# Clauxton Use Cases

Real-world examples of how Clauxton solves context management problems across different scenarios.

---

## Table of Contents

- [Overview](#overview)
- [Core Use Cases](#core-use-cases)
  - [1. Solo Developer - Personal Knowledge Management](#1-solo-developer---personal-knowledge-management)
  - [2. Team Collaboration - Shared Context](#2-team-collaboration---shared-context)
  - [3. Open Source Project - Contributor Onboarding](#3-open-source-project---contributor-onboarding)
  - [4. Enterprise Development - Compliance & Audit Trail](#4-enterprise-development---compliance--audit-trail)
  - [5. Education & Learning - Learning Journal](#5-education--learning---learning-journal)
- [Additional Use Cases](#additional-use-cases)
- [Getting Started](#getting-started)
- [Tips for All Use Cases](#tips-for-all-use-cases)
- [Resources](#resources)

---

## Overview

Clauxton provides **persistent context** for Claude Code through two core features:

1. **Knowledge Base (KB)**: Store decisions, architecture, patterns, notes
2. **Task Management**: Track dependencies, prevent conflicts, maintain state

This document shows how different users apply Clauxton to solve real problems.

---

## Core Use Cases

### 1. Solo Developer - Personal Knowledge Management

#### Persona

**Name**: Alex, Independent Full-Stack Developer
**Works On**: 3-5 client projects simultaneously
**Pain Point**: Context switching between projects causes 30-60 minute "warm-up" time

#### Problem Statement

Alex maintains multiple client projects:
- **Project A**: E-commerce site (Next.js + Postgres)
- **Project B**: Internal dashboard (React + Firebase)
- **Project C**: Mobile app backend (Python + FastAPI)

**Daily Reality**:
- Monday: Works on Project A, makes architectural decision about payment processing
- Tuesday-Thursday: Focuses on Project B
- Friday: Returns to Project A, spends 45 minutes re-reading code to remember context
- **Lost Productivity**: 2-3 hours per week just "re-learning" decisions

**Quote**: *"I know I made a decision about how to handle webhook retries in Project A, but I can't remember why we went with exponential backoff vs. immediate retry. Now I'm second-guessing myself."*

#### How Clauxton Helps

Clauxton becomes Alex's **external project memory**:

1. **Centralized Knowledge Base**: All project decisions in one searchable place
2. **TF-IDF Search**: Find "webhook retry" instantly across all projects
3. **MCP Integration**: Context automatically available in Claude Code
4. **Task Dependencies**: Track what needs to happen in what order

#### Implementation Steps

**Step 1: Initialize Clauxton in Each Project**

```bash
# Project A
cd ~/projects/ecommerce-site
clauxton init

# Project B
cd ~/projects/internal-dashboard
clauxton init

# Project C
cd ~/projects/mobile-backend
clauxton init
```

**Step 2: Document Key Decisions as They Happen**

When Alex makes the webhook decision in Project A:

```bash
cd ~/projects/ecommerce-site
clauxton kb add \
  --title "Webhook Retry Strategy: Exponential Backoff" \
  --category architecture \
  --tags "webhooks,stripe,payments,reliability" \
  --content "Decision: Use exponential backoff (1s, 2s, 4s, 8s, 16s) for webhook retries.

Reasoning:
- Stripe recommends exponential backoff for webhook retries
- Prevents overwhelming our server during outages
- Gives payment processor time to recover
- Max 5 retries = 31 seconds total

Alternative Considered:
- Immediate retry: Rejected because it could amplify problems during outages
- Fixed interval: Rejected because less efficient

Implementation:
- Using Celery with retry_backoff=True
- retry_backoff_max=16 (seconds)
- max_retries=5

References:
- Stripe Webhooks Best Practices: https://stripe.com/docs/webhooks/best-practices
- Celery Docs: https://docs.celeryproject.org/en/stable/userguide/tasks.html#retrying

Related Code:
- tasks/webhooks.py:45-60
"
```

**Step 3: Search When Returning to Projects**

Friday morning, Alex returns to Project A:

```bash
cd ~/projects/ecommerce-site
clauxton kb search "webhook retry"
```

**Output**:
```
Found 1 entry:

[1] KB-20251015-003 (Score: 0.89)
Title: Webhook Retry Strategy: Exponential Backoff
Category: architecture
Tags: webhooks, stripe, payments, reliability
Created: 2025-10-15

Decision: Use exponential backoff (1s, 2s, 4s, 8s, 16s) for webhook retries...
```

**Result**: Alex remembers the context in 30 seconds instead of 45 minutes.

**Step 4: Use Task Management for Cross-Project Dependencies**

Alex realizes Projects A and B both need authentication updates:

```bash
# Project A
cd ~/projects/ecommerce-site
clauxton task add \
  --title "Upgrade to OAuth 2.1" \
  --priority high \
  --estimate 4h

# Project B
cd ~/projects/internal-dashboard
clauxton task add \
  --title "Upgrade to OAuth 2.1" \
  --priority high \
  --estimate 3h \
  --depends-on "ecommerce:Upgrade to OAuth 2.1"
```

Now Clauxton ensures Alex finishes Project A's auth upgrade before starting Project B's.

**Step 5: MCP Integration for Seamless Context**

Alex configures MCP in Claude Code:

```json
{
  "mcpServers": {
    "clauxton": {
      "command": "clauxton",
      "args": ["mcp"]
    }
  }
}
```

**Workflow**:
1. Opens Project A in Claude Code
2. Asks: *"How do we handle webhook retries?"*
3. Claude Code uses `clauxton_kb_search` tool automatically
4. Gets full context about exponential backoff decision
5. Responds with accurate information

**No manual searching needed** - context is automatic.

#### Best Practices for Solo Developers

1. **Document Immediately**: Don't wait until end of day
   - ✅ Document decisions right after making them
   - ❌ Wait until Friday to "catch up" on documentation

2. **Use Descriptive Tags**: Makes search more effective
   - ✅ `tags: "webhooks,stripe,payments,reliability"`
   - ❌ `tags: "misc,todo"`

3. **Include "Why" Not Just "What"**: Future you needs reasoning
   - ✅ "We chose X because Y. Alternatives considered: A (rejected because B)"
   - ❌ "We use X."

4. **Search Before Implementing**: Check if you've solved this before
   ```bash
   clauxton kb search "authentication flow"
   ```

5. **Use Task Dependencies**: Prevent starting B before finishing A
   ```bash
   clauxton task add "Task B" --depends-on "Task A"
   ```

#### Results for Alex

**Before Clauxton**:
- Context switching: 30-60 min per project
- Weekly time lost: 2-3 hours
- Decisions forgotten: ~40%
- Code duplication: Common

**After Clauxton** (3 months):
- Context switching: 5-10 min per project
- Weekly time saved: 2+ hours
- Decisions documented: 90%
- Code duplication: Rare (search finds previous solutions)

**ROI**: 2+ hours per week = 8-10 hours per month = **1-2 full workdays saved**

---

### 2. Team Collaboration - Shared Context

#### Persona

**Team**: 5 full-stack engineers
**Project**: SaaS product (microservices architecture)
**Pain Point**: Async collaboration causes context loss and duplicate work

#### Problem Statement

**Team Structure**:
- **Alice**: Backend lead (API design)
- **Bob**: Frontend lead (React components)
- **Carol**: DevOps (infrastructure)
- **David**: Backend (database)
- **Eve**: Full-stack (features)

**Daily Challenges**:
1. **Context Loss**: Alice designs API on Monday, Bob implements frontend on Wednesday, but forgot why certain fields are optional
2. **Duplicate Discussions**: Same architecture questions asked multiple times
3. **Onboarding Pain**: New team member asks questions that were answered 3 months ago
4. **Decision Tracking**: "Why did we choose Postgres over MongoDB?" - no one remembers

**Quote from Bob**: *"I spent 2 hours implementing a feature, then found out Carol already solved this problem last month. We have no shared memory as a team."*

#### How Clauxton Helps

Clauxton becomes the team's **shared external memory**:

1. **Centralized Knowledge Base**: All team decisions in one place (Git-tracked)
2. **Search Across All Entries**: Find any past decision instantly
3. **Task Dependencies**: Prevent conflicting work
4. **MCP Integration**: Context available to all team members in Claude Code

#### Implementation Steps

**Step 1: Team Setup - Initialize Clauxton in Main Repo**

```bash
cd ~/projects/saas-product
git checkout main
clauxton init

# Commit to Git
git add .clauxton/
git commit -m "feat: Initialize Clauxton for team knowledge base"
git push origin main
```

Now all team members have access to the same KB.

**Step 2: Establish Documentation Guidelines**

**Team Guidelines** (in `CONTRIBUTING.md`):

```markdown
## Clauxton Documentation Standards

### When to Document in Clauxton KB

1. **Architecture Decisions**: All ADRs (Architecture Decision Records)
2. **API Design Choices**: Why fields are structured a certain way
3. **Database Schema Changes**: Reasoning behind migrations
4. **Performance Optimizations**: What was tried, what worked
5. **Failed Experiments**: What didn't work and why (saves others time)

### How to Document

```bash
clauxton kb add \
  --title "Clear, Descriptive Title" \
  --category [architecture|api|database|performance|pattern] \
  --tags "comma,separated,tags" \
  --content "Decision + Reasoning + Alternatives + Implementation"
```

### Before Starting Work

1. Search KB for existing solutions: `clauxton kb search "your topic"`
2. Check task dependencies: `clauxton task list --status pending`
```

**Step 3: Real-World Example - API Design Decision**

Alice designs a new API endpoint for user profiles:

```bash
clauxton kb add \
  --title "User Profile API: Optional vs Required Fields" \
  --category api \
  --tags "api,users,profiles,validation" \
  --content "Decision: Make 'phone' and 'avatar' optional in User Profile API.

Reasoning:
- Not all users want to provide phone numbers (privacy)
- Avatar upload requires separate flow (file upload complexity)
- Email + name are sufficient for core functionality
- We can add required=true later if needed, but can't remove it without breaking changes

API Schema:
{
  'email': string (required),
  'name': string (required),
  'phone': string | null (optional),
  'avatar_url': string | null (optional),
  'created_at': timestamp (auto)
}

Implementation:
- Pydantic model in api/models/user.py
- phone: Optional[str] = None
- avatar_url: Optional[str] = None

Discussed with: Bob (frontend), David (database)
Date: 2025-10-15
"

# Link to task
clauxton task add \
  --title "Implement User Profile API endpoint" \
  --assignee alice \
  --priority high \
  --estimate 6h \
  --status in-progress
```

**Step 4: Bob Searches Before Implementing Frontend**

Two days later, Bob starts frontend work:

```bash
clauxton kb search "user profile fields"
```

**Output**:
```
Found 1 entry:

[1] KB-20251015-008 (Score: 0.92)
Title: User Profile API: Optional vs Required Fields
Category: api
Tags: api, users, profiles, validation

Decision: Make 'phone' and 'avatar' optional...
```

**Result**: Bob immediately understands why phone is optional, implements UI correctly with optional fields.

**Time Saved**: 30+ minutes (no need to ask Alice, wait for response, or guess)

**Step 5: Task Dependencies Prevent Conflicts**

Carol needs to update the database schema, but David is working on a related migration:

```bash
# David's task (already in progress)
clauxton task add \
  --title "Add indexes to users table for performance" \
  --assignee david \
  --status in-progress \
  --estimate 3h

# Carol's task (depends on David finishing)
clauxton task add \
  --title "Add user_profiles table with foreign key to users" \
  --assignee carol \
  --priority medium \
  --estimate 4h \
  --depends-on "Add indexes to users table for performance"

clauxton task next
```

**Output**:
```
Cannot work on "Add user_profiles table" yet.
Dependency not complete: "Add indexes to users table for performance" (assigned to david, in-progress)
```

**Result**: Carol knows to wait for David, preventing merge conflicts.

**Step 6: New Team Member Onboarding**

New engineer Frank joins the team:

```bash
# Frank searches common questions
clauxton kb search "postgres mongodb"
```

**Output**:
```
Found 1 entry:

[1] KB-20250901-002 (Score: 0.88)
Title: Database Choice: Postgres vs MongoDB
Category: architecture
Tags: database, postgres, mongodb, decision

Decision: Use Postgres for main database.

Reasoning:
- Strong ACID guarantees needed for billing
- Complex relational queries (users, subscriptions, invoices)
- Team has more Postgres experience
- Better tooling for migrations (Alembic)

When MongoDB considered:
- Explored for logging/analytics (flexible schema)
- Decided to use Postgres JSONB instead (simplicity)

Implementation:
- SQLAlchemy ORM with Alembic migrations
- Connection pooling via PgBouncer
```

**Result**: Frank understands architectural decisions without interrupting senior engineers.

**Team Time Saved**: 5+ hours per new hire onboarding

#### Best Practices for Team Collaboration

1. **Git-Track `.clauxton/` Directory**: Share KB across team
   ```bash
   git add .clauxton/
   git commit -m "docs: Add API design decision to KB"
   ```

2. **Tag Team Members**: Use `@mentions` in content
   ```
   Discussed with: @alice @bob
   ```

3. **Document Failed Experiments**: Save others from repeating mistakes
   ```bash
   clauxton kb add \
     --title "Tried Redis for Session Store - Reverted" \
     --category experiment \
     --content "What we tried, why it failed, what we learned"
   ```

4. **Weekly KB Review**: 15-minute standup section
   - "What did you add to the KB this week?"
   - Ensures documentation culture

5. **Search Before Asking**: Establish team norm
   - Before Slack: `clauxton kb search "your question"`
   - Reduces interruptions by 40-60%

#### Results for Team

**Before Clauxton**:
- Context questions in Slack: 20-30 per day
- Time spent answering repeated questions: 2-3 hours/week per senior
- Duplicate work: 1-2 instances per sprint
- Onboarding time for new hires: 2-3 weeks

**After Clauxton** (6 months):
- Context questions in Slack: 5-10 per day (70% reduction)
- Time spent answering questions: 30-45 min/week per senior (75% reduction)
- Duplicate work: Rare (<1 per quarter)
- Onboarding time: 1 week (60% faster)

**ROI for 5-Person Team**:
- Senior time saved: 1.5-2 hours/week × 2 seniors = 3-4 hours/week
- Duplicate work prevented: ~8-16 hours per quarter
- **Total**: 12-16 hours per month saved = **2 full workdays per month**

---

### 3. Open Source Project - Contributor Onboarding

#### Persona

**Project**: Popular Python CLI tool (5000+ GitHub stars)
**Maintainer**: Sarah (solo maintainer)
**Pain Point**: 80% of contributor PRs require extensive feedback due to missing context

#### Problem Statement

**Sarah's Daily Reality**:
- 10-15 PRs per week from new contributors
- 80% of PRs need major revisions:
  - "Why didn't you follow the established pattern for commands?"
  - "This breaks the plugin system we designed 6 months ago"
  - "We already tried this approach and it had performance issues"

**Time Breakdown Per PR**:
- Initial review: 15-20 minutes
- Back-and-forth comments: 30-45 minutes
- Final review after revisions: 10-15 minutes
- **Total**: 55-80 minutes per PR

**Problem**: Contributors lack context about:
1. Architecture decisions
2. Design patterns used in the codebase
3. Failed experiments
4. Performance considerations

**Quote from Sarah**: *"I'm spending 8-10 hours per week just educating contributors about context they can't find in the code. I love the contributions, but I'm burning out."*

#### How Clauxton Helps

Clauxton becomes the project's **institutional memory** for contributors:

1. **Architecture Decision Records (ADRs)**: All major decisions documented
2. **Design Patterns**: Established patterns explained with examples
3. **Failed Experiments**: What doesn't work and why
4. **MCP Integration**: Contributors get context automatically in Claude Code

#### Implementation Steps

**Step 1: Document Existing Architecture Decisions**

Sarah spends 4 hours documenting key decisions:

```bash
cd ~/oss-projects/my-cli-tool

# Decision 1: Plugin System
clauxton kb add \
  --title "Plugin Architecture: Entry Points vs. Direct Imports" \
  --category architecture \
  --tags "plugins,architecture,extensibility" \
  --content "Decision: Use setuptools entry_points for plugin discovery.

Reasoning:
- Plugins can be installed as separate packages
- No need to modify core code to add plugins
- Standard Python approach (used by pytest, Flask, etc.)

How It Works:
1. Plugins define entry point in pyproject.toml:
   [project.entry-points.'mycli.plugins']
   my_plugin = 'my_plugin.main:register'

2. Core discovers plugins at runtime:
   from importlib.metadata import entry_points
   plugins = entry_points(group='mycli.plugins')

Failed Experiment:
- Tried direct imports with plugin registry pattern
- Required core code changes for each new plugin
- Rejected for maintainability

Implementation:
- src/core/plugin_loader.py
- docs/plugin-development.md

Contributing Guide:
If you're adding a new plugin, follow the entry_points pattern.
See examples in plugins/builtin/ directory.
"

# Decision 2: Command Pattern
clauxton kb add \
  --title "Command Pattern: Class-Based vs. Function-Based" \
  --category pattern \
  --tags "commands,cli,architecture" \
  --content "Decision: Use class-based commands inheriting from BaseCommand.

Reasoning:
- Consistent structure across all commands
- Built-in validation and error handling
- Easy to test (mock methods)
- Support for command options and arguments

Pattern:
class MyCommand(BaseCommand):
    name = 'my-command'
    help = 'Description'

    def add_arguments(self, parser):
        parser.add_argument('--option')

    def run(self, args):
        # Implementation here
        pass

Why Not Functions:
- Tried function-based commands in v1.0
- Hard to maintain consistent error handling
- Validation logic duplicated across commands
- Refactored to classes in v2.0

Contributing Guide:
All new commands MUST inherit from BaseCommand.
See src/commands/base.py for full API.
Examples in src/commands/builtin/.
"

# Decision 3: Performance Constraint
clauxton kb add \
  --title "Performance Requirement: CLI Startup < 100ms" \
  --category performance \
  --tags "performance,startup,imports" \
  --content "Requirement: CLI must start in under 100ms (cold start).

Why:
- CLI tools are used in scripts and CI/CD
- Slow startup impacts user experience
- Competitors (tool-x, tool-y) start in 50-80ms

How to Achieve:
1. Lazy imports: Import modules only when command runs
   ❌ Bad: import heavy_module at top of file
   ✅ Good: import heavy_module inside run() method

2. Avoid heavy dependencies in core
   ❌ Bad: import pandas, numpy in main.py
   ✅ Good: Only import click, sys, os in main.py

3. Use lazy loading for plugins
   ✅ Plugins discovered at runtime, not import time

Failed Experiment:
- Tried pre-compiling with Nuitka (v1.5)
- Startup improved to 60ms, but distribution became complex
- Users struggled with installation
- Reverted to pure Python with lazy imports

Measurement:
time my-cli --version
# Should output < 0.1s

Contributing Guide:
Before submitting PR with new dependencies, measure startup time:
pip install -e .
time my-cli --version

If startup > 100ms, use lazy imports.
"
```

**Step 2: Add Clauxton to CONTRIBUTING.md**

Sarah updates the contribution guide:

```markdown
## Before Contributing

### Search the Knowledge Base

We use Clauxton to document architecture decisions, design patterns, and failed experiments.

**Installation**:
```bash
pip install clauxton
```

**Search Before Coding**:
```bash
# In the project root
clauxton kb search "your topic"
```

**Examples**:
```bash
# Understand plugin system
clauxton kb search "plugin architecture"

# Learn command pattern
clauxton kb search "command pattern class"

# Check performance requirements
clauxton kb search "startup performance"
```

### MCP Integration (Optional but Recommended)

Configure Claude Code to automatically access project context:

1. Add to Claude Code MCP settings:
```json
{
  "mcpServers": {
    "clauxton": {
      "command": "clauxton",
      "args": ["mcp"]
    }
  }
}
```

2. When working on PRs, ask Claude:
   - "What's the established pattern for commands in this project?"
   - "Are there performance constraints I should know about?"
   - Claude Code will search the KB automatically

### Common Questions (with KB Search Queries)

| Question | KB Search Query |
|----------|-----------------|
| How do plugins work? | `plugin architecture entry points` |
| How do I add a new command? | `command pattern BaseCommand` |
| Why is startup time important? | `startup performance 100ms` |
| What dependencies are allowed? | `dependencies heavy imports` |
```

**Step 3: Contributor Workflow Example**

**New Contributor** (Mike) wants to add a new command:

```bash
# Mike clones the repo
git clone https://github.com/sarah/my-cli-tool.git
cd my-cli-tool

# Mike searches for command pattern
clauxton kb search "command pattern"
```

**Output**:
```
Found 1 entry:

[1] KB-20250915-002 (Score: 0.94)
Title: Command Pattern: Class-Based vs. Function-Based
Category: pattern
Tags: commands, cli, architecture

Decision: Use class-based commands inheriting from BaseCommand.

Pattern:
class MyCommand(BaseCommand):
    name = 'my-command'
    help = 'Description'

    def add_arguments(self, parser):
        parser.add_argument('--option')

    def run(self, args):
        # Implementation here
        pass
...
```

**Result**: Mike implements the command correctly on first try, following established pattern.

**Step 4: Mike's PR Review**

Mike submits PR following the pattern. Sarah reviews:

**Before Clauxton**:
- Sarah: "Please use class-based commands, not functions"
- Mike: "Oh, I didn't know. Let me rewrite..."
- **Review cycles**: 3-4

**After Clauxton**:
- Sarah: "LGTM! Follows the BaseCommand pattern perfectly."
- **Review cycles**: 1

**Time Saved**: 40-60 minutes per PR

#### Best Practices for Open Source Maintainers

1. **Document Top 10 Architecture Decisions**: Spend 4-6 hours upfront
   - Plugin system
   - Command pattern
   - Testing approach
   - Performance requirements
   - Code style rationale
   - Dependency philosophy
   - Error handling pattern
   - Configuration system
   - Release process
   - Backwards compatibility policy

2. **Add Clauxton to CONTRIBUTING.md**: Make it discoverable
   ```markdown
   ## Before Coding: Search the Knowledge Base
   clauxton kb search "your topic"
   ```

3. **Link to KB from PR Template**: Remind contributors
   ```markdown
   ## Pre-Submission Checklist
   - [ ] I searched the Clauxton KB for relevant decisions
   - [ ] My code follows established patterns
   ```

4. **Document Failed PRs**: Turn rejections into KB entries
   ```bash
   clauxton kb add \
     --title "Rejected Approach: Direct Database Access in Commands" \
     --category antipattern \
     --content "Why this doesn't work in our architecture..."
   ```

5. **Monthly KB Audit**: Update outdated entries
   - Mark deprecated decisions
   - Add new learnings from PRs

#### Results for Sarah

**Before Clauxton**:
- PRs per week: 10-15
- PRs needing major revisions: 80% (12/15)
- Time per PR review: 55-80 minutes
- Total review time per week: 8-10 hours
- Burnout risk: High

**After Clauxton** (6 months):
- PRs per week: 10-15 (unchanged)
- PRs needing major revisions: 30% (4-5/15) - **62% reduction**
- Time per PR review: 15-25 minutes - **70% reduction**
- Total review time per week: 2.5-4 hours - **65% reduction**
- Burnout risk: Low
- Contributor satisfaction: Higher (less back-and-forth)

**ROI**:
- Time saved: 5-6 hours per week = **20-24 hours per month**
- Better contributor experience: More likely to contribute again
- Project velocity: 60% faster PR merges

---

### 4. Enterprise Development - Compliance & Audit Trail

#### Persona

**Company**: FinTech startup (Series B, 50 employees)
**Team**: 12-person engineering team
**Compliance Requirements**: SOC 2, GDPR, PCI DSS
**Pain Point**: Auditors ask "Why did you make this security decision?" - no documentation trail

#### Problem Statement

**Regulatory Requirements**:
1. **SOC 2**: Document all security-relevant decisions
2. **GDPR**: Explain data processing decisions
3. **PCI DSS**: Justify payment handling architecture

**Current Problems**:
- Decisions made in Slack (not searchable after 90 days)
- Architecture discussions in meetings (no written record)
- Code comments insufficient for compliance
- Auditors request documentation that doesn't exist

**Real Audit Question**:
> "Why did you choose to store credit card tokens in Postgres instead of a separate vault? Document the risk assessment and alternatives considered."

**Current Response**: "Uh... let me ask the team who worked on this 8 months ago."

**Compliance Risk**: Failed audit = Delayed funding round

#### How Clauxton Helps

Clauxton becomes the **compliance-grade decision log**:

1. **Immutable Audit Trail**: All decisions Git-tracked with timestamps
2. **Searchable by Topic**: Find security/privacy decisions instantly
3. **Alternatives Documented**: Show due diligence in decision-making
4. **Git Blame Integration**: Tie decisions to specific commits

#### Implementation Steps

**Step 1: Establish Compliance-Focused KB Categories**

```bash
cd ~/work/fintech-product
clauxton init

# Define categories in team documentation
Categories for Compliance:
- security: Security architecture decisions
- privacy: GDPR-relevant data handling
- payment: PCI DSS payment processing
- access-control: Authentication/authorization
- encryption: Data encryption decisions
- audit: Audit logging decisions
```

**Step 2: Document Security Decision with Compliance in Mind**

**Example**: Credit card token storage decision

```bash
clauxton kb add \
  --title "Security Decision: Credit Card Token Storage Architecture" \
  --category security \
  --tags "pci-dss,security,payments,tokens,postgres" \
  --content "Decision: Store tokenized credit card references in Postgres, actual card data in Stripe.

Context:
- Requirement: Support saved payment methods for recurring billing
- Compliance: PCI DSS Level 1 required
- Date: 2025-10-15
- Decision Makers: Alice (CTO), Bob (Security Lead), Carol (Backend Lead)

Decision:
1. Stripe Vault: Store actual credit card data in Stripe (PCI-compliant)
2. Postgres: Store Stripe token IDs (e.g., 'tok_1234...') only
3. No raw card data ever touches our servers

Risk Assessment:

HIGH RISK (Rejected):
- Store encrypted card data in our Postgres
- Risk: We become PCI DSS Level 1 scope (expensive, complex audits)
- Risk: Encryption key management burden
- Risk: Security vulnerabilities if key leaked

MEDIUM RISK (Rejected):
- Store card data in separate vault service (e.g., HashiCorp Vault)
- Risk: Additional infrastructure complexity
- Risk: Still in PCI scope
- Cost: $2000+/month for managed vault

LOW RISK (Chosen):
- Use Stripe as card vault (Stripe is PCI Level 1 certified)
- Our servers only see tokens (out of PCI scope)
- Cost: Included in Stripe pricing
- Reduced compliance burden (Stripe handles PCI audits)

Alternatives Considered:
1. Braintree Vault - Rejected (prefer Stripe for other features)
2. Self-hosted vault - Rejected (security risk + PCI scope)
3. No saved cards - Rejected (bad UX for recurring billing)

Implementation:
1. Stripe Checkout collects card data (PCI-compliant hosted form)
2. Stripe returns token ID
3. We store token ID in users.payment_methods table (Postgres)
4. For charges: Send token ID to Stripe API

Data Flow:
User Browser → Stripe Checkout (HTTPS) → Stripe Servers → Token ID → Our API → Postgres
(Raw card data never reaches our servers)

Compliance Benefits:
- OUT of PCI DSS Level 1 scope (Stripe handles it)
- GDPR compliant (no sensitive card data stored by us)
- SOC 2 compliant (reduced attack surface)

Security Controls:
1. Token IDs encrypted at rest (Postgres TLS + disk encryption)
2. Token IDs encrypted in transit (API uses HTTPS only)
3. Access control: Only billing service can read tokens (IAM policies)
4. Audit logging: All token usage logged to CloudWatch

Monitoring:
- Alert if token used more than 5 times per hour (fraud detection)
- Alert if token accessed by unauthorized service
- Weekly audit log review

References:
- PCI DSS Tokenization Guidelines: https://www.pcisecuritystandards.org/documents/Tokenization_Guidelines_Info_Supplement.pdf
- Stripe Security: https://stripe.com/docs/security/stripe
- Our Security Policy: docs/security-policy.md

Code Implementation:
- api/services/payments.py:45-120
- database/schema.sql:234-245 (payment_methods table)

Git Commit:
- Initial implementation: abc1234
- Security review updates: def5678

Approved By:
- Alice Chen (CTO) - 2025-10-15
- Bob Smith (Security Lead) - 2025-10-15
- External Security Auditor - 2025-10-16

Audit Notes:
This decision satisfies PCI DSS Requirements 3.2 (card data storage) and 4.1 (encryption in transit).
"
```

**Step 3: Auditor Queries the Decision**

6 months later, during SOC 2 audit:

**Auditor**: "Why did you choose to store payment tokens in Postgres? Document your risk assessment."

**Engineering Team**:
```bash
clauxton kb search "credit card token storage"
```

**Output**: Full decision document with:
- ✅ Risk assessment (HIGH/MEDIUM/LOW)
- ✅ Alternatives considered
- ✅ Compliance reasoning
- ✅ Approval signatures
- ✅ Git commit references

**Auditor**: "Perfect. This satisfies our documentation requirements."

**Result**: **Audit passed** - no delays in funding round

**Step 4: GDPR Data Processing Decision**

**Example**: User data retention policy

```bash
clauxton kb add \
  --title "GDPR Compliance: User Data Retention Policy" \
  --category privacy \
  --tags "gdpr,privacy,data-retention,compliance" \
  --content "Decision: Retain user account data for 7 years after account deletion, anonymize after 30 days.

Context:
- Requirement: GDPR Right to Erasure (Article 17)
- Requirement: Financial regulations (7-year retention for tax purposes)
- Conflict: GDPR requires deletion, but tax law requires retention

Legal Basis:
- GDPR Article 17(3)(b): Retention allowed for compliance with legal obligation
- Tax law: 7-year retention for financial transactions

Decision:
1. Upon account deletion request:
   - Immediately anonymize PII (name, email, phone)
   - Retain anonymized transaction data for 7 years (tax compliance)
   - Delete all other data within 30 days

2. Anonymization Process:
   - name → 'User-[random-id]'
   - email → '[random]@deleted.example.com'
   - phone → NULL
   - Retain: transaction amounts, dates (for tax reporting)

3. Data Deletion Schedule:
   - Day 0: User requests deletion
   - Day 1: Anonymize PII (automated job)
   - Day 30: Delete all non-essential data (soft delete)
   - Year 7: Hard delete all data (automated purge)

Implementation:
- Cron job: anonymize_deleted_users.py (runs daily)
- Cron job: purge_old_data.py (runs yearly)
- Database: deleted_at timestamp on users table
- Audit log: All deletions logged for GDPR proof

GDPR Article 30 Records:
- Purpose: Fulfill tax obligations while respecting right to erasure
- Legal basis: Article 17(3)(b) - compliance with legal obligation
- Data subjects: EU users only
- Recipients: Internal finance team, tax authorities
- Transfers: None (data stays in EU)
- Retention period: 7 years post-deletion

References:
- GDPR Article 17: https://gdpr-info.eu/art-17-gdpr/
- Tax retention requirements: docs/compliance/tax-law.md

Approved By:
- Legal Counsel - 2025-10-15
- DPO (Data Protection Officer) - 2025-10-15
- CTO - 2025-10-15
"
```

**Step 5: Git Integration for Audit Trail**

All KB entries are Git-tracked:

```bash
git log .clauxton/knowledge-base.yml --oneline
```

**Output**:
```
abc1234 docs: Add credit card token storage decision
def5678 docs: Update token storage with security review feedback
ghi9012 docs: Add GDPR data retention policy
```

Auditors can trace every decision to specific Git commits and timestamps.

#### Best Practices for Enterprise Compliance

1. **Mandatory KB Entry for Security Decisions**: Policy requirement
   ```markdown
   ## Security Review Checklist
   - [ ] Clauxton KB entry created (category: security)
   - [ ] Risk assessment documented (HIGH/MEDIUM/LOW)
   - [ ] Alternatives considered
   - [ ] Approvals documented (CTO, Security Lead)
   ```

2. **Use Descriptive Categories**: Map to compliance frameworks
   - `security` → SOC 2 CC6 (Logical and Physical Access Controls)
   - `privacy` → GDPR Articles
   - `payment` → PCI DSS Requirements
   - `encryption` → SOC 2 CC6.7

3. **Include Approval Signatures**: Auditors need names and dates
   ```
   Approved By:
   - [Name] ([Title]) - [Date]
   ```

4. **Link to Git Commits**: Tie decisions to code changes
   ```
   Git Commit: abc1234
   ```

5. **Quarterly Compliance KB Review**: Ensure up-to-date
   - Legal team reviews privacy entries
   - Security team reviews security entries
   - Update outdated policies

6. **Export KB for Auditors**: Provide full documentation package
   ```bash
   clauxton kb list --format json > audit-decisions.json
   ```

#### Results for FinTech Startup

**Before Clauxton**:
- Documentation for audits: Ad-hoc (Google Docs, wikis, scattered)
- Time to prepare for audit: 2-3 weeks (scrambling to document decisions)
- Audit findings: 5-8 documentation gaps per audit
- Risk: Delayed funding round due to compliance issues

**After Clauxton** (1 year):
- Documentation for audits: Centralized, Git-tracked, timestamped
- Time to prepare for audit: 2-3 days (mostly exporting KB)
- Audit findings: 0-1 documentation gaps per audit (95% reduction)
- Risk: Low - auditors consistently satisfied
- Funding round: Closed Series B without compliance delays

**ROI**:
- Audit prep time saved: 2 weeks per audit × 2 audits/year = **4 weeks saved**
- Risk reduction: **Avoided funding delays** (worth millions)
- Compliance confidence: Team can focus on building, not scrambling for docs

---

### 5. Education & Learning - Learning Journal

#### Persona

**Name**: Jamie, Computer Science Student
**Learning**: Full-stack web development (self-paced online courses)
**Pain Point**: Forgets concepts after a few weeks, no organized notes

#### Problem Statement

Jamie is learning web development through:
- Online courses (Udemy, Coursera)
- YouTube tutorials
- Personal projects
- LeetCode practice

**Learning Challenges**:
1. **Scattered Notes**: Google Docs, notebook, screenshots - hard to find
2. **Forgetting Concepts**: Learned React hooks 2 months ago, can't remember `useEffect` cleanup
3. **No Progress Tracking**: Hard to measure what's been learned
4. **Interview Prep**: Can't quickly review key concepts before interviews

**Quote from Jamie**: *"I know I learned about database indexing somewhere, but I can't find my notes. Now I have to re-watch a 2-hour video."*

#### How Clauxton Helps

Clauxton becomes Jamie's **personal learning journal**:

1. **Centralized Knowledge Base**: All learnings in one searchable place
2. **TF-IDF Search**: Find concepts instantly (e.g., "React useEffect cleanup")
3. **Task Management**: Track learning goals and milestones
4. **Spaced Repetition**: Review past entries before interviews

#### Implementation Steps

**Step 1: Initialize Learning Journal**

```bash
mkdir ~/learning-journal
cd ~/learning-journal
clauxton init

# Create learning log
echo "# My Learning Journey with Clauxton" > README.md
```

**Step 2: Document Concepts as You Learn Them**

**Example 1**: Learning React Hooks

Jamie watches a React hooks tutorial:

```bash
clauxton kb add \
  --title "React useEffect Hook - Cleanup Functions" \
  --category react \
  --tags "react,hooks,useEffect,cleanup,memory-leaks" \
  --content "Concept: useEffect cleanup functions prevent memory leaks.

What I Learned:
- useEffect can return a cleanup function
- Cleanup runs BEFORE next effect and on unmount
- Use cleanup to cancel subscriptions, timers, event listeners

Example:
useEffect(() => {
  // Setup
  const timer = setInterval(() => console.log('tick'), 1000);

  // Cleanup function
  return () => {
    clearInterval(timer);  // Cancel timer on unmount
  };
}, []);  // Empty deps = run once

Why It Matters:
- Without cleanup: timer keeps running after component unmounts
- Result: Memory leak + console spam
- With cleanup: timer stopped when component unmounts

Common Use Cases:
1. Event listeners: addEventListener → removeEventListener
2. Timers: setInterval → clearInterval
3. Subscriptions: subscribe → unsubscribe
4. Fetch requests: AbortController

Code Example:
https://github.com/jamie-learning/react-practice/blob/main/src/TimerComponent.js

Practice Project:
Built a chat app component that subscribes to WebSocket.
Used cleanup to close WebSocket on unmount.

Date: 2025-10-15
Source: React docs + Dave Gray YouTube tutorial
"
```

**Example 2**: Learning SQL Indexing

Jamie learns about database indexes:

```bash
clauxton kb add \
  --title "SQL Database Indexes - When to Use" \
  --category database \
  --tags "sql,postgres,indexes,performance,optimization" \
  --content "Concept: Indexes speed up SELECT queries but slow down INSERT/UPDATE.

What I Learned:
- Index = data structure (B-tree) for fast lookups
- Like a book index: jump to page instead of reading whole book
- Tradeoff: Faster reads, slower writes

When to Use Index:
✅ Columns used in WHERE clauses frequently
✅ Columns used in JOIN conditions
✅ Columns used in ORDER BY

When NOT to Use Index:
❌ Small tables (<1000 rows) - full scan is fast enough
❌ Columns with many duplicates (e.g., boolean fields)
❌ Tables with frequent INSERT/UPDATE (index overhead)

Example - Before Index:
SELECT * FROM users WHERE email = 'jamie@example.com';
-- Query time: 450ms (full table scan)

Example - After Index:
CREATE INDEX idx_users_email ON users(email);
SELECT * FROM users WHERE email = 'jamie@example.com';
-- Query time: 12ms (index lookup)

37x faster!

Common Mistakes:
1. Over-indexing: Don't index everything (slows INSERT)
2. Forgetting to index foreign keys (JOIN performance)
3. Not using composite indexes for multi-column queries

Practice:
Built a blog app with 100k posts.
Added index on posts.published_at (used in ORDER BY).
Query time: 1200ms → 45ms (26x faster).

Code:
https://github.com/jamie-learning/blog-app/blob/main/migrations/003_add_indexes.sql

Date: 2025-10-16
Source: Database course + PostgreSQL documentation
"
```

**Step 3: Track Learning Goals with Tasks**

Jamie creates learning milestones:

```bash
# Goal 1: Master React
clauxton task add \
  --title "Complete React course and build project" \
  --priority high \
  --estimate 40h \
  --status in-progress

# Subtask 1
clauxton task add \
  --title "Learn React Hooks (useState, useEffect, custom hooks)" \
  --priority high \
  --estimate 8h \
  --depends-on "Complete React course and build project" \
  --status completed

# Subtask 2
clauxton task add \
  --title "Build full-stack React + Node.js app (CRUD)" \
  --priority high \
  --estimate 20h \
  --depends-on "Learn React Hooks" \
  --status in-progress

# Goal 2: Learn SQL
clauxton task add \
  --title "Complete SQL course and practice 50 LeetCode problems" \
  --priority medium \
  --estimate 30h \
  --status pending
```

**Step 4: Search Before Re-Learning**

2 months later, Jamie forgets how cleanup works:

```bash
clauxton kb search "useEffect cleanup"
```

**Output**:
```
Found 1 entry:

[1] KB-20251015-012 (Score: 0.96)
Title: React useEffect Hook - Cleanup Functions
Category: react
Tags: react, hooks, useEffect, cleanup, memory-leaks

Concept: useEffect cleanup functions prevent memory leaks.

useEffect(() => {
  const timer = setInterval(() => console.log('tick'), 1000);
  return () => clearInterval(timer);  // Cleanup
}, []);
...
```

**Result**: Jamie remembers the concept in 30 seconds instead of re-watching a 20-minute video.

**Time Saved**: 19.5 minutes

**Step 5: Interview Prep - Review Key Concepts**

Jamie has a technical interview tomorrow:

```bash
# Review React concepts
clauxton kb list --category react

# Review database concepts
clauxton kb list --category database

# Review algorithm concepts
clauxton kb list --category algorithms
```

**Output** (React category):
```
Category: react (5 entries)

[1] KB-20251015-012 - React useEffect Hook - Cleanup Functions
[2] KB-20251016-003 - React Context API vs. Redux
[3] KB-20251017-005 - React.memo and useMemo for Performance
[4] KB-20251018-008 - React Custom Hooks - Best Practices
[5] KB-20251019-011 - React Error Boundaries
```

Jamie reviews all 5 entries in 15 minutes - ready for interview.

**Step 6: Track Progress Over Time**

Jamie checks learning progress:

```bash
clauxton task list --status completed
```

**Output**:
```
Completed Tasks (12):

✅ Learn React Hooks (completed 2025-10-15)
✅ Build CRUD app with React (completed 2025-10-18)
✅ Complete SQL basics course (completed 2025-10-20)
✅ Solve 20 LeetCode Easy problems (completed 2025-10-22)
...
```

**Result**: Jamie can see tangible progress - motivating!

#### Best Practices for Students

1. **Document Immediately After Learning**: Don't wait
   - ✅ Right after tutorial: `clauxton kb add ...`
   - ❌ "I'll document everything next weekend" (never happens)

2. **Use Simple Categories**: Match your learning areas
   - `react`, `database`, `algorithms`, `nodejs`, `python`

3. **Include Code Examples**: Future you needs working code
   ```bash
   clauxton kb add --content "
   Example:
   function debounce(fn, delay) {
     let timer;
     return (...args) => {
       clearTimeout(timer);
       timer = setTimeout(() => fn(...args), delay);
     };
   }
   "
   ```

4. **Link to Practice Projects**: Context helps memory
   ```
   Practice Project: https://github.com/jamie/my-project
   ```

5. **Review Before Interviews**: Spaced repetition
   ```bash
   clauxton kb list --category algorithms
   ```

6. **Track Learning Goals**: Measure progress
   ```bash
   clauxton task add "Complete React course" --estimate 40h
   ```

#### Results for Jamie

**Before Clauxton**:
- Notes: Scattered (Google Docs, notebooks, screenshots)
- Time to find a concept: 10-30 minutes (often can't find it)
- Re-learning frequency: 40-50% of concepts
- Interview prep: Stressful (can't find notes)
- Progress tracking: None (hard to stay motivated)

**After Clauxton** (6 months):
- Notes: Centralized, searchable (one `clauxton kb search`)
- Time to find a concept: 30 seconds - **95% faster**
- Re-learning frequency: 5-10% (search KB first)
- Interview prep: Confident (review all concepts in 20 min)
- Progress tracking: Clear (`clauxton task list --status completed`)

**Learning ROI**:
- Time saved per week: 2-3 hours (not re-learning)
- Interview success: Landed 2 internships (confident knowledge review)
- Motivation: High (visible progress tracking)

**Quote from Jamie** (6 months later):
> "Clauxton changed how I learn. I used to forget everything after a few weeks. Now I have a searchable 'second brain' of everything I've learned. I can review React hooks in 30 seconds before an interview instead of panic-watching videos."

---

## Additional Use Cases

Beyond the 5 core use cases above, Clauxton is valuable for:

### 6. API Development & Documentation

**Use Case**: Backend team documents API design decisions
- Why certain endpoints are RESTful vs. GraphQL
- Authentication choices (JWT vs. session cookies)
- Rate limiting strategies
- Versioning approach

**KB Entry Example**:
```bash
clauxton kb add \
  --title "API Versioning: URL-based vs. Header-based" \
  --category api \
  --tags "api,versioning,rest" \
  --content "Decision: Use URL-based versioning (/v1/, /v2/).

Reasoning:
- Easier for clients to understand
- Clear in browser/curl (no header manipulation)
- Caching-friendly (CDN can cache per version)

Alternatives:
- Header-based (Accept: application/vnd.api+json;version=1)
  Rejected: Harder for clients, cache complexity
"
```

### 7. DevOps & Infrastructure Decisions

**Use Case**: DevOps team documents infrastructure choices
- Why Kubernetes over Docker Swarm
- Database replication strategy
- Backup and disaster recovery approach
- Monitoring stack selection

**KB Entry Example**:
```bash
clauxton kb add \
  --title "Infrastructure: Why We Chose AWS over GCP" \
  --category devops \
  --tags "cloud,aws,gcp,infrastructure" \
  --content "Decision: AWS for production infrastructure.

Reasoning:
- Team has 5 years AWS experience (GCP = learning curve)
- Better third-party integrations (Stripe, SendGrid)
- Cost: Similar to GCP for our workload
- Region coverage: 8 regions vs. GCP's 5 in our target markets

When to Revisit:
- If team grows and brings GCP expertise
- If Google Cloud costs drop significantly
- If multi-cloud strategy becomes necessary
"
```

### 8. Security Practices & Threat Modeling

**Use Case**: Security team documents threat models and mitigations
- Why rate limiting is implemented a certain way
- SQL injection prevention strategy
- Authentication flow security analysis

**KB Entry Example**:
```bash
clauxton kb add \
  --title "Security: Rate Limiting Strategy for API" \
  --category security \
  --tags "security,rate-limiting,ddos,api" \
  --content "Decision: Token bucket algorithm with per-user and per-IP limits.

Threat Mitigated:
- DDoS attacks (per-IP limit: 1000 req/min)
- API abuse (per-user limit: 100 req/min)

Implementation:
- Redis-based rate limiter (fast, distributed)
- 429 status code with Retry-After header

Why Token Bucket:
- Allows bursts (better UX than fixed window)
- Industry standard (used by AWS, Stripe)
"
```

### 9. Product Development & Feature Decisions

**Use Case**: Product team documents feature prioritization and A/B test results
- Why Feature X was prioritized over Feature Y
- A/B test results and learnings
- User feedback synthesis

**KB Entry Example**:
```bash
clauxton kb add \
  --title "Product: Why We Removed the 'Share' Button from Dashboard" \
  --category product \
  --tags "product,features,a-b-test,ux" \
  --content "Decision: Remove 'Share' button from main dashboard.

A/B Test Results:
- Used by only 2% of users
- 15% found it confusing (user interviews)
- Removed button = 8% increase in core feature usage (less distraction)

Lesson:
- Not all features add value
- Less is more for UX
- Test before assuming users want features
"
```

### 10. Microservices Architecture Decisions

**Use Case**: Engineering team documents service boundaries and communication patterns
- Why Service X communicates via REST vs. gRPC
- Event-driven patterns vs. synchronous calls
- Service ownership and responsibilities

**KB Entry Example**:
```bash
clauxton kb add \
  --title "Microservices: Payment Service Communication Pattern" \
  --category architecture \
  --tags "microservices,grpc,rest,architecture" \
  --content "Decision: Payment Service uses gRPC for internal communication, REST for external.

Reasoning:
Internal (service-to-service):
- gRPC: 5-10x faster than REST (protobuf vs JSON)
- Type safety (protobuf schemas)
- Bi-directional streaming (real-time payment status)

External (client-to-service):
- REST: Better browser/mobile support
- Easier debugging (curl, Postman)
- More developer-friendly for third-party integrations

Implementation:
- gRPC server: payment-service:50051
- REST proxy: payment-api:8080 (translates REST → gRPC)
"
```

---

## Getting Started

### For Solo Developers

1. **Initialize Clauxton in your project**:
   ```bash
   cd ~/projects/my-project
   clauxton init
   ```

2. **Document your next architectural decision**:
   ```bash
   clauxton kb add \
     --title "Your Decision Title" \
     --category architecture \
     --tags "relevant,tags" \
     --content "Decision + Reasoning + Alternatives"
   ```

3. **Set up MCP** in Claude Code (see [MCP Setup Guide](mcp-server-guide.md))

4. **Search before coding**:
   ```bash
   clauxton kb search "your topic"
   ```

### For Teams

1. **Initialize in shared repo**:
   ```bash
   git clone <your-repo>
   cd <your-repo>
   clauxton init
   git add .clauxton/
   git commit -m "feat: Initialize Clauxton KB"
   git push
   ```

2. **Add to CONTRIBUTING.md**:
   ```markdown
   ## Knowledge Base

   Search before coding:
   clauxton kb search "your topic"

   Document decisions:
   clauxton kb add --title "..." --category ... --content "..."
   ```

3. **Establish team norms**:
   - Weekly KB review in standup
   - Mandatory KB entry for architectural decisions
   - Search before asking in Slack

### For Open Source Maintainers

1. **Document top 10 architecture decisions** (4-6 hour investment)
2. **Add KB section to CONTRIBUTING.md** with search examples
3. **Link from PR template**: "Did you search the KB?"

### For Students

1. **Create learning journal**:
   ```bash
   mkdir ~/learning-journal
   cd ~/learning-journal
   clauxton init
   ```

2. **Document after each tutorial/course**:
   ```bash
   clauxton kb add --title "Concept I Learned" ...
   ```

3. **Review before interviews**:
   ```bash
   clauxton kb list --category react
   ```

---

## Tips for All Use Cases

### Effective KB Entries

**DO**:
- ✅ Document decisions immediately (while context is fresh)
- ✅ Include "Why" and "Alternatives Considered"
- ✅ Use descriptive tags for searchability
- ✅ Link to code/commits/docs
- ✅ Update entries when decisions change

**DON'T**:
- ❌ Document just "what" without "why"
- ❌ Wait until end of week to document (you'll forget)
- ❌ Use vague tags like "misc" or "other"
- ❌ Leave entries outdated (mark deprecated)

### Effective Searching

**Use TF-IDF Search**:
```bash
# Good queries (specific terms)
clauxton kb search "webhook retry exponential backoff"
clauxton kb search "postgres index performance"
clauxton kb search "react useEffect cleanup function"

# Less effective (too broad)
clauxton kb search "api"
clauxton kb search "database"
```

### Task Management Best Practices

1. **Use Dependencies**: Prevent conflicts
   ```bash
   clauxton task add "Task B" --depends-on "Task A"
   ```

2. **Estimate Realistically**: Use for planning
   ```bash
   clauxton task add "Build feature" --estimate 8h
   ```

3. **Check Before Starting**: What can I work on?
   ```bash
   clauxton task next
   ```

### MCP Integration Tips

**Configure Once, Use Everywhere**:
```json
{
  "mcpServers": {
    "clauxton": {
      "command": "clauxton",
      "args": ["mcp"]
    }
  }
}
```

**Ask Claude**:
- "Search the KB for webhook retry strategies"
- "What tasks can I work on next?"
- "Show me all architecture decisions"

Claude Code will use Clauxton tools automatically.

---

## Resources

### Documentation

- **Quick Start**: [docs/quick-start.md](quick-start.md)
- **Tutorial** (30 min): [docs/tutorial-first-kb.md](tutorial-first-kb.md)
- **MCP Setup**: [docs/mcp-server-guide.md](mcp-server-guide.md)
- **Task Management**: [docs/task-management-guide.md](task-management-guide.md)
- **Best Practices**: [docs/best-practices.md](best-practices.md)

### Installation

```bash
# PyPI (recommended)
pip install clauxton

# Source
git clone https://github.com/nakishiyaman/clauxton.git
cd clauxton
pip install -e .
```

### CLI Reference

```bash
# Knowledge Base
clauxton kb add --title "..." --category ... --content "..."
clauxton kb search "query"
clauxton kb get KB-20251019-001
clauxton kb list --category architecture

# Task Management
clauxton task add "Task" --priority high --estimate 4h
clauxton task list --status pending
clauxton task next
clauxton task status TASK-001 --status completed

# MCP Server
clauxton mcp  # Starts MCP server for Claude Code
```

### Community

- **GitHub**: [github.com/nakishiyaman/clauxton](https://github.com/nakishiyaman/clauxton)
- **Issues**: [Report bugs or request features](https://github.com/nakishiyaman/clauxton/issues)
- **Discussions**: [Ask questions](https://github.com/nakishiyaman/clauxton/discussions)

---

## Conclusion

Clauxton solves the **context loss problem** that affects developers, teams, and learners:

1. **Solo Developers**: Never forget project decisions (save 2+ hours/week)
2. **Teams**: Shared context reduces repeated questions (save 3-4 hours/week per team)
3. **Open Source**: Contributor context reduces PR review cycles (save 5-6 hours/week)
4. **Enterprise**: Compliance audit trail (save 2-3 weeks per audit)
5. **Students**: Learning journal prevents re-learning (save 2-3 hours/week)

**Start today**:
```bash
pip install clauxton
clauxton init
clauxton kb add --title "My First Decision" ...
```

Your future self (and your team) will thank you.

---

**Questions?** Open an issue or discussion on GitHub!
