AuC is a Python framework for running a single AI agent with an asynchronous, pluggable reasoning loop, language-model adapters, permission levels, and observable events. It is used to build coding and conversational agents with tools, security checks, web interfaces, background jobs, evaluations, and isolated execution. The catalogue entries are skills for extending its agent workflow.
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 ufy2024/AuC --skill finance-billing-opsgit clone --depth 1 https://github.com/ufy2024/AuCWrote 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/ufy2024/auc/finance-billing-ops)<a href="https://agentmods.dev/skills/ufy2024/auc/finance-billing-ops"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/finance-billing-ops.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 22 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00896 |
| Opus 5 | $0.00026 | $0.00448 |
| Sonnet 5 | $0.00011 | $0.00179 |
| Haiku 4.5 | $0.00005 | $0.00090 |
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 4d 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- finance-billing-ops — 94% identical, 29 lines differ
- finance-billing-ops — 94% identical, 29 lines differ
- finance-billing-ops — 92% identical, 28 lines differ
- finance-billing-ops — 92% identical, 28 lines differ
How it starts
The opening of the file, as written. The whole thing — 150 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.
- 4d ago First seen · 150 lines · 53 tokens per session scan A 7ac906a5703a
finance-billing-ops is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 53 tokens to every session and 896 once invoked, about $0.0003 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 2026-09-03.
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