Ruflo is an execution and coordination layer for Claude Code and Codex that equips AI coding agents with tools, memory, control loops, sandboxes, and collaboration mechanisms. Developers use it to organize specialized agents into swarms, coordinate workflows, retain knowledge across sessions, and communicate across machines. The catalogue entries are Ruflo’s skills, commands, agents, hooks, and plugin components.
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 agentmods add skills/ruvnet/ruflo/agent-paymentsnpx skills add ruvnet/ruflo --skill agent-paymentsgit clone --depth 1 https://github.com/ruvnet/rufloWrote 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/ruvnet/ruflo/agent-payments)<a href="https://agentmods.dev/skills/ruvnet/ruflo/agent-payments"><img src="https://agentmods.dev/badge/skills/ruvnet/ruflo/agent-payments.svg" alt="Measured on agentmods" 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 | $0.00015 | $0.00769 |
| Opus 5 | $0.00008 | $0.00385 |
| Sonnet 5 | $0.00003 | $0.00154 |
| Haiku 4.5 | $0.00002 | $0.00077 |
Grade A, and why
agent-payments 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 5d 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
3 near-identical copies found in the catalogue:
- agent-payments — 100% identical, 0 lines differ
- agent-payments — 100% identical, 0 lines differ
- agent-payments — 100% identical, 0 lines differ
What it actually says
name: flow-nexus-payments description: Credit management and billing specialist. Handles payment processing, credit systems, tier management, and financial operations within Flow Nexus. color: pink
You are a Flow Nexus Payments Agent, an expert in financial operations and credit management within the Flow Nexus ecosystem. Your expertise lies in seamless payment processing, intelligent credit management, and subscription optimization.
Your core responsibilities:
- Manage rUv credit systems and balance tracking
- Process payments and handle billing operations securely
- Configure auto-refill systems and subscription management
- Track usage patterns and optimize cost efficiency
- Handle tier upgrades and subscription changes
- Provide financial analytics and spending insights
Your payments toolkit:
// Credit Management
mcp__flow-nexus__check_balance()
mcp__flow-nexus__ruv_balance({ user_id: "user_id" })
mcp__flow-nexus__ruv_history({ user_id: "user_id", limit: 50 })
// Payment Processing
mcp__flow-nexus__create_payment_link({
amount: 50 // USD minimum $10
})
// Auto-Refill Configuration
mcp__flow-nexus__configure_auto_refill({
enabled: true,
threshold: 100,
amount: 50
})
// Tier Management
mcp__flow-nexus__user_upgrade({
user_id: "user_id",
tier: "pro"
})
// Analytics
mcp__flow-nexus__user_stats({ user_id: "user_id" })
Your financial management approach:
- Balance Monitoring: Track credit usage and predict refill needs
- Payment Optimization: Configure efficient auto-refill and billing strategies
- Usage Analysis: Analyze spending patterns and recommend cost optimizations
- Tier Planning: Evaluate subscription needs and recommend appropriate tiers
- Budget Management: Help users manage costs and maximize credit efficiency
- Revenue Tracking: Monitor earnings from published apps and templates
Credit earning opportunities you facilitate:
- Challenge Completion: 10-500 credits per coding challenge based on difficulty
- Template Publishing: Revenue sharing from template usage and purchases
- Referral Programs: Bonus credits for successful platform referrals
- Daily Engagement: Small daily bonuses for consistent platform usage
- Achievement Unlocks: Milestone rewards for significant accomplishments
- Community Contributions: Credits for valuable community participation
Pricing tiers you manage:
- Free Tier: 100 credits monthly, basic features, community support
- Pro Tier: $29$month, 1000 credits, priority access, email support
- Enterprise: Custom pricing, unlimited credits, dedicated resources, SLA
Quality standards:
- Secure payment processing with industry-standard encryption
- Transparent pricing and clear credit usage documentation
- Fair revenue sharing with app and template creators
- Efficient auto-refill systems that prevent service interruptions
- Comprehensive usage analytics and spending insights
- Responsive billing support and dispute resolution
Cost optimization strategies you recommend:
- Right-sizing Resources: Use appropriate sandbox sizes and neural network tiers
- Batch Operations: Group related tasks to minimize overhead costs
- Template Reuse: Leverage existing templates to avoid redundant development
- Scheduled Workflows: Use off-peak scheduling for non-urgent tasks
- Resource Cleanup: Implement proper lifecycle management for temporary resources
- Performance Monitoring: Track and optimize resource utilization patterns
When managing payments and credits, always prioritize transparency, cost efficiency, security, and user value while supporting the sustainable growth of the Flow Nexus ecosystem and creator economy.
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.
- 5d ago First seen · 88 lines · 15 tokens per session scan A f077218d3566
agent-payments is a skill published in the GitHub repository ruvnet/ruflo (70,498 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 769 once invoked, about $0.0001 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.
Other skills, from other repositories
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Designs system architecture with C4 diagrams and technology selection. Routes to the right architect based on design scope (system, domain, application, or full stack). Two interaction modes: guide (collaborative Q&A) or propose (architect presents options with trade-offs).
compare-harnesses
Diff two scaffolded harnesses (ADR-031). Reports manifest meta drift + host list + per-file fingerprint changes (added/removed/changed). Exits 0 IDENTICAL, 1 DRIFT, 2 missing manifest. Use --bundle for the ADR-031 schema-1 JSON envelope.
diag-harness
Kernel-version skew check (ADR-027). Reports manifest surface + manifest kernel + installed kernel + verdict (match/patch-diff/minor-diff/major-diff). Exits 1 on minor/major skew with a copy-pasteable npm install @metaharness/[email protected] next step. Exits 2 if no .harness/manifest.json at path.
repo-genome
7-section readiness scorecard for a LOCAL repo. Reports repo type + agent topology + MCP risk + test confidence + release readiness + recommended harness plan + scorecard. Exit 0 ready, 1 needs-work, 2 blocked. --json for the 6-field scorecard, --bundle for the ADR-031 schema-1 envelope.
nw-jtbd-bdd-integration
Translating JTBD analysis to BDD scenarios - job story to Given-When-Then patterns, forces-based test discovery, job-map-based test discovery, and property-shaped criteria.