# Data retention archiving planner Human Guide

## What This Is For
Manage data lifecycle with automated retention and archiving. It gives the agent a clearer input/output frame for data retention archiving planner: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the Data retention archiving planner agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for data retention archiving planner.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the Data retention archiving planner guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- **Define clear policies**: Document retention periods
- **Automate everything**: Manual cleanup is unreliable
- **Test restore**: Regularly test archive restoration
- **Monitor job health**: Alert on failures
- **Compliance first**: Meet legal requirements
- **Soft delete**: Before hard delete
- **Batch operations**: Avoid locking tables
- [ ] Retention policy documented
- [ ] Archival jobs implemented
- [ ] Soft delete pattern (if applicable)
- [ ] GDPR compliance (right to be forgotten)
- [ ] Job scheduling configured

## Decision Points And Nuance
The original skill emphasizes: Retention Policy Document, Retention Periods, Compliance Requirements, GDPR (EU), HIPAA (Healthcare), SOX (Financial), PCI DSS (Payments), Archive Schema Design, Archival Job Implementation, Automated Cleanup Jobs.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- Secure archival required
- **Batch operations**: Avoid locking tables

## Copy-And-Paste Prompt
```text
Use the Data retention archiving planner human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the patricio0312rev/skills skill entry for `data-retention-archiving-planner`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# Data Retention & Archiving Planner

Manage data lifecycle with automated retention and archiving.

## Retention Policy Document

```markdown
# Data Retention Policy

## Retention Periods

| Data Type             | Hot Storage | Cold Storage | Total Retention | Reason            |
| --------------------- | ----------- | ------------ | --------------- | ----------------- |
| User accounts         | Active      | N/A          | Indefinite      | Business need     |
| Order history         | 2 years     | 5 years      | 7 years         | Tax compliance    |
| Logs                  | 30 days     | 90 days      | 120 days        | Operational       |
| Analytics events      | 90 days     | 1 year       | 15 months       | Business insights |
| Audit trails          | 1 year      | 6 years      | 7 years         | Legal compliance  |
| User sessions         | 30 days     | None         | 30 days         | Security          |
| Failed login attempts | 90 days     | None         | 90 days         | Security          |

## Compliance Requirements

### GDPR (EU)

- Right to erasure (right to be forgotten)
- Data minimization
- Storage limitation

### HIPAA (Healthcare)

- Minimum 6 years retention
- Secure archival required

### SOX (Financial)

- 7 years retention for financial records
- Immutable audit trails

### PCI DSS (Payments)

- 1 year minimum for audit logs
- 3 months minimum for transaction logs
```

## Archive Schema Design

```sql
-- Hot database: Current active data
CREATE TABLE orders (
  id BIGSERIAL PRIMARY KEY,
  user_id BIGINT NOT NULL,
  total DECIMAL(10,2) NOT NULL,
  status TEXT NOT NULL,
  created_at TIMESTAMP NOT NULL DEFAULT NOW(),
  updated_at TIMESTAMP NOT NULL DEFAULT NOW()
);

-- Cold database: Archived historical data
CREATE TABLE orders_archive (
  id BIGINT PRIMARY KEY,
  user_id BIGINT NOT NULL,
  total DECIMAL(10,2) NOT NULL,
  status TEXT NOT NULL,
  created_at TIMESTAMP NOT NULL,
  updated_at TIMESTAMP NOT NULL,
  archived_at TIMESTAMP NOT NULL DEFAULT NOW()
);

-- Create partition for time-based archival
CREATE TABLE orders_2024_q1 PARTITION OF orders
  FOR VALUES FROM ('2024-01-01') TO ('2024-04-01');

CREATE TABLE orders_2024_q2 PARTITION OF orders
  FOR VALUES FROM ('2024-04-01') TO ('2024-07-01');
```

## Archival Job Implementation

```typescript