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Agent Skill · 研究检索

b2a(乙二甲)

b2a 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

b2a 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 7,793。

总安装 18,034周安装 759GitHub Stars 2下载 6,315核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:b2a(乙二甲)
来源仓库:https://github.com/ivangdavila/b2a
安装命令:
openclaw skills install b2a
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install b2a

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

通过机器可读的产品、代理优化的 API、结构化定价和代理经济的发现策略向AI Agent销售。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install b2a;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

b2a 怎么安装?

在终端执行 openclaw skills install b2a。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

b2a 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

b2a 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

b2a 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

b2a 用的人多吗?

公开数据是累计安装 18,034 次,近一周安装 759 次,下载 6,315 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

b2a 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
b2a

乙二甲 · 本页

18,0342调用外部服务MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
B2A
slug
b2a
version
1.0.0
description
Sell to AI agents with machine-readable products, agent-optimized APIs, structured pricing, and discovery strategies for the agentic economy.
metadata
{"clawdbot":{"emoji":"🤖","requires":{"bins":[]},"os":["linux","darwin","win32"]}}

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

TopicFile
Technical implementationinfrastructure.md
Agent discovery & SEOdiscovery.md
Retail/ecommerce specificsretail.md

The Paradigm Shift

B2C/B2BB2A
Humans browse, compare, feelAgents query, parse, decide
Emotional storytelling winsStructured data wins
UX optimized for eyesAPIs optimized for parsing
Brand = trust + emotionBrand = verified track record
Loyalty = relationshipLoyalty = switching cost
Marketing = persuasionMarketing = 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.json or 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 < 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

MetricWhat It Measures
Agent Conversion Rate% queries → purchase
Decision LatencyTime from first query to commit
Comparison Survival% times reaching final shortlist
Repeat Agent Retention% agents that return
API Error RateFailures causing agent to discard

Traditional metrics (page views, bounce rate) are meaningless.

Common Traps

TrapWhy It Fails
Pretty website, no APIAgents don't see your UI
"Contact us for pricing"Agents need programmatic pricing
Marketing copy in descriptionsAgents parse data, skip prose
HTML error pagesAgents need JSON errors
Manual onboardingAgents won't wait
Trust badges instead of APIsUnverifiable = untrusted
Optimizing for humans firstDelays 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 < 5 API calls
□ Payment rails support autonomous agents
□ SLA metrics exposed via API
□ Listed in relevant skill registries

平台分布

OpenClaw

70.28%
按下载量换算4,438

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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