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dymchenkkodymchenkko/claude-study-agent/.claude/skills/setup/SKILL.md

setup

Skill2 starsChanged 7 days agoMITView on GitHub

First-run onboarding - check this machine, install what is missing, pick the right semantic-search mode for the hardware, create the first subject. Use on first run, on a new computer, or when the user asks about setup, requirements, installation or search being slow / not working.

  • Pipes a download into a shell
  • Installs packages

191 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use add-voice-transcription, add-discord and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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  • +8 more from microsoft

The file

We split this skill into the rules it gives an agent

7 rules. 0 are common, 2 are distinctive, and 5 are very specific to this project.

  • 0

    Common

    Most of the 171 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Run ~/Study/.tools/study doctor and read the report (machine, tutor backend, tools, current and recommended search mode).

    line 9
  2. Very specific:

    If it can't run because there is no Python at all (rare): on macOS run xcode-select --install (I click Install in the dialog.

    line 10
  3. Very specific:

    If the Python line says needs 3.10+: ask me in one line, e.g.

    line 12
  4. Distinctive:

    Ask me one short question: which mode (recommended first.

    line 26
  5. Very specific:

    Run ~/Study/.tools/study setup --mode <mode> in the background (first time ~1–2 min: llama.cpp ~15 MB + a 310 MB model, no Python packages).

    line 28
  6. Distinctive:

    If the Whisper model is missing and I have lectures as video/audio, offer the download from the README.

    line 31
  7. Very specific:

    If no subject exists, ask for the subject name and exam date, run ~/Study/.tools/study new "<Subject>", and fill in the date and exam …

    line 32

“Common” is measured: kept by at least 6 in 10 of the 171 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Setup / onboarding

  1. Run ~/Study/.tools/study doctor and read the report (machine, tutor backend, tools, current and recommended search mode). If it can't run because there is no Python at all (rare): on macOS run xcode-select --install (I click Install in the dialog; it's also what reads scanned PDFs), on Linux sudo apt install python3; then rerun it. If the Python line says needs 3.10+: ask me in one line, e.g. "Your Python is too old for meaning-based search (3.9). Install a newer one? ~1 min, no password." On yes, if brew exists run brew install python, else curl -LsSf https://astral.sh/uv/install.sh | sh and then ~/.local/bin/uv python install 3.13. Rerun study doctor: the line now says ok (study switches to the newer Python by itself) and the recommended mode is no longer off because of Python.
  2. Tell me in ≤ 120 words, in plain words:
    • which file types I can already import, and which tools are missing (only the ones for file types I said I have — ask if unsure);
    • the search mode it recommends and why. The modes:
      • auto (Apple Silicon): uses the Apple GPU for indexing. Best when available.
      • cpu (any other Mac or Linux, ≥ 4 GB RAM): same results; indexing ~0.1 s per passage (a 90-min lecture ≈ 10 s, a 300-page PDF ≈ 1 min, once).
      • off (Windows without WSL, < 4 GB RAM or < 1 GB free disk, or "keep it light"): Grep only. Everything works; only meaning-based / cross-language search is missing.
  3. Ask me one short question: which mode (recommended first; accept the argument if given). Also offer to install the missing tools; show the exact commands from the report and run them only after I agree.
  4. Run ~/Study/.tools/study setup --mode <mode> in the background (first time ~1–2 min: llama.cpp ~15 MB + a 310 MB model, no Python packages). When done, show the two OK lines (device and timing). If it says .tools/.venv is no longer used, offer to delete it (~1 GB, the old PyTorch setup).
  5. If the Whisper model is missing and I have lectures as video/audio, offer the download from the README.
  6. If no subject exists, ask for the subject name and exam date, run ~/Study/.tools/study new "<Subject>", and fill in the date and exam format in its CLAUDE.md from what I tell you.
  7. End with the next action: drop files into <Subject>/materials/, then /ingest <Subject>, then /today.

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