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learn-from-materials

Turn books, PDFs, slides, Word documents, web pages, and multi-file material sets into traceable knowledge bases, interactive learning pages, and Markdown derived from the same content data.

learn-from-materials is a cross-agent learning skill built on the open Agent Skills specification. Systematic study emphasizes complete reading; a quick overview extracts the core argument. Both require verifiable sources, a strict separation between material facts and model-added content, offline-first operation, and least privilege.

It works in agent environments that can read files, run local commands, and recognize SKILL.md — such as WorkBuddy, Codex, Claude Code, and GitHub Copilot CLI. Pure chat environments without file-system access or Python execution can only use parts of the prompting workflow; they cannot perform material extraction, coverage validation, or HTML rendering.

Key Features

A Methodology That Spans the Whole Material

It starts by extracting the material's central question and its goal, then organizes the argument, frameworks and action rules into one complete structure. It supports the main flow, decision branches, causal and hierarchical relations, and evidence-backed feedback loops; it does not fix a step count and does not force every material into an eight-step process. The overview is not split into groups by node count, and selecting a node shows its inputs, actions, outputs, check conditions, related learning units and sources.

The whole structure is also saved separately as methodology.json / methodology.md, keeping what the source material itself does clearly distinct from the whole-material synthesis. "Apply This Methodology" carries the entire structure by default, letting the AI locate your entry point and advance you condition by condition; a single card can still be chosen instead.

Guided content shows source hints for core ideas, key points and conclusions on mouse hover and on keyboard focus, plus an expandable "Source" panel for touch screens. These stay available after switching units. When a verified fine-grained location exists, the matching page number is displayed; otherwise the unit-level or conclusion-level range is reported as-is.

See the whole-material methodology protocol, the original three-page teaching PDF, and the systematic-study example. The example includes coverage, action-rule, content-review and original-heading records. Its short length is for demonstration and regression testing, not an extraction ceiling for real materials.

An Accumulating Method Library

After parsing new material, reusable methods are saved to the knowledge base's methods.json, and a readable patterns.md is generated from it. Each card records purpose, prerequisites, limits, steps, effect checks, a short source quotation, a stable ID and a version; when a material contains no methodology, that is stated plainly rather than invented.