What gets captured, how it's measured, and what it means for your career. This is the complete guide to every metric, score, and signal UseAI produces.
Every time you work with an AI tool, UseAI silently records the full prompt lifecycle — from the first message to the final evaluation. No manual logging, no forms to fill out, no context switching. The background daemon captures everything.
useai_startSession begins when your AI tool sends the first message. Tool, task type, and project are recorded automatically.
useai_heartbeatHeartbeats keep the session alive during long prompts, tracking active time intervals for accurate clock time calculation.
useai_endSession closes with a full evaluation, Ed25519 signature, and hash chain entry. Any change from this point forward breaks the signature.
Features shipped. Bugs fixed. Refactors completed. Tests written. Every milestone you complete is categorized by type and weighted by complexity — because a complex architecture overhaul is not the same as a quick typo fix.
Complexity weights: simple ×1 · medium ×2 · complex ×4. Your output fingerprint shows what kind of developer you really are.
New functionality shipped
Defect identified and resolved
Structural improvement, same behavior
Test coverage added or improved
Documentation written or updated
Project scaffolding or tooling
Released to production
Miscellaneous development work
Are you mostly debugging or mostly building? UseAI breaks down your AI time by task type, giving you real numbers for how AI fits into your workflow — daily, weekly, and monthly.
Active session time is measured via heartbeats, not wall clock. If you step away for coffee, that gap isn't counted. You see real time spent with AI, not calendar time.
Building new features and writing implementation code
Investigating and fixing bugs, tracing error paths
Writing and running tests, verifying behavior
Architecture decisions, task breakdown, scoping
Code review, PR feedback, quality checks
Writing docs, READMEs, inline comments
Exploring new tools, libraries, or concepts
At the end of every prompt, the AI evaluates how effectively you used it across four dimensions. Each dimension is scored 1–5, and for any score below 5, the AI provides a concrete, actionable reason explaining what was missing and how to improve next time.
These scores feed into your APS and public profile — they're not just feedback, they're the foundation of your AI proficiency signal.
How clear, specific, and well-structured your prompts are. High scores mean the AI rarely needs clarification and can act on your instructions immediately.
How much relevant context you give the AI upfront — file references, constraints, background. Better context means fewer round-trips and more accurate output.
How well-scoped your tasks are. A focused, single-responsibility prompt scores higher than a vague or overly broad request that tries to do too much at once.
How autonomously the AI can work from your instructions. High independence means you gave enough direction for the AI to execute without constant hand-holding.
The APS is a composite 0–1000 score that aggregates your performance across multiple sessions. It combines five components, each normalized to 0–1 and weighted to produce a holistic measure of AI-assisted development proficiency.
APS captures your entire body of work — rewarding consistency, breadth of skills, and sustained output over time.
Complexity-weighted milestones completed in the window
Complexity weight per hour of AI session time
Average prompt quality, context, and scope scores
Active days ratio, streak, and session frequency
Unique languages, AI tools, and tool leverage score
GitHub shows your commits. UseAI shows what you built with AI and how effectively you wield it. A public, shareable profile displaying your tools, languages, output volume, complexity distribution, and proficiency scores — your AI development resume.
In a world where every developer “uses AI,” prove you don't just use it — you're proficient with it.
A shareable page showing your AI activity — tools, languages, output volume, complexity, and proficiency scores. Only aggregate stats are shown — no titles, project names, or code.
See where you stand globally. APS ranks developers by output, efficiency, prompt quality, consistency, and breadth.
Visible to recruiters, teams, and the community. Demonstrate AI proficiency with cryptographically sealed session data.
Every prompt is sealed with an Ed25519 signature and linked in a hash chain. A real-time seal verification call to the cloud proves the session happened when it claims — only verified sessions count towards the leaderboard.
Every completed session is sealed with an Ed25519 digital signature and includes milestones in the signed data. Any edit after sealing invalidates the signature and is detected on read or upload.
Sessions are linked in a SHA-256 hash chain. Each entry references the previous one. Tampering with any record breaks the chain and is immediately detectable.
At session end, a verification request is sent to the cloud with the session ID and timestamp. The server generates a unique signature — proving the session was sealed in real-time, not fabricated later.
No source code or prompt contents are ever transmitted. The daemon processes everything locally in ~/.useai. When you sync, session metadata, titles, project names, evaluation scores, and milestones are sent. You own your raw data — always.
The entire project is open source under the AGPL-3.0 license. You can audit every line of code that runs on your machine.
No source code or prompt contents are ever transmitted. Session metadata, titles, project names, evaluation scores, and milestones are synced.
Private titles, project names, and evaluation reasons are synced but only visible to you. Public profiles show aggregate stats only — no titles, no project names, no code.
The UseAI daemon runs on your machine and stores data in ~/.useai. A seal verification call is made at session end for leaderboard eligibility — if offline, the session still seals normally.
Your session history is stored as date-based JSONL files (e.g. 2026-04-27.jsonl) you can read, export, or delete at any time. No vendor lock-in. Your data belongs to you.
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