book-to-skill
Turn any technical book PDF into a Claude Code skill, ready to study, reference, and use while you work.
Runssource: GitHubPythonMITcommit a6cad12dee07
Python, MIT licensed. The project labels itself: agent skills, ai agents, book to skill, context engineering, document processing, edtech, knowledge base and knowledge management.
book-to-skill runs. An Argusic agent installed it in 6 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
The book-to-skill package is installed as an editable pip package, passes ruff lint, all 627 tests pass, skill validation passes, and the CLI extracts text from documents producing structured JSON metadata and clean text output.
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 100 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
- Install time
- 6 minutes
- Cold machine to finish
- 3 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- How the result was proved
- pytest -q exited 0, 627 passed; book-to-skill /tmp/test_book.md --mode text extracted full_text.txt (48 words, 2 chapters detected) and metadata.json correctly; ruff check . passed; python3 tools/validate_skill.py SKILL.md passed
- Model tokens used
- 30,183
- Exact commit tested
- a6cad12dee07
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
Watch the session
The whole run, from a clean machine, at the speed it actually happened. Nothing is cut and nothing is sped up.
A recording of attempt 1, run . The verdict above comes from a different attempt, so read this as one session and not as the current result. The terminal recording it was made from is the evidence, stored with a sha256 fingerprint; the video is a rendering of it. Nothing loads from the video host until you press play.
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
"chapters_detected": 2,
"chapters_method": "numeric",
"chapter_headings_sample": [
"## Chapter 1: Introduction",
"## Chapter 2: Core Concepts"
],
"has_toc": false
}
The project installs, builds, passes all checks, and extracts content end-to-end. Here's the summar…
2026-09-21T22:19:22.011877Z ERROR codex_core::tools::router: error=exec_command failed: CreateProce…
tokens used
30,183Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Reached a running state on a clean machine, with the session recorded.
- Nothing broke on the way: zero errors between clone and running.
- Ran without a GPU, so it does not need one to start.
- Licensed MIT, as reported by its host.
- Measured 3 times, so the result is not a one-off.
What did not, or is not known
- Took 6 minutes to install, slower than the median of the 8 comparable projects Argusic has measured.
Of the 9 agent-skills projects Argusic has installed and timed, book-to-skill was the 7th fastest to reach a running state, and 8 of 9 reached one at all.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
- A quick evaluation: it was running 6 minutes after the clone.
- Following its own README: the documented path worked with nothing to fix.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
Topics (from GitHub)
agent-skillsai-agentsbook-to-skillcontext-engineeringdocument-processingedtechknowledge-baseknowledge-managementllmpdf-to-markdownragself-studystudy-tools
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/book-to-skill)Questions
- Does book-to-skill run?
- Yes. book-to-skill runs. Argusic installed and launched it on a clean machine in 6 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test book-to-skill?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit a6cad12dee07. 3 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test book-to-skill?
- The run that produced this verdict cost $0.01: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does book-to-skill take to install?
- 6 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does book-to-skill need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing book-to-skill?
- Nothing did, in the recorded run: zero errors between clone and running.
- How does book-to-skill compare with the alternatives?
- Of the 9 agent-skills projects Argusic has installed and timed, book-to-skill was the 7th fastest to reach a running state, and 8 of 9 reached one at all.
- Where is the evidence for book-to-skill?
- All 3 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.