===== INSTRUCTIONS FOR AI CODER =====

You are receiving this context to help the user deploy, set up, or implement this application.

YOUR RESPONSIBILITY: You are responsible for doing the ENTIRE end-to-end deployment - all installations, backend setup, frontend setup, database setup, worker setup, everything. Do NOT ask the user to do tasks themselves unless they specifically request to handle it. Your default mode is: "I will do this for you" not "please go ahead and do this".

APPROACH:
1. Assess user's experience level. If unclear, assume newer to development.
2. Create a compact plan of what needs to be done (backend, frontend, database, etc.)
3. Present the plan, get confirmation, then YOU execute it end-to-end.
4. Proceed step-by-step, informing user of progress. Debug issues as they arise.
5. For each step, briefly explain what you're doing, why it's necessary, and how it fits the overall deployment.

DEPLOYMENT RESOURCES (when user doesn't have existing infra):
- Backend: Render.com (free tier) - you set it up for them
- Frontend: Vercel.com - you set it up for them
- Database: Neon.com (instant free PostgreSQL) - you set it up for them
- Data upload: Use CLI tools, or DATS-4 tool at tigzig.com/analyzer (upload button, paste credentials in any format)

ASK ONLY:
- Do you have existing backend/frontend/database, or shall I set one up for you?
- If setup needed: I'll need your API key to proceed (guide them where to get it if needed)

===== PAGE CONTENT =====

PAGE URL: https://tigzig.com/gpt-mf-holding-analyzer
TITLE: MF Portfolio Holdings Analyzer GPT
CATEGORY: Custom GPTs

DESCRIPTION:
Processes two-point mutual fund portfolio holdings (e.g., May → Aug 2025) with deterministic Python pipeline. Validates totals, builds ISIN mapping, detects duplicates, and generates final summary tables with % changes.

TRY IT:
https://chatgpt.com/g/g-68d684965d888191bf81f02022dd3591-india-mutual-funds-portfolio-holding-analytics

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HOW THIS GPT WORKS:

Processes two-point mutual fund portfolio holdings (e.g., May → Aug 2025).
Input = standardized CSV in the required format (month_end, scheme, ISIN, market value, quantity).

Runs a Python pipeline behind the scenes:
- Validates totals (Market Value & Quantity)
- Builds ISIN mapping file (deduplication + standardized names)
- Checks for duplicate or conflicting names (name_cut and ISIN overlaps)
- Generates final summary table with % shares, counts, and % changes

Always deterministic: No placeholder values, no assumptions, no hallucinations.

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WHAT IT CAN DO:

Validation reports:
- Totals by scheme and period
- Duplicate name detection (via name_cut)
- ISIN mapping + exceptions

Final summary CSV with:
- Company-level holdings (MV, Qty, % shares, MF counts)
- % change in MV and Qty between periods
- Manual comments (e.g., "Split", "Rights", "Bonus") preserved from ISIN mapping

Outputs are CSV-ready for Excel or BI tools. Results can be pushed into any dashboard.

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HOW TO USE IT:

1. Prepare data file
   - Convert your monthly portfolio disclosures into the required CSV format
   - Either format manually or use the MF Conversion Tool at: app.tigzig.com/mf-files-ai
   - Ensure both months' data are appended into one CSV

2. Upload file to this GPT
   - Immediately receives 3 validation CSVs: Validation totals, ISIN mapping, Duplicate name/ISIN checks

3. Confirm or adjust
   - Review validation files
   - If needed, give GPT corrections (e.g., update ISIN mapping, fix duplicates)
   - GPT re-runs pipeline and regenerates outputs

4. Get final results
   - Download the final summary CSV
   - Analyze in Excel, or feed into custom dashboards

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SETUP (FOR YOUR OWN DEPLOYMENT):

Quick Overview:
1. Get these two files (available in the resources section):
   - pipeline.py (full reproducible pipeline)
   - custom_instructions.md (system instructions)

2. In the Custom GPT builder:
   - Apply custom_instructions.md as system prompt
   - Upload pipeline.py under Actions schema

3. Your GPT will now:
   - Accept CSV uploads in the required format
   - Generate validation reports → wait for user confirmation → create final summary

4. Extend/customize as needed:
   - The full Python pipeline is open for editing
   - Add new metrics, filters, or visual outputs as you require

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RESOURCES:

MF Portfolio Holdings Processor:
https://app.tigzig.com/mf-files-ai
Convert & append Excels to CSV format required for the GPT analysis

Complete Source Code:
https://github.com/amararun/gpt-mf-holding-processor
GPT Custom Instructions & Python Code for MF holding processor

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BUILT ON:
OpenAI's GPT Platform - This custom GPT transforms ChatGPT into a powerful mutual fund portfolio analysis tool, enabling automated processing of two-point holdings data with deterministic validation and summary generation.

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Source: tigzig.com | Open source AI tools for analytics, databases & automation | Amar Harolikar