aiception

Extract verified lessons from work sessions into reusable skills in Open Brain.

Updated Apr 29, 2026
One-click install
npx skills add https://github.com/Greyborne/OB1-Canobi --skill aiception-greyborne
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: aiception
Source: https://github.com/Greyborne/OB1-Canobi/tree/main/skills/claudeception
Command: npx skills add https://github.com/Greyborne/OB1-Canobi --skill aiception-greyborne

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Aiception captures valuable, verified knowledge discovered during real work and converts it into reusable skills so future sessions can solve the same problems faster without repeating the investigation.

Core Features & Use Cases

  • Knowledge extraction from debugging and experimentation: Identifies non-obvious solutions, misleading-error root causes, and workaround patterns.
  • Duplicate-aware skill creation: Searches Open Brain and local skill directories to avoid redundant skills and update existing ones when appropriate.
  • Structured, reusable skill outputs: Drafts a new skill with clear triggers, problem context, solution steps, and verification guidance.

Quick Start

Tell your AI client to invoke aiception (for example, say “save this as a skill” after a notable breakthrough) so it can draft a new reusable skill and record it into Open Brain.

Frequently Asked Questions about aiception

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I save debugging breakthroughs as reusable skills?

To extract reusable knowledge from work sessions, invoke aiception to identify non-obvious solutions and misleading-error root causes, then draft structured skills with triggers, context, and verification steps. It persists these lessons in Open Brain to prevent future redundant investigations.

How do I prevent duplicate skills when extracting knowledge into Open Brain?

Preventing duplicate skills during Open Brain knowledge extraction is handled by searching existing directories before creating new entries. If matching skills exist, aiception updates them instead of generating redundant drafts.

Can I capture workflow automation quirks as structured skills for future tasks?

Capturing workflow automation quirks as structured skills is fully supported by extracting repeatable optimizations into shareable formats. Aiception drafts skills with deterministic trigger descriptions and specific problem context to ensure recurrence across future tasks.

Do I need Open Brain search functions to extract reusable lessons from work sessions?

Open Brain search and capture functions are required dependencies to extract reusable lessons from work sessions. Aiception needs these functions to persist new skills, search existing knowledge, and prevent duplicate creation during the knowledge extraction workflow.

What is the best way to document misleading-error root causes for future reference?

The best way to document misleading-error root causes is drafting a reusable skill with clear problem context and solution steps. Aiception converts verified debugging investigations into structured outputs persisted in Open Brain for future reference.