No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by pulseaiclub · MCP Server · ★ 465
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is phi safe to install? View the security audit →
English | 中文 A lean, high-performance terminal coding agent harness in Go — a sibling to Pi. Docs: pulseaiclub.github.io Fast and small — 15 MB release binary, 21 MB idle RSS, 31 ms to first frame; no Node / Electron / Python runtime Sub-agents — spawn isolated jobs and watch the full run unfold in the TUI / job logs, without stuffing every tu
| Stars | 465 |
| Forks | 17 |
| Language | Go |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68.430783887529/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-20 |
| Created | 2026-08-03 |
| Platforms | claude-code, cli, codex, go, mcp |
| Est. Tokens | ~21k |
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phi is a coding agent, rpc plugin, sub-agents, hashline edits, and mcp. It is categorized as a MCP Server with 465 GitHub stars.
phi is primarily written in Go. It covers topics such as ai, ai-agent, claude.
You can find installation instructions and usage details in the phi GitHub repository at github.com/pulseaiclub/phi. The project has 465 stars and 17 forks, indicating an active community.
phi is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to phi on Agent Skills Hub include agent-deck, codemap, hcom. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: