Learn

Skill antonioshaman/aura-companion/.agents/skills/learn

Self-learning AI companion — 29 skills: adaptive knowledge base + Carmack Council + impeccable design. Every session makes it smarter.

Install

npx -y skills add antonioshaman/aura-companion --skill learn

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Quick-capture a learning during a session without interrupting flow. Appends to the knowledge base immediately.

SKILL.md

2.7 KB, 658 tokens by cl100k_base, as published. Nobody here has run it

Capture a learning right now, mid-session, without breaking flow.

Process

1. Parse the Insight

From the user's input or the current context, determine:

Type: Is this a pattern, gotcha, decision, anti-pattern, codebase-fact, or api-behavior?
Confidence: Did we verify this (high), observe it (medium), or suspect it (low)?
Tags: What files, features, or areas does this relate to?

2. Check for Duplicates

Read the target .jsonl file and check if a similar entry already exists:

If yes → re-confirm the existing entry (do NOT append a duplicate):
- bump helpfulCount by 1
- bump confidence if previously low/medium and the new evidence is strong
- set updatedAt to now
- update recommendation only if it's clearly better
If no → append a new entry

3. Write Entry

Append to the appropriate file in .agents/knowledge/. Field order matches .agents/knowledge/README.md:

{
  "id": "<type-prefix>-<next-number>",
  "type": "<detected-type>",
  "fact": "<concise insight>",
  "recommendation": "<what to do about it>",
  "confidence": "<detected-confidence>",
  "provenance": [{"source": "<human|agent|test-failure>", "reference": "<context>", "date": "<today>"}],
  "tags": ["<relevant>", "<tags>"],
  "affectedFiles": ["<paths>"],
  "createdAt": "<now ISO>",
  "updatedAt": "<now ISO>",
  "usageCount": 0,
  "helpfulCount": 0,
  "outdatedReports": 0
}

usageCount is bumped by /prime when surfacing, helpfulCount by /learn on re-confirmation, outdatedReports by /self-reflect or the user when an entry is flagged stale.

4. Confirm

Output a one-liner:

📝 Learned: [fact] → saved to [category] (confidence: [level])

Then continue with whatever you were doing.

Examples

User says: /learn the recorder auto-rotates at 1M lines → Saves as codebase-fact with tags ["recorder", "rotation"]

User says: /learn don't use window.location for routing, use hash routing → Saves as anti-pattern with tags ["routing", "frontend"]

Agent encounters unexpected behavior during work: → Auto-captures as gotcha with source: "agent"

Auto-Learn Triggers

During normal work, automatically capture learnings when:

A test fails for a non-obvious reason
The user corrects your approach ("no, don't do it that way")
You discover an undocumented API behavior
A code review reveals a missed pattern
You find something that contradicts an existing knowledge entry

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.