing-ops/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/unrealandychan/clean-code-skill/finance-billing-ops"><img src="https://agentmods.dev/badge/skills/unrealandychan/clean-code-skill/finance-billing-ops.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 | $0.00053 | $0.00792 |
| Opus 5.5 | $0.00021 | $0.00317 |
| Sonnet 5.5 | $0.00011 | $0.00158 |
| Haiku 4.5 | $0.00005 | $0.00079 |
Grade A, and why
finance-billing-ops 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.
This is a copy
94% identical to finance-billing-ops — 29 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Finance Billing Ops
Use this when the user wants to understand money, pricing, refunds, team-seat logic, or whether the product actually behaves the way the website and sales copy imply.
This is broader than customer-billing-ops. That skill is for customer remediation. This skill is for operator truth: revenue state, pricing decisions, team billing, and code-backed billing behavior.
Skill Stack
Pull these ECC-native skills into the workflow when relevant:
customer-billing-opsfor customer-specific remediation and follow-upresearch-opswhen competitor pricing or current market evidence mattersmarket-researchwhen the answer should end in a pricing recommendationgithub-opswhen the billing truth depends on code, backlog, or release state in sibling reposverification-loopwhen the answer depends on proving checkout, seat handling, or entitlement behavior
When to Use
- user asks for Stripe sales, refunds, MRR, or recent customer activity
- user asks whether team billing, per-seat billing, or quota stacking is real in code
- user wants competitor pricing comparisons or pricing-model benchmarks
- the question mixes revenue facts with product implementation truth
Guardrails
- distinguish live data from saved snapshots
- separate:
- revenue fact
- customer impact
- code-backed product truth
- recommendation
- do not say "per seat" unless the actual entitlement path enforces it
- do not assume duplicate subscriptions imply duplicate value
Workflow
1. Start from the freshest billing evidence
Prefer live billing data. If the data is not live, state the snapshot timestamp explicitly.
Normalize the picture:
- paid sales
- active subscriptions
- failed or incomplete checkouts
- refunds
- disputes
- duplicate subscriptions
2. Separate customer incidents from product truth
If the question is customer-specific, classify first:
- duplicate checkout
- real team intent
- broken self-serve controls
- unmet product value
- failed payment or incomplete setup
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 · 129 lines · 53 tokens per session scan A 823a1b8f7549
finance-billing-ops is a skill published in the GitHub repository unrealandychan/clean-code-skill (12 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 792 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to finance-billing-ops, differing in 29 lines, and is treated as a copy.
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