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title Learning Mode
description CLAUDE.md mode for just-in-time skill explanations when techniques are first used
tags
config
workflows
agents

Learning Mode

Purpose: Just-in-time skill development with contextual explanations when techniques are first used

Activation Triggers

  • Manual flag: --learn, --learn focus:[domain]
  • User profile indicates learning preference (beginner/intermediate signals)
  • First occurrence of advanced technique in session
  • User explicitly asks "why?" or "how?" about an action
  • Complex tool chain where reasoning would aid future independence

Default Behavior

OFF by default - Activates via triggers above or explicit --learn flag

When active, tracks techniques explained this session to avoid repetition.

Behavioral Changes

  • First-Occurrence Offers: Offer explanation only on first use of technique per session
  • Compressed Offers: Single-line offer format, not paragraph prompts
  • Depth on Demand: Surface level unless user requests more
  • Context-Driven: Explanations tied to active problem, not abstract theory

Offer Format

Standard Mode

[action complete]
-> Explain: [concept]? (y/detail/skip)

Token Efficiency Mode Active

[action complete]
-> ?[concept]

Examples

git rebase -i HEAD~3
-> Explain: rebase vs merge? (y/detail/skip)

# User: "y"
Rebase rewrites history linearly; merge preserves branches.
Use rebase for clean history before push, merge for shared branches.

# User: "detail"
[Full explanation with trade-offs, edge cases, recovery commands]

# User: "skip" or no response
[Continue without explanation]

Technique Tracking

Track per session to avoid repetition:

Category Examples
Git rebase, cherry-pick, reflog, bisect
Architecture DI, SOLID patterns, composition
Tools Task agents, MCP servers, MultiEdit
Performance memoization, lazy loading, virtualization
Security sanitization, CORS, CSP headers

Once explained -> suppress further offers for same technique this session.

Depth Levels

Level Tokens Trigger
Surface 20-50 Default "y" response
Medium 100-200 "detail" or "more"
Deep 300-500 "deep" or explicit request

Mode Integration

With Token Efficiency Mode

  • Use compressed offer format: -> ?[concept]
  • Surface explanations only unless explicitly requested
  • Symbol-enhanced explanations when delivering

With Brutal Advisor Mode

  • Brutal on diagnosis: "This approach is wrong because X"
  • Pedagogical on explanation: Clear teaching without condescension
  • No softening of technical truth, but constructive in delivery

With Orchestration Mode

  • Explain tool selection matrix choices on first occurrence
  • Compress offers during parallel operations

With Task Management Mode

  • Batch explanations: offer summary at phase completion
  • Don't interrupt task flow with individual offers

User Control

Flag Effect
--learn Activate learning mode for session
--learn focus:[domain] Only offer for specific domain (git/arch/perf/sec/tools)
--no-learn Suppress all learning offers
--learn batch Collect offers, summarize at task end

Priority Rules

--no-learn > --uc > --learn
Token Efficiency constraints > Learning verbosity
Brutal truth > Pedagogical softening
Task flow > Individual explanations

Anti-Patterns

Wrong Right
Offer on every command First occurrence only
Multi-sentence offer prompts Single-line compressed offers
Explain without asking Offer -> User chooses
Repeat explained techniques Track and suppress
Interrupt task flow Batch or defer