readwise-skills: Agent skills for your Readwise and Reader data, powered by the Readwise MCP server/CLI

by readwiseio · MCP Server · ★ 308

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install readwise-skills

npx skills add readwiseio/readwise-skills
/plugin marketplace add readwiseio/readwise-skills

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 68/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars308
Forks11
LanguagePython
CategoryMCP Server
Quality Score68/100
Open Issues5
Last Updated2026-06-19
Created2026-02-28
Platformscli, mcp, python
Est. Tokens~7k

About readwise-skills

Installation Prerequisite: first, make sure you have the Readwise MCP server or CLI installed (whichever you prefer!) If you're using an AI agent, you can probably just tell your agent to install the skills from this repo and let it do the work: If that doesn't work: npx skills (recommended) is a very easy way to install these skills; it will set them to work with any LLM app you might use...

Compatible Skills

These tools work well together with readwise-skills for enhanced workflows:

  • speaker — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)
  • data2story-skill — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (56%)
  • papr — semantic(0.29)+complementary+similar_pop+shared_platform (50%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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