How do I install the Basecred skill?

Run npx skillmds@latest add kbarbel640-del/basecred in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Basecred safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Basecred?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Basecred free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Basecred?

kbarbel640-del (@kbarbel640-del) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Basecred by kbarbel640-del — Agent Skill

Name: Basecred
Rating: 4.5 (4 reviews)
Author: kbarbel640-del

Basecred

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.

kbarbel640-del Updated Sep 8, 2026 1 repo stars

File contents

BaseCred — Onchain Reputation Queries

Prerequisites

Package installed in workspace: npm i basecred-sdk

API keys in workspace .env:

TALENT_PROTOCOL_API_KEY=<key>
NEYNAR_API_KEY=<key>          # optional — enables Farcaster scoring

Ethos Network requires no key.

Quick workflow

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.
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.

Frequently asked questions