inno-agent: An open-source personal learning agent with three-layer memory, a proactive scheduler, personal IM channels

by hhyqhh · Agent Tool · ★ 1.4k

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

How to install inno-agent

git clone https://github.com/hhyqhh/inno-agent.git

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

Security audit verdict: SAFE · quality 73/100

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.

clielectronlearning-agentllm-agentmemorypersonal-knowledge-managementpi-sdktypescript

Quick Facts

Stars1,372
Forks239
LanguageTypeScript
CategoryAgent Tool
LicenseMIT
Quality Score73/100
Open Issues9
Last Updated2026-11-04
Created2026-05-28
Platformscli, node
Est. Tokens~17k

About inno-agent

Inno Agent An open-source personal learning agent with a layered memory system, a proactive scheduler, multi-channel messaging, and a workspace-scoped Practice Lab — built on the Pi coding-agent SDK without modifying its kernel. 🌐 Homepage: https://hhyqhh.github.io/inno-agent-website/ - project overview, feature walkthrough, and live demos.

Compatible Skills

These tools work well together with inno-agent for enhanced workflows:

  • swarmvault — semantic(0.31)+complementary+same_lang+similar_pop+shared_platform (61%)
  • ChatCrystal — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)
  • llm-wiki-plugin — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (59%)
  • Kompl — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (58%)
  • MineEcho — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)

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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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