# Session Skill Extraction

Extracts reusable skills and lessons from work sessions and avoids duplicates.

- Repository: https://github.com/NateBJones-Projects/OB1 (4752 stars)
- Category: AI and agents
- License: see repository
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add NateBJones-Projects/OB1 --skill aiception -g -a claude-code -y`
Codex: `npx skills add NateBJones-Projects/OB1 --skill aiception -g -a codex -y`
Cursor: `npx skills add NateBJones-Projects/OB1 --skill aiception -g -a cursor -y`
Gemini CLI: `npx skills add NateBJones-Projects/OB1 --skill aiception -g -a gemini-cli -y`

## Description

Continuous learning system that extracts reusable knowledge from work sessions. Triggers: (1) /aiception command, (2) 'save this as a skill' or 'extract a skill from this', (3) 'what did we learn?', (4) after non-obvious debugging or trial-and-error discovery. Creates new skills when valuable reusable knowledge is identified. Integrates with Open Brain to prevent duplicates.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Aiception

A continuous learning system that extracts reusable knowledge from work sessions and
codifies it into new skills. This enables autonomous improvement over time.

## Core Principle

When working on tasks, continuously evaluate whether the current work contains extractable
knowledge worth preserving. Not every task produces a skill. Be selective about what's truly
reusable and valuable.

## When to Extract

Extract when you encounter:

1. **Non-obvious Solutions**: Debugging that required significant investigation and wouldn't
   be immediately apparent to someone facing the same problem.
2. **Error Resolution**: Specific error messages and their actual root causes, especially
   when the error message is misleading.
3. **Tool Integration Knowledge**: How to properly use a tool, library, or API in ways
   that documentation doesn't cover well.
4. **Workflow Optimizations**: Multi-step processes that can be streamlined.
5. **Project-Specific Patterns**: Conventions or decisions specific to a codebase.

## Quality Criteria

Before extracting, verify:

- **Reusable**: Will this help with future tasks, not just this one instance?
- **Non-trivial**: Does this require discovery, not just documentation lookup?
- **Specific**: Can you describe exact trigger conditions and solution?
- **Verified**: Has this solution actually worked?

## Extraction Process

### Step 1: Search Open Brain for Existing Knowledge

Before creating anything, check if this knowledge already exists:

```
search_thoughts({ "query": "[keywords from the discovery]", "match_count": 5 })
```

| Search Result | Action |
|---------------|--------|
| Strong match found | Update the existing skill instead of creating new |
| Partial match | Create new, add "See also" cross-reference |
| No match | Create new |

### Step 2: Check for Existing Skills

Search local skill directories for related skills:

The rest: https://github.com/NateBJones-Projects/OB1/blob/HEAD/skills/claudeception/SKILL.md