keep-learning

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name: keep-learning description: "Learn and memorize knowledge from local directories. Supports Markdown and code files. Extracts key insights, builds knowledge index, and stores in agent memory. Trigger with '持续学习知识' or 'keep learning'." license: MIT-0 compatibility: "Requires local filesystem access and git (optional, for auto-pull)." metadata: author: nileader version: "0.0.2" repository: https://github.com/nileader/keep-learning

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Keep Learning

Learn knowledge from local directories and store it in agent memory for future reference.

When to Use This Skill

Activate this skill when user says:

"持续学习知识"

"keep learning"

"learn knowledge base"

"学习知识库"

Supported File Formats (v0.0.1)

| Format | Extensions | Support | |--------|------------|---------| | Markdown | .md, .markdown | Full | | Python | .py | Full | | JavaScript/TypeScript | .js, .ts, .jsx, .tsx | Full | | Java | .java | Full | | Go | .go | Full | | Rust | .rs | Full | | C/C++ | .c, .cpp, .h, .hpp | Full | | Shell | .sh, .bash, .zsh | Full | | YAML/JSON/TOML | .yaml, .yml, .json, .toml | Full | | SQL | .sql | Full | | Other text | .txt, .csv | Full |

Not supported in v0.0.1: PDF, Word, Excel, PowerPoint, Keynote, audio, video files.

Three-Layer Knowledge Architecture

| Layer | Storage | Content | Purpose | |-------|---------|---------|---------| | L1 Core Memory | Agent Memory | Key conclusions, core concepts, decisions | Auto-surface in daily conversations | | L2 Knowledge Index | Agent Memory | File paths, summaries, keyword mappings | Know where knowledge lives | | L3 Source Files | Local filesystem | Complete original content | Deep-dive when needed via read_file |

How It Works: 1. Daily conversations: L1 memories automatically appear in memory_overview 2. Need more detail: Query L2 index to find relevant files 3. Deep investigation: Use read_file to access L3 source files

Runtime Data Directory

All runtime data is stored in ~/.keep-learning/:

| File | Purpose | |------|---------| | last-commit | Git commit hash of last learning session | | config.json | User configuration (knowledge base path, etc.) |

Learning Workflow

Step 1: Get Configuration

First, search memory (category: project_environment_configuration) for an existing knowledge base path.

If found: confirm the path with the user before proceeding. Example: "Found your knowledge base at ~/knowledge/work-assistant. Start learning from there?"

If NOT found: stop and ask the user to provide the knowledge base path before doing anything else. Do NOT proceed until the user provides a valid path. Example: "Please provide the path to your knowledge base directory (e.g., ~/knowledge/work-assistant)."

Once confirmed, store the path in memory using update_memory with category project_environment_configuration.

Step 2: Git Pull (If Applicable)

Check if knowledge base is a git repository and pull latest changes before learning.

Step 3: Scan Files

Scan for supported files. Exclude: .git, node_modules, .obsidian, __pycache__, .venv

Step 4: Detect Changes (Incremental Learning)

For git repositories, detect ALL types of changes:

1. Committed changes: Compare current HEAD with last-commit hash stored in ~/.keep-learning/last-commit using git diff HEAD --name-only 2. Uncommitted changes: Detect modified/added files in working directory using git status --porcelain

Combine both results to get the full list of changed files. This ensures learning happens even when:

Remote has no updates, but local files were edited

Local commits exist that haven't been pushed yet

Files are modified but not yet committed

After learning completes, update ~/.keep-learning/last-commit with current HEAD hash.

For non-git directories: scan all supported files (no incremental detection).

Step 5: Read and Extract Knowledge

For each file: read content, identify theme/concepts/conclusions, extract key knowledge.

Step 6: Store L1 Core Memory

Create L1 memory entries using update_memory with appropriate category:

expert_experience: Domain expertise, best practices

project_introduction: Project/product overviews

learned_skill_experience: Reusable methods, procedures

Title format: [Domain] Concise Topic Description

Step 7: Build L2 Knowledge Index

Create knowledge index with file path, theme, keywords mappings.

Step 8: Generate Learning Report

Output: Timestamp, Statistics, L1 Memories list, L2 Index summary, Notes.

Memory Deduplication

Before creating: search_memory first. If exists, update; if not, create.

Quick Reference

| Situation | Action | |-----------|--------| | First time user | Ask for knowledge base path | | Git repo detected | Run git pull before scanning | | Large file | Read in chunks, summarize each section | | Duplicate knowledge | Update existing memory | | Unsupported file | Skip and note in report |

Limitations (v0.0.1)

Only Markdown and code files supported

No PDF/Word/Excel/PPT support

Memory entries have size limits