Hugging Face's logo

williamKang112
/
llm-fit

Model card Files
xet
 Community
llm-fit / RESUME_GUIDE.md
WilliamK112
feat: hardware detect + README comparison blurb
7af337e
preview code
|
Raw
History Blame Contribute Delete
3.65 kB

llm-fit Resume Guide (for next session)

Last updated: 2026-03-09 (America/Chicago)

Mission

Reach 1000 GitHub stars for llm-fit before next week by combining:

  1. product quality improvements,
  2. clear positioning,
  3. fast distribution + feedback loops.

Repo: https://github.com/WilliamK112/llm-fit

Current Progress Snapshot

  • Build progress: ███████░░░ 70%
  • Launch readiness: █████░░░░░ 50%
  • Star progress: ░░░░░░░░░░ 0% (0/1000)

Latest shipped commits

  • cc9a9e2 feat: benchmark submission schema + contribution guide
  • 3fa24b6 feat: improved detect output + README usage docs
  • 355d766 docs: v0.1.0 release notes
  • 7c579a8 feat: --detect + macOS auto-detection

Release

What is already done

  • CLI estimator works.
  • Web local UI works (npm start → http://localhost:4173).
  • Progress dashboard works (/progress.html).
  • --detect mode implemented (macOS via system_profiler).
  • README includes differentiation vs benchmark-only tools.
  • CONTRIBUTING.md + benchmark template added.
  • Launch-post templates exist in LAUNCH_POSTS.md.

Remaining TODO (priority order)

P0 (immediate)

  1. Add README conversion assets:
    • badges,
    • screenshot/GIF,
    • stronger above-the-fold demo section.
  2. Publish distribution wave:
    • X post,
    • Reddit post(s),
    • Show HN post.
  3. Monitor reactions and ship 1 fast follow-up patch (v0.2) from feedback.

P1

  1. Improve estimator realism:
    • quant-aware estimates,
    • confidence ranges,
    • clearer fallback guidance.
  2. Add machine profile presets and import/export.

P2

  1. Add lightweight test coverage for core estimator logic.

Expectations

  • Move fast with small, high-quality commits.
  • Never wait for a huge perfect release.
  • Every work block should end in one of:
    1. pushed commit,
    2. launched distribution action,
    3. clear unblock request.
  • Report progress in PR-style updates with:
    • commit hash,
    • progress bars,
    • star delta,
    • next highest-leverage action.

Limitations / Constraints

  • Stars cannot be guaranteed on a fixed timeline.
  • External platform posting may require human approval/session context.
  • No personal/privacy leakage.
  • No actions that impersonate user voice without explicit direction.
  • If required auth/platform access is missing, request shortest unblock step.

Allowed actions (pre-approved by user intent)

  • Continue building and improving llm-fit autonomously.
  • Install/use safe skills when needed (prefer vetted/security-reviewed flow).
  • Commit and push directly to the project repo.
  • Prepare launch/distribution content and execute where access permits.
  • Keep heartbeat-driven 10-minute progress checks aligned with HEARTBEAT.md.

Do/Don’t checklist for next session

Do

  • Read llm-fit/STAR_SPRINT.md first.
  • Run quick sanity checks before push:
    • npm run cli -- --detect
    • npm run cli -- --ram=16 --vram=8 --cpu=mid --platform=apple-silicon
  • Keep README and launch copy synchronized with current capabilities.

Don’t

  • Don’t claim launch/post actions were done unless verified.
  • Don’t stall on planning without shipping.
  • Don’t modify unrelated repos/files for this sprint.

Quick command block 

cd /Users/William/.openclaw/workspace/llm-fit
npm run cli -- --detect
npm start
# progress dashboard
open http://localhost:4173/progress.html

# git flow
git status
git add .
git commit -m "<small focused change>"
git push