SiftStack CLAUDE.md

A repository-specific instruction file for SiftStack, a full-stack platform for running a real-estate investing business. It describes the project, setup, commands, and major workflows.

In plain words
What is it for?
Use it when developing, setting up, or troubleshooting SiftStack and its data collection, property analysis, market research, CRM, and lead-management workflows.
Why use it?
It gives a coding agent the context needed to work in this particular codebase without guessing how the project is organised or run.

Instructions file

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/datasift-ty-personal/siftstack/claude-md
Clone the repo
git clone --depth 1 https://github.com/DataSift-Ty-Personal/SiftStack
Per session 32,351 This file is loaded in full into every session.
When invoked 32,351 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.32351 $0.32351
Opus 5 $0.16175 $0.16175
Sonnet 5 $0.06470 $0.06470
Haiku 4.5 $0.03235 $0.03235

Measured 2d ago against content hash 2be6a80d1096, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

SiftStack CLAUDE.md scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- **L3 fallback fetcher (Scrapfly ASP, build 1.0.32+):** `src/scrapfly_browser.py` (`ScrapflyBrowserClient.fetch(url)`, plus a `python src/scrapfly_browser.py <url>` CLI) clears Cloudflare/JS walls on county-record + gen
CLAUDE.md · 849 lines

How it starts

The opening of the file, as written. The whole thing — 849 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md — SiftStack

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

SiftStack — Full-stack real estate investing operations platform built around DataSift.ai CRM. Covers the entire REI business lifecycle:

  1. Data Acquisition: Web scraping tnpublicnotice.com (foreclosures, tax sales, probates), scanned PDF import, courthouse terminal photo import (probate, eviction, code violations, divorce), Dropbox auto-polling
  2. Enrichment Pipeline: 10+ steps — Smarty address standardization, Zillow property data, Knox County Tax API, obituary/heir research, Ancestry.com SSDI, Tracerfy skip trace, Trestle phone scoring, entity research
  3. Deal Analysis: Comparable sales (Two-Bucket ARV), rehab estimation (4-tier room-by-room), deal analyzer (MAO/ROI/financing scenarios)
  4. Market Intelligence: Zip code scoring, Market Finder reports, cash buyer list building, investor portfolio analysis
  5. CRM Automation: DataSift upload, 26 TCA sequence templates, 12 niche sequential marketing presets, filter preset management, SiftMap sold property tagging
  6. Lead Management: 4 Pillars of Motivation auto-qualification, STABM daily routine, pipeline reporting, deep prospecting (4-level framework)
  7. Operations: Acquisition playbook generator (SOPs, scripts, checklists), Slack/Discord notifications, Google Drive upload, Apify Actor deployment

Currently focused on Knox and Blount counties, Tennessee. A realtor sphere-of-influence beta runs on the Columbus OH metro (the soi_* modules; see "Sphere of Influence Pipeline").

  1. REI Skill Library: 21 Claude Co-Work skill files (.skill/.plugin ZIPs) for distribution to DataSift community via learn.datasift.ai/claude-skills-rei. Skills teach Claude specific REI workflows when uploaded to Co-Work sessions or Projects.

Commands

# Setup
pip install -r requirements.txt
playwright install chromium
cp .env.example .env  # then fill in credentials

# Run
python src/main.py daily                          # new notices since last run
python src/main.py historical                     # last 12 months of data
python src/main.py daily --split                  # separate CSV per county+type
python src/main.py daily --counties Knox          # only Knox county
python src/main.py daily --types foreclosure,probate  # only specific types
python src/main.py daily -v                       # verbose/debug logging

# Comp package (boundary-filtered comps + dual-track ARV + rehab + buyers -> Excel)
python src/comp_package.py --address "158 Old State Rd" --zip 37914 \
    --beds 2 --baths 1 --sqft 1946 --year-built 1938 \
    --bbox "35.996,36.016,-83.895,-83.840" --streets "old state|nash rd|seahorn"

# Post-walkthrough package (comps + rehab matrix + walk findings + exits + dispo, Sift-linked)
python src/post_walkthrough.py --walkthrough-template     # writes walkthrough_template.json
python src/post_walkthrough.py --address "158 Old State Rd" --city Knoxville --zip 37914 \
    --bbox "35.996,36.016,-83.895,-83.840" --streets "old state|nash rd|seahorn" \
    --walkthrough walk_158.json --buyers output/buyer_sweep_37914_20260723.json \
    --outreach output/dispo_skiptrace_158.json
python src/post_walkthrough.py --address "..." --sold-json output/zillow_37914_sold.json  # free re-run

# DataSift preset/sequence management
python src/main.py manage-presets --discover                      # list all presets and sequences
python src/main.py manage-presets --add-sold-exclusion            # add Sold exclusion to all presets
python src/main.py manage-presets --create-sold-sequence          # create Sold cleanup sequence
python src/main.py manage-presets --all                           # discovery + update + sequence

# SiftMap sold property tagging
python src/main.py manage-sold --months-back 12                   # tag sold properties (last 12 months)
python src/main.py manage-sold --counties Knox --min-sale-price 5000

# Courthouse photo import (build 1.0.28+)
python src/main.py photo-import --folder ./photos --photo-county Knox --photo-type probate
python src/main.py photo-import --folder ./photos --photo-county Knox --photo-type eviction --skip-obituary
python src/main.py dropbox-watch                                  # auto-poll Dropbox for new photos
python src/main.py dropbox-watch --poll-interval 300 --max-polls 5  # 5-min interval, 5 cycles
python src/main.py dropbox-watch --no-delete                      # keep photos in Dropbox after processing

Read the full file on GitHub · 849 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 849 lines · 32,351 tokens per session scan A 2be6a80d1096

Subscribe to this mod's changes

SiftStack CLAUDE.md is an instructions file published in the GitHub repository DataSift-Ty-Personal/SiftStack (21 stars, last pushed 5d ago), licensed MIT. It adds 32,351 tokens to every session, about $0.1618 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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