AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
목표나 사용 중인 랩을 입력하면 가격·사용량·최근 변동을 한눈에 알려주는 AI 모델 의사결정 도구
A calm, opinionated decision tool for AI models. Tell it your goal, or the lab you already use, and get a straight answer — sourced pricing, real usage, and what changed lately.
개발 도구JavaScript · HTMLGitHub @lucascashwell3-ai온라인운영자 미확인
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개인 계정의 공개 저장소 소유자는 GitHub로 로그인해 운영자를 확인하고 소개를 직접 관리할 수 있습니다. 관리자 승인은 필요하지 않습니다.
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프로젝트 폴더에서 /nomorevibe verify를 실행하면 소유권을 확인하고 소개를 직접 관리할 수 있습니다.
1분 만에 확인하기Which AI model should you actually use? An independent, sourced decision tool
저장소 README에서 가져옴
README 전체를 불러오는 중입니다. 아래는 저장된 발췌입니다.
Which AI model should you actually use?
Everyone has access to more models than they can keep track of — and no time to work out which
one fits the task and the budget in front of them. Modelproof answers that in two ways:README 전문 보기 ↗Always-current AI model facts, and a setup that installs into the tools you already use.
Everyone has access to more models than they can keep track of. Modelproof keeps the facts straight and puts them where you work:
AGENTS.md. It sets which model each helper agent runs on — your choice first, then the
tool's or lab's own published default for that job, otherwise the same model as your main one —
plus a few lines on using them well. Every package includes a checker helper that re-checks
finished work in a fresh context with real evidence and never edits files. Two opt-ins stay off
unless you ask: big-job mode (your main model plans and reviews, the helpers do every piece) and
an example setup someone shared, labeled as one person's own choice. It adds files next to yours
instead of overwriting them, shows you the full plan before it writes anything, and undoes byte
for byte.Live at lucascashwell3-ai.github.io/modelproof.
assets/install-prompt.txt (also
on the home page) goes into Claude Code, Codex or Cursor. It reads your setup, asks a few quick
questions, shows every file before it writes, installs on your yes, and prints one undo line.skills/modelproof-advisor/ runs the same flow. The
prompt runs it once without installing it; to keep it, copy the folder into ~/.claude/skills/
(or your tool's skills folder).board.html builds the same package from a board you lay out, under
Install package.mcp/ serves the same facts (prices, releases, sourced quotes) over the
Model Context Protocol.table.html) — every tracked model with its sources and sourced
quotes, filterable by lab.board.html) — lay out the teams and routines in a company, or your
own set of models, and see the monthly bill and the cost per person and per year.how-we-pick.html) — where every number and quote
comes from.data/models.json is the single source: models across the major labs and
open-weight vendors, refreshed twice a week by an automated Collect → Judge → Verify pipeline
(GitHub Actions + a research pass with citations; see
automation/jobs/auto-refresh/). Anything the pipeline can't
source cleanly is held in a review issue instead of published. Each model also carries an
availability object — where it can actually be reached (direct API, OpenRouter, AWS Bedrock,
open weights) — derived automatically every Collect run by
scripts/derive-availability.mjs; a field is true only when
sourced, null otherwise, never a guessed negative. data/plans.json holds
seat/subscription pricing for the major chat apps and coding tools (Claude, ChatGPT, Gemini,
Grok, Cursor, GitHub Copilot), refreshed manually (see
scripts/refresh-plans.md) straight from each vendor's own pricing
page — a null price means the page didn't show that number in static HTML, never an invented one.
Honesty rules:
scripts/check-sources.mjs) — a claim that can't
be found on the page it cites is rejected, not softened.scripts/validate-data.mjs) blocks any publish that breaks
schema or sourcing rules.Retired pieces (the old ranking code and its answer key) are kept for history in
archive/.
Pure static site — no build step, no dependencies.
python3 -m http.server 8475 --directory .
# → http://localhost:8475
Vanilla HTML + CSS + JS, one models.json. Type: Fraunces (wordmark) + Cabinet Grotesk /
Switzer / JetBrains Mono. Restrained, GPU-friendly motion; no build tooling anywhere.
usage.openrouter on every
model, collected from OpenRouter's own rankings feed (scripts/derive-usage.mjs).Independent project · not affiliated with any model vendor · built by Lucas Cashwell. Sibling project: DATproof.