Claude Prompt Engineering for Indian Business Use Cases

Claude Opus 4.6 is a frontier model, but its real value is unlocked when you prompt it in a structured way. Indian use cases add an extra layer: languages mix, cultural context matters, and business documents follow local formats. This guide covers the patterns that work.

The Anthropic Prompt Template

Anthropic's recommended format uses XML tags:

<role>
You are a legal analyst specializing in Indian contract law.
</role>

<context>
I'm a freelancer being asked to sign an NDA with a Bangalore startup.
The NDA covers 5 years post-termination.
</context>

<task>
Review the attached NDA and flag:
1. Unusual clauses for the Indian context
2. Terms against the freelancer's interests
3. Specific negotiation points
</task>

<output_format>
Return as markdown:
- ## Executive Summary (2-3 lines)
- ## Red Flags (bulleted)
- ## Suggested Edits (clause-by-clause)
- ## Negotiation Script (sample email to founder)
</output_format>

<document>
[paste NDA text]
</document>

XML tags help Claude parse the prompt cleanly. GPT-style system prompts also work, but XML is Anthropic-native.

Pattern 1 — Professional English Output

For Indian business audiences, professional English with regional context works best:

Respond in clear, professional English.
Use Indian examples (cities, companies, currencies in INR) where relevant.
Tone: conversational but professional, as if explaining to a colleague.

This produces clean, accessible output suitable for most Indian business contexts.

Pattern 2 — Indic Language Native

For pure Hindi or regional content (e.g., when using Sarvam or native-language use cases):

Entire response must be in Hindi (Devanagari script).
Use the formal "aap" register, suitable for business contexts.
Avoid transliterated English words where natural Hindi exists.
Length: 300-400 words.

For truly native fluency in Hindi, Sarvam AI is the better tool. Claude handles Hindi well, but not at Sarvam-grade fluency.

Pattern 3 — Structured Business Output

For invoice analysis, contract review, or financial summaries:

<output_format>
Return JSON:
{
  "summary": "2-line exec summary",
  "redFlags": [{"clause": "...", "severity": "high|medium|low", "reason": "..."}],
  "suggestedEdits": [{"original": "...", "proposed": "..."}],
  "overallRecommendation": "proceed|negotiate|reject"
}
</output_format>

Structured output drops directly into your code.

Pattern 4 — Long Document Handling

The 1M context window is Claude Opus 4.6's edge. For large docs:

<instruction>
I'm attaching a 200-page contract.
DO NOT summarize the entire document.
Instead, find these 5 specific items and quote the relevant section verbatim:

1. Termination conditions
2. Auto-renewal clauses
3. Liability caps (in INR if specified)
4. IP assignment terms
5. Dispute resolution jurisdiction

Return each as:
## [Item Name]
> [verbatim quote]
**Page**: [number]
**Interpretation**: [1-2 line plain English]
</instruction>

Specific extraction beats vague summaries.

Pattern 5 — Chain-of-Thought For Indian Legal

For complex queries (tax, compliance, labour law):

<task>
Walk me through whether I can hire a contractor in Dubai while being a registered Indian LLP.
</task>

<thinking_style>
Before answering, think through:
1. FEMA implications
2. GST on cross-border services
3. TDS obligations under Section 195
4. Treaty benefits (India-UAE DTAA)

Show your reasoning step-by-step, then give a final checklist.
Flag anywhere a CA / CS should confirm.
</thinking_style>

Pattern 6 — Persona Consistency

For ongoing agents (blog writer, customer support), define a persona:

<persona>
Name: Asha
Role: Customer support agent for TaxWalaAI
Tone: Warm, patient, technically precise
Always: use formal English; offer to switch to Hindi/Tamil/Telugu if the user indicates preference
Never: use Western-centric examples (use INR, Indian cities, Indian cultural references)
Signature: always end with "— Asha, TaxWalaAI team"
</persona>

Inject this persona at the start of each conversation for consistency.

Pattern 7 — Safety Rails For The Indian Context

Certain topics need extra care:

• Religious / political opinions
• Regional stereotypes
• Caste references
• Bollywood celebrities (defamation risk)

Add instructions like:

Do not make statements about specific individuals that could be defamatory under Indian law.
If asked about political parties or religious groups, provide only factual information with sources.

Debugging Prompts

Output not what you expected? Check these first:

1. Temperature — Claude Code defaults to 0, which works for most tasks. For creative work, go to 0.7+
2. Task specificity — "Write a marketing email" vs "Write a 120-word marketing email for a B2B SaaS launch in Bangalore"
3. Examples — one or two (few-shot) examples pin down the output format

Claude's full API docs: docs.anthropic.com. For the terminal use case, see Claude Code setup.