learn
Diagnose and fix agent behavioral surfaces when the user corrects a mistake — connects to Claude native memory.
Best use case
learn is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Diagnose and fix agent behavioral surfaces when the user corrects a mistake — connects to Claude native memory.
Teams using learn should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/learn/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How learn Compares
| Feature / Agent | learn | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Diagnose and fix agent behavioral surfaces when the user corrects a mistake — connects to Claude native memory.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# /learn — Behavioral Correction
When a user corrects a mistake, `/learn` diagnoses which behavioral surface caused it and applies a minimal, targeted fix.
## When to Use
- User corrects agent behavior ("no, don't do that", "you should always...", "stop doing X")
- Agent made a mistake that should never recur
- User explicitly invokes `/learn`
- A pattern of repeated errors suggests a missing behavioral rule
## How It Works
This is an **interactive skill**. The user invokes `/learn` directly, and the agent runs in the foreground, conversing with the user throughout.
## Flow
1. **Analyze the mistake:** What went wrong? Read the conversation context, recent changes, and relevant code to understand the error.
2. **Determine root cause:** Why did the agent behave this way? Missing rule? Stale convention? Wrong default?
3. **Diagnose the surface:** Which behavioral surface needs to change? (See Writable Surfaces below.)
4. **Propose minimal fix:** Enter native plan mode. Show exactly which file will change, what content will be added/modified, and why. One change per learning — never batch.
5. **Apply with approval:** User must approve before any write. Apply the change. Confirm what was learned.
6. **Save to memory:** Write the learning as a feedback memory in `.claude/memory/` so Claude native memory retains it across sessions.
## Writable Surfaces
The learn agent diagnoses which surface needs the fix:
| Surface | Path | What It Controls |
|---------|------|-----------------|
| Project conventions | `CLAUDE.md` | Commands, gotchas, project rules, coding style |
| Agent identity | `AGENTS.md` | Agent role, preferences, team behavior |
| Agent personality | `SOUL.md` / `IDENTITY.md` | Tone, communication style |
| Global rules | `~/.claude/rules/*.md` | Cross-project behavioral rules |
| Claude native memory | `.claude/memory/` | Feedback, user prefs, project context |
| Project memory | `memory/` | Project-scoped knowledge files |
| Hooks | `.claude/settings.json` | Event-driven automation, permission gates |
| Any config file | varies | Any file that shapes agent behavior |
## Never-Touch Surfaces
- `plugins/genie/skills/` — framework skills (maintained by framework developers)
- `plugins/genie/agents/` — framework agents (maintained by framework developers)
- Other projects' files — scope is the current project only
- Source code — learn updates behavior configuration, not implementation
## Claude Native Memory Connection
When a learning is applied, also save it as a feedback memory:
1. Write a memory file to `.claude/memory/` with frontmatter:
```markdown
---
name: <concise-name>
description: <one-line description for relevance matching>
type: feedback
---
<The rule itself>
**Why:** <reason the user gave or the incident that caused it>
**How to apply:** <when/where this guidance kicks in>
```
2. Update `.claude/memory/MEMORY.md` index with a pointer to the new file.
This ensures the learning persists across conversations via Claude's native memory system.
## Rules
- **Plan mode is mandatory** — never write without user approval via native plan mode.
- **One learning at a time** — diagnose one surface, propose one fix.
- **Never assume** — verify with the user before recording any learning.
- **Never modify framework files** — `plugins/genie/skills/` and `plugins/genie/agents/` are off limits.
- **Never write source code** — behavioral configuration only.
- **Minimal changes** — add the smallest rule that prevents the mistake from recurring.
- **Always save to memory** — every learning gets a feedback memory for cross-session persistence.Related Skills
work
Execute an approved wish plan — orchestrate subagents per task group with fix loops, validation, and review handoff.
wish
Convert an idea into a structured wish plan with scope, acceptance criteria, and execution groups for /work.
trace
Dispatch trace subagent to investigate unknown issues — reproduces, traces, and reports root cause for /fix handoff.
review
Validate plans, execution, or PRs against wish criteria — returns SHIP / FIX-FIRST / BLOCKED with severity-tagged gaps.
report
Investigate bugs comprehensively — cascade through /trace, capture browser evidence, extract observability data, and auto-create a GitHub issue with all findings.
refine
Transform a brief or prompt into a structured, production-ready prompt via prompt-optimizer. File or text mode.
genie
Transform any Claude Code session into an Automagik Genie orchestrator — guide users through brainstorm, wish, team, and PR lifecycle.
fix
Dispatch fix subagent for FIX-FIRST gaps from /review, re-review, and escalate after 2 failed loops.
dream
Batch-execute SHIP-ready wishes overnight — pick wishes, orchestrate workers, review PRs, wake up to results.
docs
Dispatch docs subagent to audit, generate, and validate documentation against the codebase.
council
Brainstorm and critique with 10 specialist viewpoints. Use for architecture, plan reviews, or tradeoffs.
brainstorm
Explore ambiguous or early-stage ideas interactively — tracks wish-readiness and crystallizes into a design for /wish.