'Set up Finta workflow automation and data export for local analysis.
Scanned 5/29/2026
Install to Claude Code
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill finta-local-dev-loop --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: finta-local-dev-loop
description: 'Set up Finta workflow automation and data export for local analysis.
Use when building fundraising reports, exporting pipeline data,
or automating investor outreach workflows.
Trigger with phrases like "finta workflow", "finta automation",
"finta data export", "finta reporting".
'
allowed-tools: Read, Write, Edit, Bash(python3:*), Grep
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- fundraising-crm
- investor-management
- finta
compatibility: Designed for Claude Code
---
# Finta Local Dev Loop
## Overview
Finta is primarily UI-driven without a public API. For local automation, use CSV exports from Finta combined with Python scripts for analysis, reporting, and integration with other tools.
## Instructions
### Export Pipeline Data
1. In Finta, go to **Pipeline** > **Export** > **CSV**
2. Save as `pipeline-export.csv`
### Analyze Fundraise Pipeline
```python
import pandas as pd
from datetime import datetime
# Load Finta export
df = pd.read_csv("pipeline-export.csv")
# Pipeline summary
summary = df.groupby("Stage").agg(
count=("Name", "count"),
avg_check=("Check Size", "mean"),
).reset_index()
print("Pipeline Summary:")
print(summary.to_string(index=False))
# Conversion rates
stages = ["Researching", "Reaching Out", "Intro Meeting", "Follow-up", "Due Diligence", "Term Sheet", "Closed"]
for i in range(len(stages) - 1):
current = len(df[df["Stage"] == stages[i]])
next_stage = len(df[df["Stage"] == stages[i+1]])
rate = (next_stage / current * 100) if current > 0 else 0
print(f" {stages[i]} -> {stages[i+1]}: {rate:.0f}%")
```
### Weekly Pipeline Report
```python
def generate_weekly_report(df: pd.DataFrame) -> str:
total = len(df)
active = len(df[df["Stage"].isin(["Intro Meeting", "Follow-up", "Due Diligence"])])
term_sheets = len(df[df["Stage"] == "Term Sheet"])
closed = len(df[df["Stage"] == "Closed"])
return f"""
Fundraise Pipeline Report ({datetime.now().strftime('%Y-%m-%d')})
==================================================
Total investors: {total}
Active conversations: {active}
Term sheets: {term_sheets}
Closed: {closed}
"""
```
## Resources
- [Finta Website](https://www.trustfinta.com)
## Next Steps
See `finta-sdk-patterns` for integration patterns.
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