learn

CLAUDE.md Learning Integration

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "learn" with this command: npx skills add mintuz/claude-plugins/mintuz-claude-plugins-learn

CLAUDE.md Learning Integration

Use this skill to identify learning opportunities and document insights into CLAUDE.md. The goal is to ensure hard-won knowledge is preserved for future developers.

When to Use

  • User discovers a gotcha or unexpected behavior

  • User completes a complex feature and wants to document learnings

  • User makes an architectural decision worth preserving

  • User fixes a tricky bug with insights to share

  • User says "I wish I'd known this earlier"

Philosophy

Core Principle: Knowledge that isn't documented is knowledge that will be lost. Every hard-won insight must be preserved for future developers.

Identifying Learning Opportunities

Watch for these signals during development:

  • Gotchas or unexpected behavior discovered

  • "Aha!" moments or breakthroughs

  • Architectural decisions being made

  • Patterns that worked particularly well

  • Anti-patterns encountered

  • Tooling or setup knowledge gained

Discovery Questions

About the Problem

  • What was unclear or surprising at the start?

  • What took longer to figure out than expected?

  • What assumptions were wrong?

  • What would have saved time if known upfront?

About the Solution

  • What patterns or approaches worked particularly well?

  • What patterns should be avoided?

  • What gotchas or edge cases were discovered?

  • What dependencies or relationships were not obvious?

About the Context

  • What domain knowledge is now clearer?

  • What architectural decisions became apparent?

  • What testing strategies were effective?

  • What tooling or setup was required?

Learning Significance Assessment

Document if ANY of these are true:

  • Would save future developers significant time (>30 minutes)

  • Prevents a class of bugs or errors

  • Reveals non-obvious behavior or constraints

  • Captures architectural rationale or trade-offs

  • Documents domain-specific knowledge

  • Identifies effective patterns or anti-patterns

  • Clarifies tool setup or configuration gotchas

Skip if ALL of these are true:

  • Already well-documented in CLAUDE.md

  • Obvious or standard practice

  • Trivial change (typos, formatting)

  • Implementation detail unlikely to recur

CLAUDE.md Section Classification

Determine which section the learning belongs to:

Existing Sections

  • Core Philosophy - Fundamental principles (TDD, FP, immutability)

  • Testing Principles - Test strategy and patterns

  • TypeScript Guidelines - Type system usage

  • Code Style - Functional patterns, naming, structure

  • Development Workflow - TDD process, refactoring, commits

  • Working with Claude - Expectations and communication

  • Example Patterns - Concrete code examples

  • Common Patterns to Avoid - Anti-patterns

New Sections (if learning doesn't fit existing)

  • Project-specific setup instructions

  • Domain-specific knowledge

  • Architectural decisions

  • Tool-specific configurations

  • Performance considerations

  • Security patterns

Formatting Guidelines

For Principles/Guidelines

New Principle Name

Brief explanation of why this matters.

Key points:

  • Specific guideline with clear rationale
  • Another guideline with example
  • Edge case or gotcha to watch for
// ✅ GOOD - Example following the principle
const example = "demonstrating correct approach";

// ❌ BAD - Example showing what not to do
const bad = "demonstrating wrong approach";

For Gotchas/Edge Cases

Gotcha: Descriptive Title

Context: When does this occur Issue: What goes wrong Solution: How to handle it

// ✅ CORRECT - Solution example
const correct = handleEdgeCase();

// ❌ WRONG - What causes the problem
const wrong = naiveApproach();

For Project-Specific Knowledge

Project Setup / Architecture / Domain Knowledge

Specific Area

Clear explanation with:

  • Why this is important
  • How it affects development
  • Examples where relevant

Documentation Proposal Format

CLAUDE.md Learning Integration

Summary

Brief description of what was learned and why it matters.

Proposed Location

Section: [Section Name] Position: [Before/After existing content, or new section]

Proposed Addition

[Exact markdown content to add to CLAUDE.md]

Rationale

  • Why this learning is valuable
  • How it fits with existing guidelines
  • What problems it helps prevent
  • Time saved by documenting this

Verification Checklist

  • Learning is not already documented
  • Fits naturally into CLAUDE.md structure
  • Maintains consistent voice and style
  • Includes concrete examples if applicable
  • Prevents future confusion or wasted time

Voice and Style

  • Imperative tone: "Use X", "Avoid Y", "Always Z"

  • Clear rationale: Explain WHY, not just WHAT

  • Concrete examples: Show good and bad patterns

  • Emphasis markers: Use bold for critical points, ❌ ✅ for anti-patterns

  • Structured format: Use headings, bullet points, code blocks consistently

Quality Standards

  • Actionable: Reader should know exactly what to do

  • Specific: Avoid vague guidelines

  • Justified: Explain the reasoning and consequences

  • Discoverable: Use clear headings and keywords

  • Consistent: Match existing CLAUDE.md conventions

Quality Gates

Before proposing documentation, verify:

  • Learning is significant and valuable

  • Not already documented in CLAUDE.md

  • Includes concrete examples (good and bad)

  • Explains WHY, not just WHAT

  • Matches CLAUDE.md voice and style

  • Properly categorized in appropriate section

  • Actionable (reader knows exactly what to do)

Example Learning Integration

CLAUDE.md Learning Integration

Summary

Discovered that Zod schemas must be exported from a shared location for test files to import them, preventing schema duplication in tests.

Proposed Location

Section: Schema-First Development with Zod Position: Add new subsection "Schema Exports and Imports"

Proposed Addition

#### Schema Organization for Tests

**CRITICAL**: All schemas must be exported from a shared module that both production and test code can import.

```typescript
// ✅ CORRECT - Shared schema module
// src/schemas/payment.schema.ts
export const PaymentSchema = z.object({
  amount: z.number().positive(),
  currency: z.string().length(3),
});
export type Payment = z.infer<typeof PaymentSchema>;

// src/services/payment.service.ts
import { PaymentSchema, type Payment } from "../schemas/payment.schema";

// src/services/payment.service.test.ts
import { PaymentSchema, type Payment } from "../schemas/payment.schema";

Why this matters:

  • Tests must use the exact same schemas as production code
  • Prevents schema drift between tests and production
  • Ensures test data factories validate against real schemas
  • Changes to schemas automatically propagate to tests

Common mistake:

// ❌ WRONG - Redefining schema in test file
// payment.service.test.ts
const PaymentSchema = z.object({
  /* duplicate definition */
});

### Rationale

- Encountered this when tests were failing due to schema mismatch
- Would have saved 30 minutes if schema export pattern was documented
- Prevents future schema duplication violations
- Directly relates to existing "Schema Usage in Tests" section

### Verification Checklist

- [x] Learning is not already documented
- [x] Fits naturally into Schema-First Development section
- [x] Maintains consistent voice with CLAUDE.md
- [x] Includes concrete examples showing right and wrong approaches
- [x] Prevents the specific confusion encountered during this task

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

app-store-scraper

No summary provided by upstream source.

Repository SourceNeeds Review
General

gps-method

No summary provided by upstream source.

Repository SourceNeeds Review
General

local-ai-models

No summary provided by upstream source.

Repository SourceNeeds Review