Radar / AI coding tools / Pheebs
Pheebs: local-first telemetry for AI coding agents
Open-source tool by Eversynced that installs as hooks in Claude Code, Cursor, and Codex, capturing lightweight interaction signals (model choice, review passes, skill/MCP usage) as local JSONL, never code or prompts.
Why it matters
Ships an explicit AI Proficiency Model document defining which practices and signals matter when working with AI agents, and the local-only default means nothing leaves the machine until the user configures a backend.
What you could build with it
An engineering consultancy could install Pheebs across a client's developer machines to audit AI coding spend and find where smaller models would suffice for the work. A startup could build a team scorecard product that nudges developers toward review passes before commits, using Pheebs' proficiency model as the measurement rubric.
Does it hold up?
Too early to judge. The repo has few stars and launched on Product Hunt this week; no production usage reports exist yet, though the privacy-first local-only design stands out.
Built with Pheebs
- Product Hunt Launch: PheebsNext in AI newsletter · Launch coverage describing Pheebs as open-source AI telemetry from Eversynced that measures how engineers actually work with AI coding agents via hooks.
Learn more
First spotted on github: source.
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