The code

The whole tool is about 250 lines of plain Python — no framework, no platform, nothing hidden. run.py asks the engines the questions and saves a dated snapshot; report.py turns those snapshots into the weekly report. Open any file raw:

run.py · report.py · prompts.json

run.py — the engine probe

#!/usr/bin/env python3
"""GIG AI-Visibility runner. Asks a prompt set across answer engines, detects whether
GIG Gulf (and competitors) get cited, scores by GEO phase, saves a dated snapshot."""
import json, os, re, datetime, urllib.request, concurrent.futures as cf

ROOT = os.path.dirname(os.path.abspath(__file__))
CRED = os.path.expanduser("~/ClaudeWork/Claude/credentials.md")

def key(section, pat):
    f=False
    for l in open(CRED, errors="ignore"):
        if l.startswith("### "+section): f=True; continue
        if f and re.search(pat, l): return re.search(pat, l).group(0)

ANTH = key("Anthropic API", r"sk-ant-[A-Za-z0-9_-]{20,}")
OAI  = key("OpenAI", r"sk-[A-Za-z0-9_-]{20,}")
SERP = key("Serper", r"[a-f0-9]{40}")

# GIG Gulf is the rebrand of AXA Gulf. AXA legacy equity is OWNED demand, so an
# "AXA" mention counts as GIG-favourable, not a competitor.
GIG = [r"gig gulf", r"gulf insurance group", r"gig-gulf", r"\baxa\b"]
COMP = {"Sukoon":["sukoon"],"Tawuniya":["tawuniya"],"Salama":["salama"],
        "Orient":["orient"],"Daman":["daman"],"ADNIC":["adnic"],
        "RSA/Liva":["liva"],"Yallacompare":["yallacompare","policybazaar"]}

def mentioned(t, pats): t=t.lower(); return any(re.search(p,t) for p in pats)

def http(url, data, headers):
    req=urllib.request.Request(url, data=json.dumps(data).encode(), headers=headers)
    with urllib.request.urlopen(req, timeout=30) as r: return json.loads(r.read())

def ask_openai(q):
    d=http("https://api.openai.com/v1/chat/completions",
        {"model":"gpt-4o-mini","max_tokens":400,"messages":[
         {"role":"system","content":"Insurance shopping assistant for the UAE. Name specific insurers."},
         {"role":"user","content":q}]},
        {"Authorization":"Bearer "+OAI,"Content-Type":"application/json"})
    return d["choices"][0]["message"]["content"]

ENGINES={"ChatGPT":ask_openai, "Claude":ask_claude, "Google":ask_google}

def run_one(p, eng):
    txt=ENGINES[eng](p["q"])
    return {"id":p["id"],"phase":p["phase"],"lob":p["lob"],"engine":eng,
            "gig":mentioned(txt,GIG),"competitors":[c for c,ps in COMP.items() if mentioned(txt,ps)]}

def main():
    prompts=json.load(open(os.path.join(ROOT,"prompts.json")))
    jobs=[(p,e) for p in prompts for e in ENGINES]
    with cf.ThreadPoolExecutor(max_workers=12) as ex:
        rows=[f.result() for f in cf.as_completed([ex.submit(run_one,p,e) for p,e in jobs])]
    date=datetime.date.today().isoformat()
    json.dump({"date":date,"rows":rows}, open(os.path.join(ROOT,"snapshots",date+".json"),"w"))

if __name__=="__main__": main()

Abridged for reading — Claude and Google callers follow the same shape as ChatGPT. Full file via the link above.

How to run

cd ~/ClaudeWork/Clients/GIG/AIVisibility
python3 run.py      # asks the engines, writes snapshots/YYYY-MM-DD.json
python3 report.py   # builds the weekly report from the snapshots

The roadmap is the same shape, about 80 lines more: add Perplexity and Gemini callers, run each prompt three times for a confidence band, and capture the cited URLs.