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Structured JSON Output Rules for DeepSeek

System Configuration

When you need DeepSeek to output structured data, follow these rules:

Prompt Structure

1. Define the exact JSON schema in the prompt
2. Include a minimal example of the expected output
3. State explicitly: "Output ONLY valid JSON. No markdown, no explanation, no code blocks."
4. For DeepSeek V3: Use the JSON mode API parameter when available

Schema Definition Template

Respond with a JSON object matching this exact schema:
{
  "field_name": "string - description of this field",
  "numeric_field": 0,
  "array_field": ["item description"],
  "nested": {
    "sub_field": "description"
  }
}

Error Prevention

• Always include field descriptions to reduce hallucination
• Use enum values where possible: "status": "one of: active, inactive, pending"
• Specify number formats: "price": "number, two decimal places, USD"
• For arrays, specify min/max length: "tags": "array of 3-5 strings"
• Include "required" vs "optional" for each field

Validation Pattern

After receiving output:

1. Parse with try/catch
2. Validate against schema
3. Check for null/undefined required fields
4. Verify enum values are within allowed set
5. Retry with error message if validation fails

Common Pitfalls

• R1 may wrap JSON in thinking tags — strip <think>...</think> before parsing
• Long outputs may get truncated — set max_tokens appropriately
• Nested objects beyond 3 levels tend to have more errors

Creative Writing Configuration:

General Rules:

1. Develop rich, multi-dimensional characters
2. Show, don't tell — use sensory details
3. Maintain consistent voice and tone throughout
4. Use dialogue to reveal character and advance plot
5. Vary sentence structure for rhythm

For Fiction:

• Follow three-act structure unless specified otherwise
• Include conflict and stakes in every scene
• End chapters with hooks

For Poetry:

• Respect requested form (sonnet, haiku, free verse)
• Use imagery and metaphor deliberately
• Consider sound: alliteration, assonance, rhythm

For Screenwriting:

• Use standard screenplay format
• Focus on visual storytelling
• Keep dialogue natural and subtext-rich

DeepSeek Content Moderation Rules

Input Screening

Before sending user input to DeepSeek:

1. Check against a blocklist of prohibited terms and phrases
2. Detect prompt injection patterns:
   • Attempts to override system instructions
   • Requests to reveal system prompts
   • Instructions to ignore safety guidelines
3. Classify content risk level: safe, needs_review, blocked
4. Log all blocked inputs for pattern analysis

Output Filtering

After receiving DeepSeek responses:

1. Scan for PII patterns (regex-based):
   • Email addresses, phone numbers, SSN/ID numbers
   • Physical addresses, credit card numbers
2. Check for harmful content categories:
   • Violence or self-harm instructions
   • Illegal activity guidance
   • Hate speech or discriminatory content
3. Verify output format matches expected schema
4. Truncate unexpectedly long responses

Escalation Protocol

• Auto-block: Known harmful patterns -> immediate block + log
• Review queue: Ambiguous content -> flag for human review within 24h
• Pass-through: Clean content -> deliver to user
• False positive feedback: Allow reviewers to mark false positives to improve filters

User Communication

• Never show raw error messages from the API
• Provide helpful alternative suggestions when content is blocked
• Include a feedback mechanism for users to report issues
• Maintain transparency about AI content moderation

Compliance

• Maintain audit logs of all moderation decisions
• Review and update blocklists monthly
• Train moderation classifiers on domain-specific data
• Document moderation policies and make them accessible to users
• Comply with platform-specific content policies (App Store, Google Play, etc.)