Book To Skill

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SCRIPT_PATH=""
HERMES_HOME_RESOLVED="${HERMES_HOME:-$HOME/.hermes}"
PROJECT_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || true)"
HERMES_PROJECT_TRUSTED=false
if [ -n "$PROJECT_ROOT" ] && [ "${HERMES_AGENT:-}" = true ] && \
  command -v hermes >/dev/null 2>&1 && \
  command -v python3 >/dev/null 2>&1 && \
  hermes config get skills.trusted_project_dirs --json 2>/dev/null | PROJECT_ROOT="$PROJECT_ROOT" python3 -c 'import json, os, pathlib, sys; root=pathlib.Path(os.environ["PROJECT_ROOT"]).resolve(); sys.exit(not any(pathlib.Path(p).expanduser().resolve() == root for p in json.load(sys.stdin)))' 2>/dev/null
then
  HERMES_PROJECT_TRUSTED=true
fi

CANDIDATES=(
  "$HOME/.copilot/skills/book-to-skill/scripts/extract.py"
  "$HOME/.agents/skills/book-to-skill/scripts/extract.py"
  "$HOME/.claude/skills/book-to-skill/scripts/extract.py"
  "$HERMES_HOME_RESOLVED/skills/book-to-skill/scripts/extract.py"
  "$HERMES_HOME_RESOLVED"/skills/*/book-to-skill/scripts/extract.py
)
if [ "${HERMES_AGENT:-}" != true ]; then
  CANDIDATES+=(
    ".github/skills/book-to-skill/scripts/extract.py"
    ".claude/skills/book-to-skill/scripts/extract.py"
    ".agents/skills/book-to-skill/scripts/extract.py"
  )
fi
CANDIDATES+=(
  "$HOME/.config/agents/skills/book-to-skill/scripts/extract.py"
  "$HOME/.config/amp/skills/book-to-skill/scripts/extract.py"
)
if [ "$HERMES_PROJECT_TRUSTED" = true ]; then
  CANDIDATES=(
    "$PROJECT_ROOT/.hermes/skills/book-to-skill/scripts/extract.py"
    "$PROJECT_ROOT/.hermes/skills"/*/book-to-skill/scripts/extract.py
    "$PROJECT_ROOT/.agents/skills/book-to-skill/scripts/extract.py"
    "$PROJECT_ROOT/.agents/skills"/*/book-to-skill/scripts/extract.py
    "${CANDIDATES[@]}"
  )
fi
for candidate in "${CANDIDATES[@]}"
do
  if [ -f "$candidate" ]; then
    SCRIPT_PATH="$candidate"
    break
  fi
done

if [ -z "$SCRIPT_PATH" ]; then
  echo "Could not find scripts/extract.py for book-to-skill" >&2
  exit 1
fi

PYTHON_BIN="${PYTHON_BIN:-python3}"
if ! command -v "$PYTHON_BIN" >/dev/null 2>&1; then
  PYTHON_BIN="python"
fi

"$PYTHON_BIN" "$SCRIPT_PATH" $INPUT_PATHS --mode <BOOK_TYPE> --install-missing ask

📖 Sources detected: <total_sources> source(s)
<list each source filename and format from the sources metadata list>
<if images_dropped > 5: warn that N source images were not read>
📄 Combined Pages/Sections: ~<N> | Words: ~<N> | Total tokens: ~<N>K

💰 Estimated token cost (Full Conversion / Update):
   Input  (reading + prompts): ~<N>K tokens
   Output (skill files generated/updated):  ~<N>K tokens
   Total:                           ~<N>K tokens

   Cost: multiply the token counts above by your model's current
   input/output per-1M-token rates (prices and model

name: book-to-skill
description: "Converts books and documents (PDF, EPUB, DOCX, HTML, Markdown, plain text, RTF, MOBI/AZW with Calibre) into structured agent skills, extracting frameworks, mental models, principles, techniques, and anti-patterns. Use when the user wants to study a document through GitHub Copilot CLI, Amp, Claude Code, or Hermes Agent, apply an author's frameworks while working, or build a reusable knowledge base from a file."

---
name: book-to-skill
description: "Converts books and documents (PDF, EPUB, DOCX, HTML, Markdown, plain text, RTF, MOBI/AZW with Calibre) into structured agent skills, extracting frameworks, mental models, principles, techniques, and anti-patterns. Use when the user wants to study a document through GitHub Copilot CLI, Amp, Claude Code, or Hermes Agent, apply an author's frameworks while working, or build a reusable knowledge base from a file."
---

<!--
Cross-agent notes (informational; ignored by host agents):
  - Compatible skill roots: GitHub Copilot CLI (~/.copilot/skills, ~/.agents/skills,
    .github/skills, .claude/skills, .agents/skills), Amp (.agents/skills,
    ~/.config/agents/skills, ~/.config/amp/skills), Claude Code (~/.claude/skills),
    Hermes Agent ($HERMES_HOME/skills, .hermes/skills, .agents/skills).
  - `allowed-tools` is intentionally omitted to stay agent-neutral: Copilot CLI uses
    `shell`/MCP-server names, Claude uses `Bash`/`Read`/`Write`/`Glob`/`Grep`, Amp
    adds `shell_command`. The skill needs shell (to run extract.py) and file
    read/write — each host will prompt for those on first use.
  - Argument hint: <path-to-document-folder-or-glob>... [skill-name-slug]
-->

# Book-to-Skill Converter

Transform written knowledge into actionable agent skills by extracting structure — not producing summaries.

## Philosophy

Books contain crystallized expertise: frameworks, principles, and techniques that took years to develop. This skill extracts that knowledge into a format GitHub Copilot CLI, Amp, Claude Code, Hermes Agent, or another compatible agent can leverage repeatedly.

**Extract structure, not summaries.** A skill isn't a book report. It's a toolkit of:
- Named frameworks (mental models with clear application)
- Actionable principles (rules that guide decisions)
- Techniques (step-by-step methods)
- Anti-patterns (what to avoid and why)
- Voice calibration (how the author thinks and communicates)

**Preserve the author's precision.** Frameworks often have specific names for reasons. "The 5 Whys" isn't interchangeable with "ask why multiple times." Capture the exact formulation.

**Layer depth appropriately.** Simple books → simple skills. Complex books with 10+ frameworks → skills with reference files and on-demand chapters.

---

## Modes of Operation

Four paths available. Route based on what the user asks:

### 1. Full Conversion (Default)
**Trigger:** User provides one or more document/directory/glob paths without special instructions
**Action:** Run all steps below (Steps 0–9)
**Output:** Complete skill with SKILL.md, chapters/, glossary, patterns, cheatsheet

### 2. Analyze Only
**Trigger:** User says "analyze", "just extract", or "I want to review before generating"
**Action:** Run Steps 0–3, then produce a structured extraction report (frameworks, principles, techniques found). Stop — do NOT generate skill files.
**Output:** Analysis report for user review

### 3. Generate from Prior Analysis
**Trigger:** User has existing analysis notes or previously ran analyze-only
**Action:** Skip Steps 0–3, use the provided analysis as input, run Steps 4–9
**Output:** Skill files from the provided analysis

### 4. Update / Fold-in (Existing Skill)
**Trigger:** User provides one or more new source paths and indicates they want to update an existing skill (either by pointing to the existing skill folder, providing a skill slug that already exists in `SKILLS_HOME`, or explicitly requesting an update).
**Action:** Run Step 0 (out-of-scope check), Step 1 (validate inputs), Step 1.5 (identify book type), and Step 2 (extract new files). Then skip to Step 5 (identify/detect existing skill path) and run the **Update / Fold-in Workflow** to merge the new content into the existing skill files.
**Output:** Updated existing skill with new/revised chapter summaries and merged indexes/glossaries.

---

## Skill Locations

This converter can run from multiple skill systems. When looking for this converter's helper script or writing the generated book skill, prefer these locations in order:

1. GitHub Copilot CLI personal skills: `~/.copilot/skills/`
2. Cross-agent personal skills (Copilot, Amp, Codex): `~/.agents/skills/`
3. Claude Code personal skills: `~/.claude/skills/`
4. Project-local Copilot skills: `.github/skills/`
5. Project-local Claude skills: `.claude/skills/`
6. Project-local Amp / Copilot skills: `.agents/skills/`
7. Amp global skills: `~/.config/agents/skills/`
8. Amp legacy global skills: `~/.config/amp/skills/`
9. Hermes Agent personal skills: `$HERMES_HOME/skills/` (defaults to `~/.hermes/skills/`)
10. Hermes Agent project skills: `.hermes/skills/` or `.agents/skills/`

For **generated** book skills, pick a destination that the user's host agent can actually discover (see Step 5). When more than one valid root exists, ask the user once and remember the answer for the session — do not silently default.

---

## Step 0 — Out-of-scope check

If no arguments are provided, stop and respond:
> "book-to-skill requires a supported document path, folder, or glob pattern. Usage: `book-to-skill <path-to-document-folder-or-glob>... [skill-name-slug]`"

Throughout the workflow:
- Identify the input paths and the optional skill slug.
- If the last argument is not a file, folder, or glob that exists or matches any files, and it looks like a skill slug (e.g. lowercase hyphens, alphanumeric), treat it as `SKILL_NAME`.
- Treat all other arguments as the list of `INPUT_PATHS`.
- If any input path is an existing skill directory (contains `SKILL.md` and a `chapters/` sub-folder), or if `SKILL_NAME` matches an existing skill slug in `SKILLS_HOME`, flag this run as an **Update/Fold-in** operation (Mode 4).

---

## Step 1 — Validate input

Verify that there is at least one supported file, directory, or glob pattern among the `INPUT_PATHS`.
For directories and globs, expand them to find matching supported files (`.pdf`, `.epub`, `.docx`, `.txt`, `.md`, `.markdown`, `.rst`, `.adoc`, `.html`, `.htm`, `.rtf`, `.mobi`, `.azw`, `.azw3`).

If no supported files are found, stop with a clear error message.

---

## Step 1.5 — Identify content type

Before extracting, ask the user:

> "What kind of content do these sources have? This helps me choose the best extraction method.
>
> 1. **Technical** — has code blocks, tables, formulas, diagrams (e.g. programming books, academic papers, architecture guides)
> 2. **Text-heavy** — mostly prose, few or no tables/code (e.g. management, productivity, narrative non-fiction)
> 3. **Not sure** — I'll use the fast method and warn you if quality seems limited"

Store the answer as `BOOK_TYPE`:
- Option 1 → `BOOK_TYPE=technical`
- Option 2 → `BOOK_TYPE=text`
- Option 3 → `BOOK_TYPE=text`

**If `BOOK_TYPE=technical`**, inform the user before proceeding:
> "📐 Technical mode selected — using Docling for structure-aware extraction (tables, code blocks, formulas preserved as markdown). This takes ~1.5s per page, so expect a few minutes for longer sources. Starting now…"

**If `BOOK_TYPE=text`**, inform:
> "📄 Text mode selected — using the fastest suitable extractor for each file type. Plain text/Markdown/HTML are usually ready in seconds; PDFs use pdftotext when available."

---

## Step 2 — Extract text from the source documents

Run the extraction script, passing the input paths:

```bash
SCRIPT_PATH=""
HERMES_HOME_RESOLVED="${HERMES_HOME:-$HOME/.hermes}"
PROJECT_ROOT="$(git rev-parse --show-toplevel 2>/dev/null || true)"
HERMES_PROJECT_TRUSTED=false
if [ -n "$PROJECT_ROOT" ] && [ "${HERMES_AGENT:-}" = true ] && \
  command -v hermes >/dev/null 2>&1 && \
  command -v python3 >/dev/null 2>&1 && \
  hermes config get skills.trusted_project_dirs --json 2>/dev/null | PROJECT_ROOT="$PROJECT_ROOT" python3 -c 'import json, os, pathlib, sys; root=pathlib.Path(os.environ["PROJECT_ROOT"]).resolve(); sys.exit(not any(pathlib.Path(p).expanduser().resolve() == root for p in json.load(sys.stdin)))' 2>/dev/null
then
  HERMES_PROJECT_TRUSTED=true
fi

CANDIDATES=(
  "$HOME/.copilot/skills/book-to-skill/scripts/extract.py"
  "$HOME/.agents/skills/book-to-skill/scripts/extract.py"
  "$HOME/.claude/skills/book-to-skill/scripts/extract.py"
  "$HERMES_HOME_RESOLVED/skills/book-to-skill/scripts/extract.py"
  "$HERMES_HOME_RESOLVED"/skills/*/book-to-skill/scripts/extract.py
)
if [ "${HERMES_AGENT:-}" != true ]; then
  CANDIDATES+=(
    ".github/skills/book-to-skill/scripts/extract.py"
    ".claude/skills/book-to-skill/scripts/extract.py"
    ".agents/skills/book-to-skill/scripts/extract.py"
  )
fi
CANDIDATES+=(
  "$HOME/.config/agents/skills/book-to-skill/scripts/extract.py"
  "$HOME/.config/amp/skills/book-to-skill/scripts/extract.py"
)
if [ "$HERMES_PROJECT_TRUSTED" = true ]; then
  CANDIDATES=(
    "$PROJECT_ROOT/.hermes/skills/book-to-skill/scripts/extract.py"
    "$PROJECT_ROOT/.hermes/skills"/*/book-to-skill/scripts/extract.py
    "$PROJECT_ROOT/.agents/skills/book-to-skill/scripts/extract.py"
    "$PROJECT_ROOT/.agents/skills"/*/book-to-skill/scripts/extract.py
    "${CANDIDATES[@]}"
  )
fi
for candidate in "${CANDIDATES[@]}"
do
  if [ -f "$candidate" ]; then
    SCRIPT_PATH="$candidate"
    break
  fi
done

if [ -z "$SCRIPT_PATH" ]; then
  echo "Could not find scripts/extract.py for book-to-skill" >&2
  exit 1
fi

PYTHON_BIN="${PYTHON_BIN:-python3}"
if ! command -v "$PYTHON_BIN" >/dev/null 2>&1; then
  PYTHON_BIN="python"
fi

"$PYTHON_BIN" "$SCRIPT_PATH" $INPUT_PATHS --mode <BOOK_TYPE> --install-missing ask
```

Before extraction, the script checks optional Python packages needed for the detected format. If a better extractor is missing, it prompts the user with the available fallback. Non-interactive sessions default to fallback unless install mode is explicitly `yes`.

**Tip — preflight the environment:** run `"$PYTHON_BIN" "$SCRIPT_PATH" --check` to print a per-format report of which extractors are installed and the exact command to install whatever is missing, without processing any file. Useful when a user reports a setup or quality problem.

This creates a **per-run** work directory — `<tempdir>/book_skill_work-<pid>/` by default, or exactly the path you set in `BOOK_SKILL_WORKDIR` — containing:
- `full_text.txt` — combined extracted text of all sources with clear visually demarcated boundaries.
- `metadata.json` — overall combined size, words, pages, token counts, dropped EPUB image counts, the resolved `workdir`, and a detailed list of individual processed `sources`.

The run prints all three paths on completion (`Workdir ->`, `Text ->`, `Meta ->`). **Take the paths from that output (or from `metadata.json`'s own `workdir` field) rather than assuming a fixed location** — the directory name differs per run so that concurrent extractions on one machine cannot overwrite each other's results.

Read that run's `metadata.json` to inspect the results.

**Always confirm the extraction is the document you asked for** before generating anything: check `filename` / `source_file` in `metadata.json`, or the `SOURCE:` header on the first line of `full_text.txt`. If you are waiting on a background run, wait on *its* specific workdir — polling a shared path can surface a different run's output.

---

## Step 2.5 — Pre-flight cost estimate

Read this run's `metadata.json` (the `Meta ->` path from the extraction output) and present the user with an estimate **before doing any generation**:

```
📖 Sources detected: <total_sources> source(s)
<list each source filename and format from the sources metadata list>
<if images_dropped > 5: warn that N source images were not read>
📄 Combined Pages/Sections: ~<N> | Words: ~<N> | Total tokens: ~<N>K

💰 Estimated token cost (Full Conversion / Update):
   Input  (reading + prompts): ~<N>K tokens
   Output (skill files generated/updated):  ~<N>K tokens
   Total:                           ~<N>K tokens

   Cost: multiply the token counts above by your model's current
   input/output per-1M-token rates (prices and model