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our-claude-skills/custom-skills/95-ourdigital-presales-seo/scripts/estimate.py
Andrew Yim 3a8edebfef estimate.py: scale local_seo/onpage_entity by portfolio size
Add configurable sub-linear scope-scaling bands to rate_card.yaml; estimate.py
now multiplies monthly line-item rates by properties_total (local_seo) and
subbrands_total (onpage_entity), with the scope note written into the 견적.

Validated: L'Escape (1 property) stays at base 23-47M; SHR (25 properties,
5 sub-brands) scales to 54.8-110.6M (local ×4.5, on-page ×2.2).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-28 00:24:33 +09:00

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#!/usr/bin/env python3
"""Generate a ranged 견적 (estimate) from findings.json using the OurDigital rate card.
Part of the ourdigital-presales-seo skill (Stage 5). Maps detected findings to
rate-card service lines (see references/findings_to_service.md) and emits:
- 05_estimate_ko.md (Korean line-item quote)
- data/estimate.json (consumed by build_deck.py)
- 05_estimate.xlsx (spreadsheet quote)
Usage:
python estimate.py --findings findings.json --rate-card ../references/rate_card.yaml \
--out-dir ./audits/2026-05-27-presales --seq 1
"""
import argparse
import datetime
import json
import os
import yaml
from openpyxl import Workbook
from openpyxl.styles import Alignment, Font, PatternFill
def won(n):
return f"{n:,}"
def select_services(f):
"""Return {service_key: [reasons]} based on findings signals."""
chosen = {}
d = f.get("discovery", {})
t = f.get("technical", {})
e = f.get("entity", {})
m = f.get("measurement", {})
def need(key, reason):
chosen.setdefault(key, [])
if reason not in chosen[key]:
chosen[key].append(reason)
# Crawlability / indexation
if d.get("sitemap_status", 200) != 200 or d.get("robots_sitemap_declared", True) is False:
need("technical_audit", "sitemap/robots 색인 이슈")
need("technical_remediation", "sitemap 복구·크롤성 개선")
# Core Web Vitals
cwv = t.get("cwv", {})
if (cwv.get("perf", 1) < 0.5 or cwv.get("cls", 0) > 0.1
or cwv.get("lcp_ms", 0) > 2500 or cwv.get("ttfb_ms", 0) > 600):
need("technical_audit", "Core Web Vitals 취약")
need("technical_remediation", "CWV(CLS/LCP/TTFB) 개선")
# Schema / entity
if (t.get("schema", {}).get("org") in ("bare", "none") or e.get("panel") != "hotel"
or e.get("name_split") or e.get("legacy_contamination")
or (e.get("subbrands_with_entity", 0) == 0 and e.get("subbrands_total", 0) > 0)):
need("schema_build", "Organization/Hotel schema·브랜드 표기 정합")
need("onpage_entity", "엔티티·서브브랜드 최적화")
# Local
hygiene = " ".join(d.get("url_hygiene", [])).lower()
if ((e.get("properties_with_entity", 0) == 0 and e.get("properties_total", 0) > 0)
or "local" in hygiene or "gbp" in hygiene or "dup_path" in hygiene):
need("local_seo", "프로퍼티 로컬·GBP 정합")
# Measurement
if m.get("gsc_access") is False or m.get("ga4_access") is False:
need("ga4_impl", "측정 환경(GA4) 구축")
need("dashboard", "리포팅 대시보드 구축")
if m.get("tag_gaps"):
need("gtm_setup", "태그 관리(GTM) 구축")
# On-page hygiene
if t.get("meta_dupe") or t.get("title_i18n_mismatch") or t.get("hreflang") == "incomplete":
need("onpage_entity", "Meta/Title/hreflang 정리")
return chosen
DRIVER_LABEL = {"properties_total": "프로퍼티", "subbrands_total": "서브브랜드"}
def scope_multiplier(rate, key, f):
"""Sub-linear scope multiplier for a service, driven by portfolio size.
Returns (multiplier, driver, count). count is floored at 1 (unknown→base).
"""
rule = rate.get("scaling", {}).get(key)
if not rule:
return 1.0, None, None
driver = rule["driver"]
count = max(int(f.get("entity", {}).get(driver, 0) or 0), 1)
for max_count, mult in rule["bands"]:
if count <= max_count:
return float(mult), driver, count
return 1.0, driver, count
def build_line_items(chosen, rate, f):
months = rate["defaults"]["retainer_months"]
order = {"one_time": 0, "project": 1, "monthly": 2}
items = []
for key, reasons in chosen.items():
svc = rate["services"][key]
unit = svc["unit"]
qty = months if unit == "monthly" else 1
mult, driver, count = scope_multiplier(rate, key, f)
umin = int(round(svc["min"] * mult))
umax = int(round(svc["max"] * mult))
reason = "; ".join(reasons)
scope_note = None
if mult != 1.0:
scope_note = f"{DRIVER_LABEL.get(driver, driver)} {count}개 기준 ×{mult:g}"
reason = f"{reason} [{scope_note}]"
items.append({
"key": key, "label": svc["label_ko"], "unit": unit, "qty": qty,
"unit_min": umin, "unit_max": umax,
"amount_min": umin * qty, "amount_max": umax * qty,
"reason": reason,
"scope_multiplier": mult, "scope_driver": driver,
"scope_count": count, "scope_note": scope_note,
})
items.sort(key=lambda x: order.get(x["unit"], 9))
return items, months
def totals(items):
one = [i for i in items if i["unit"] != "monthly"]
mon = [i for i in items if i["unit"] == "monthly"]
return {
"one_time_min": sum(i["amount_min"] for i in one),
"one_time_max": sum(i["amount_max"] for i in one),
"monthly_min": sum(i["amount_min"] for i in mon),
"monthly_max": sum(i["amount_max"] for i in mon),
"grand_min": sum(i["amount_min"] for i in items),
"grand_max": sum(i["amount_max"] for i in items),
}
UNIT_KO = {"one_time": "1회", "project": "프로젝트", "monthly": ""}
def write_md(path, quote_no, date, prospect, items, tot, months, disclaimer):
L = [f"# 견적서 (Pre-sales 추정) — {prospect}",
"", f"- **견적번호**: {quote_no}", f"- **작성일**: {date}",
f"- **대상**: {prospect}", f"- **공급자**: OurDigital (andrew.yim@ourdigital.org)",
"", "## 견적 내역", "",
"| 항목 | 근거 | 단위 | 수량 | 단가(범위) | 금액(범위) |",
"|---|---|---|---:|---|---|"]
for i in items:
L.append(f"| {i['label']} | {i['reason']} | {UNIT_KO.get(i['unit'], i['unit'])} | {i['qty']} | "
f"{won(i['unit_min'])}~{won(i['unit_max'])} | {won(i['amount_min'])}~{won(i['amount_max'])} |")
L += ["", "## 합계 (범위)", "",
f"- 일회성/프로젝트: **{won(tot['one_time_min'])} ~ {won(tot['one_time_max'])}**",
f"- 월 운영({months}개월 기준): **{won(tot['monthly_min'])} ~ {won(tot['monthly_max'])}**",
f"- 총계: **{won(tot['grand_min'])} ~ {won(tot['grand_max'])}**",
"", f"> {disclaimer}"]
with open(path, "w", encoding="utf-8") as fh:
fh.write("\n".join(L) + "\n")
def write_xlsx(path, quote_no, date, prospect, items, tot, months, disclaimer):
wb = Workbook()
ws = wb.active
ws.title = "견적"
hdr = PatternFill("solid", fgColor="11243D")
hf = Font(color="FFFFFF", bold=True)
ws.append([f"견적서 (Pre-sales 추정) — {prospect}"])
ws.append([f"견적번호 {quote_no}", f"작성일 {date}", "공급자 OurDigital"])
ws.append([])
cols = ["항목", "근거", "단위", "수량", "단가 min", "단가 max", "금액 min", "금액 max"]
ws.append(cols)
for c in range(1, len(cols) + 1):
cell = ws.cell(row=ws.max_row, column=c)
cell.fill = hdr
cell.font = hf
for i in items:
ws.append([i["label"], i["reason"], UNIT_KO.get(i["unit"], i["unit"]), i["qty"],
i["unit_min"], i["unit_max"], i["amount_min"], i["amount_max"]])
ws.append([])
ws.append(["일회성/프로젝트 합계", "", "", "", "", "", tot["one_time_min"], tot["one_time_max"]])
ws.append([f"월 운영 합계 ({months}개월)", "", "", "", "", "", tot["monthly_min"], tot["monthly_max"]])
ws.append(["총계", "", "", "", "", "", tot["grand_min"], tot["grand_max"]])
ws.cell(row=ws.max_row, column=1).font = Font(bold=True)
ws.append([])
ws.append([disclaimer])
widths = [34, 30, 8, 6, 12, 12, 14, 14]
for idx, w in enumerate(widths, 1):
ws.column_dimensions[chr(64 + idx)].width = w
wb.save(path)
def main():
ap = argparse.ArgumentParser(description="Generate ranged 견적 from findings.json")
ap.add_argument("--findings", required=True)
ap.add_argument("--rate-card", required=True)
ap.add_argument("--out-dir", default=".")
ap.add_argument("--seq", type=int, default=1, help="quote sequence number (NNN)")
args = ap.parse_args()
with open(args.findings, encoding="utf-8") as fh:
f = json.load(fh)
with open(args.rate_card, encoding="utf-8") as fh:
rate = yaml.safe_load(fh)
prospect = f.get("prospect", {}).get("name", "(prospect)")
date = f.get("prospect", {}).get("audit_date") or datetime.date.today().isoformat()
year = date[:4]
quote_no = f"{rate.get('quote_prefix', 'OD')}-{year}-{args.seq:03d}"
disclaimer = rate["defaults"]["disclaimer_ko"]
chosen = select_services(f)
items, months = build_line_items(chosen, rate, f)
tot = totals(items)
os.makedirs(args.out_dir, exist_ok=True)
data_dir = os.path.join(args.out_dir, "data")
os.makedirs(data_dir, exist_ok=True)
md_path = os.path.join(args.out_dir, "05_estimate_ko.md")
xlsx_path = os.path.join(args.out_dir, "05_estimate.xlsx")
json_path = os.path.join(data_dir, "estimate.json")
write_md(md_path, quote_no, date, prospect, items, tot, months, disclaimer)
write_xlsx(xlsx_path, quote_no, date, prospect, items, tot, months, disclaimer)
with open(json_path, "w", encoding="utf-8") as fh:
json.dump({"quote_no": quote_no, "date": date, "prospect": prospect,
"line_items": items, "totals": tot, "retainer_months": months,
"disclaimer": disclaimer}, fh, ensure_ascii=False, indent=2)
print(f"견적 {quote_no}: {len(items)} line items | "
f"one-time {won(tot['one_time_min'])}~{won(tot['one_time_max'])} | "
f"monthly {won(tot['monthly_min'])}~{won(tot['monthly_max'])}/{months}mo")
print(f"Wrote: {md_path}\n {xlsx_path}\n {json_path}")
if __name__ == "__main__":
main()