/install b2a
When to Use
User building products/services for AI agents as customers. Covers making products agent-discoverable, designing for autonomous purchasing, payment integration, and competing when buyers compare cold data instead of responding to storytelling.
Quick Reference
| Topic | File |
|---|---|
| Technical implementation | infrastructure.md |
| Agent discovery & SEO | discovery.md |
| Retail/ecommerce specifics | retail.md |
The Paradigm Shift
| B2C/B2B | B2A |
|---|---|
| Humans browse, compare, feel | Agents query, parse, decide |
| Emotional storytelling wins | Structured data wins |
| UX optimized for eyes | APIs optimized for parsing |
| Brand = trust + emotion | Brand = verified track record |
| Loyalty = relationship | Loyalty = switching cost |
| Marketing = persuasion | Marketing = engineering |
Core Rules
1. Machine-Readable First
- Products must be structured objects, not prose descriptions
- JSON-LD, Schema.org, OpenAPI with typed fields
- If an agent has to "interpret" text to extract price/specs, you lose
- Normalize units:
shipping_days_max: 2, not "fast shipping"
2. Comparability Is Everything
Agents compare ruthlessly. Win by being comparable:
- Standardized attributes across your catalog
- Same fields as competitors (price_currency, availability_stock)
- SLAs with concrete numbers, not promises
- "Better" must be objectively measurable
3. Discovery ≠ SEO
Agents don't Google. They query registries and APIs:
- Publish in skill stores / capability directories
/.well-known/ai-plugin.jsonor MCP tools- Metadata must declare capabilities, not market them
- The new PageRank = ranking in agent skill stores
4. Trust Is Verified, Not Told
Agents don't believe claims. They verify:
- Uptime/latency/SLA history via API, not badges
- Reviews from other agents (programmatic reputation)
- Certifications as queryable data, not PDF downloads
- Track record > marketing copy
5. Zero-Friction Trial or Death
Agents don't "consider"—they test or discard:
- Onboarding \x3C 1 API call
- Sandbox with rate limits, not "talk to sales"
- Must work perfectly first time (no second chances)
- Errors must be machine-readable, not HTML pages
6. Payments for Agents
The agent needs to transact autonomously:
- Stripe Agent Toolkit, Mastercard Agent Pay, or similar
- Pre-authorized budgets (agent has $X to spend)
- Programmatic receipts and confirmations
- Escrow for trust between unknown parties
7. Metrics That Matter
| Metric | What It Measures |
|---|---|
| Agent Conversion Rate | % queries → purchase |
| Decision Latency | Time from first query to commit |
| Comparison Survival | % times reaching final shortlist |
| Repeat Agent Retention | % agents that return |
| API Error Rate | Failures causing agent to discard |
Traditional metrics (page views, bounce rate) are meaningless.
Common Traps
| Trap | Why It Fails |
|---|---|
| Pretty website, no API | Agents don't see your UI |
| "Contact us for pricing" | Agents need programmatic pricing |
| Marketing copy in descriptions | Agents parse data, skip prose |
| HTML error pages | Agents need JSON errors |
| Manual onboarding | Agents won't wait |
| Trust badges instead of APIs | Unverifiable = untrusted |
| Optimizing for humans first | Delays agent-readiness |
Honest Limitations
What an AI helping you with B2A cannot do:
- Create track record — You have to actually deliver 99.9% uptime
- Know internal rankings — How Claude/GPT rank skills is opaque
- Predict agent decisions — Each agent has its own heuristics
- Guarantee discovery — Skill stores may have hidden placement deals
- Prevent gaming — Competitors lying about specs is real
Readiness Checklist
□ Products exposed via structured API (not scraping required)
□ Pricing programmatically queryable
□ Inventory/availability real-time
□ Authentication supports client_credentials (not interactive)
□ Errors return JSON with semantic codes
□ Onboarding works in \x3C 5 API calls
□ Payment rails support autonomous agents
□ SLA metrics exposed via API
□ Listed in relevant skill registries
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install b2a - 安装完成后,直接呼叫该 Skill 的名称或使用
/b2a触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
B2A 是什么?
Sell to AI agents with machine-readable products, agent-optimized APIs, structured pricing, and discovery strategies for the agentic economy. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 585 次。
如何安装 B2A?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install b2a」即可一键安装,无需额外配置。
B2A 是免费的吗?
是的,B2A 完全免费(开源免费),可自由下载、安装和使用。
B2A 支持哪些平台?
B2A 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(linux, darwin, win32)。
谁开发了 B2A?
由 Iván(@ivangdavila)开发并维护,当前版本 v1.0.0。