什么是 BaseCred 链上信誉？

BaseCred 是 Openclaw Skills 库的重要组成部分，旨在弥合原始区块链数据与可操作信誉洞察之间的鸿沟。它允许开发者和 AI 代理查询特定的 0x 地址，并接收涵盖可信度、专业构建者评分和社交质量信号的多维概况。通过集成 BaseCred SDK，该技能简化了在去中心化环境中评估信任的过程。

该技能对于需要身份验证、人才招聘或风险评估的应用特别有价值。它将复杂数据合成为易读格式，确保 Openclaw Skills 用户能够快速了解任何链上实体的社交和专业地位。

下载入口:https://github.com/openclaw/skills/tree/main/skills/callmedas69/basecred

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

BaseCred 链上信誉 应用场景

• 评估去中心化金融 (DeFi) 参与者的信誉。
• 根据 Talent Protocol 构建者评分审查开发者或创作者。
• 按账户质量和社交情感过滤 Farcaster 用户。
• 监控钱包活跃度以区分活跃贡献者和休眠账户。

1. AI 代理从指定工作区执行 BaseCred 查询脚本。
2. SDK 从 Ethos Network、Talent Protocol 和 Farcaster API 获取信誉数据。
3. 系统将原始数值评分内部映射到标准化的等级表。
4. 应用活跃度逻辑将概况标记为近期活跃、陈旧或休眠。
5. 展示包含统一评分、评论情感和验证状态的最终 JSON 对象。

BaseCred 链上信誉 配置指南

要将其集成到您的 Openclaw Skills 工作区，请遵循以下步骤：

1. 安装所需的 SDK：

npm i basecred-sdk

2. 将您的 API 凭据添加到 .env 文件：

TALENT_PROTOCOL_API_KEY=your_key_here
NEYNAR_API_KEY=your_key_here

3. 运行测试查询以确保连接正常：

node path/to/skills/basecred/scripts/query.mjs <0x-address>

BaseCred 链上信誉 数据架构与分类体系

name: basecred
description: Fetch onchain reputation profiles via BaseCred SDK (Ethos, Talent Protocol, Farcaster/Neynar). Use when the user wants to check wallet reputation, builder score, creator score, Ethos credibility, or Farcaster account quality for any 0x address. Supports multi-source unified profiles with level derivation and recency tracking.

BaseCred — Onchain Reputation Queries

Prerequisites

1. Package installed in workspace: npm i basecred-sdk
2. API keys in workspace .env:

   TALENT_PROTOCOL_API_KEY=
   NEYNAR_API_KEY=          # optional — enables Farcaster scoring
   

   Ethos Network requires no key.

Quick workflow

1. Run the query script from the workspace:

   node /path/to/skills/basecred/scripts/query.mjs <0x-address>
   

   The script auto-locates node_modules/basecred-sdk and .env by walking up from cwd. Run it with cwd set to the workspace.

2. Parse the JSON output and present results to the user. Use the level tables in references/output-schema.md to translate raw scores into human-readable levels.

Presenting results

Summarize the three facets clearly:

• Ethos — score + credibility level + review sentiment + vouches. Flag hasNegativeReviews if true.
• Talent Protocol — builder score/level + creator score/level. Note verified status.
• Farcaster — quality score (0–1) and whether it passes threshold.
• Recency — recent / stale / dormant. Mention if stale or dormant as a caveat.

Highlight actionable signals: e.g. zero vouches on Ethos is an easy win, or a dormant Talent score that needs activity.

Reference

• Output schema + all level tables: references/output-schema.md — read when you need to map scores → levels or explain the shape of a response.