pi_agent_rust: High-performance AI coding agent CLI written in Rust with zero unsafe code

by Dicklesworthstone · Agent Tool · ★ 2.0k

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

How to install pi_agent_rust

git clone https://github.com/Dicklesworthstone/pi_agent_rust.git

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

Security audit verdict: SAFE · quality 69/100

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.

ai-agentsclideveloper-toolsrust

Quick Facts

Stars1,962
Forks231
LanguageRust
CategoryAgent Tool
Quality Score69/100
Open Issues12
Last Updated2026-11-05
Created2026-02-02
Platformscli, rust
Est. Tokens~34k

About pi_agent_rust

piagentrust piagentrust - Native AI coding agent CLI written in Rust Why Should You Care? • TL;DR • Methodology • Quick Start • Features • Installation • Commands • Configuration The Problem You want an AI coding assistant in your terminal, but existing tools are: Slow to start: Managed runtimes can add noticeable startup overhead Resource intensive: Electron apps or heavy runtimes can add...

Compatible Skills

These tools work well together with pi_agent_rust for enhanced workflows:

  • umadev — semantic(0.32)+complementary+same_lang+similar_pop+shared_platform (61%)
  • claude-code-api-rs — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)
  • librefang — semantic(0.26)+complementary+same_lang+similar_pop+shared_platform (59%)
  • rust-mcp-sdk — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)

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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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