ChemaVX
cffd174d4a
Hasta ahora el hreflang era un estado —puesto una vez a mano— y no una regla. Un slug que cambiara habría dejado el enlace apuntando al artículo viejo sin que nada avisara. El auditor gana dos reglas: hreflang.missing (pareja declarada sin bloque) y hreflang.stale (bloque que ya no coincide con la pareja). Viven en seo_hreflang y no en seo_rules porque necesitan hreflang-parejas.md, que es una decisión editorial curada; el motor sigue sin saber que hay parejas. Probadas en los cinco estados, no solo en el feliz: dispara sin bloque, dispara con el bloque apuntando a un slug viejo, y se calla cuando está correcto, cuando el post no es de ninguna pareja y cuando aún es borrador. Y el remate gana el paso 3c: buscar el espejo en el otro idioma y dejarlo en el informe. Con la advertencia explícita de decidir por TÍTULO y no por vector, y las dos reglas duras — solo espejos publicados, y uno a uno.
243 lines
10 KiB
Python
Executable File
243 lines
10 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Tool A — site-wide SEO auditor para los dos blogs (Ghost).
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READ-ONLY. Fetches every published post via the ghst-en wrapper (Ghost Admin API,
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staff token pulled on-demand from the pod — nothing written to disk), runs the
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shared rule engine (seo_rules.py), and prints:
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1. a summary of aggregate violations,
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2. a per-post table sorted worst-first,
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3. a ranked "fix this first" list.
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Usage:
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python3 seo_audit.py # EN (por defecto), en vivo
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python3 seo_audit.py --site es # el blog ES
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python3 seo_audit.py --json cache.json # audit a saved posts JSON instead of fetching
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python3 seo_audit.py --save cache.json # fetch live AND save the raw JSON
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Changes NOTHING in Ghost.
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"""
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import argparse
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import json
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import os
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import subprocess
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import sys
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import tempfile
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from collections import Counter
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import seo_rules as R
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import seo_exceptions as X
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import seo_hreflang as HL
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def partition(post, violations, site="en"):
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"""Split one post's violations into (actionable, accepted, info).
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'accepted' = an actionable-severity violation whose (rule, slug) is a
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documented waiver in seo_exceptions — kept OUT of the to-fix count and shown
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in its own section. The rule still ran; this is a reporting-side filter only.
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"""
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slug = post.get("slug")
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actionable, accepted, info = [], [], []
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for v in violations:
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if v.severity == R.INFO:
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info.append(v)
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elif X.accepted_reason(v.rule, slug, site):
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accepted.append(v)
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else:
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actionable.append(v)
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return actionable, accepted, info
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SITIOS = {"en": {"cli": "ghst-en", "host": "theexclusionzone.com"},
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"es": {"cli": "ghst-es", "host": "zonadeexclusion.com"}}
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def fetch_posts(cli="ghst-en"):
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"""Pull all published posts (with html) via the site's ghst wrapper.
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We redirect ghst's stdout to a temp file rather than capturing the pipe:
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ghst's output is ~750 KB and a captured PIPE truncates at the 64 KB pipe
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buffer, whereas a file redirect gets the whole document.
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"""
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fd, path = tempfile.mkstemp(suffix=".json", prefix="seo_audit_")
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os.close(fd)
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try:
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# ⚠️ `--status published` NO filtra: ghst devuelve published Y scheduled
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# (medido el 2026-07-28: 33 + 9 = los 42 que el informe llamaba
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# "published"). Se pide sin filtro y se separa aquí, que es lo honesto.
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cmd = (f"{cli} post list --limit all "
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"--formats html,lexical --json > " + path)
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r = subprocess.run(cmd, shell=True, stderr=subprocess.PIPE, text=True)
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if r.returncode != 0:
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sys.exit(f"{cli} fetch failed:\n{r.stderr}")
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data = json.load(open(path))
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posts = data["posts"] if isinstance(data, dict) and "posts" in data else data
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return [x for x in posts if x.get("status") in ("published", "scheduled")]
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finally:
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os.unlink(path)
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def load_posts(path):
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data = json.load(open(path))
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return data["posts"] if isinstance(data, dict) and "posts" in data else data
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--site", choices=("en", "es"), default="en")
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ap.add_argument("--json", help="audit a saved posts JSON instead of fetching live")
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ap.add_argument("--save", help="save fetched raw posts JSON to this path")
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args = ap.parse_args()
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if args.json:
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posts = load_posts(args.json)
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src = f"file {args.json}"
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else:
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posts = fetch_posts(SITIOS[args.site]["cli"])
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src = f"live ({SITIOS[args.site]['cli']}, Ghost Admin API)"
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if args.save:
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json.dump({"posts": posts}, open(args.save, "w"), indent=2)
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# El motor decide qué href es interno con R.SITE_HOST: sin esto, auditar
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# el ES contaría cero enlaces internos en los 31 posts.
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R.usar_sitio(args.site)
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# Las parejas espejo son una decisión editorial curada, no una regla del
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# motor: el auditor las inyecta y seo_rules sigue sin saber que existen.
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try:
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parejas = HL.lee_parejas()
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except OSError:
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parejas = []
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results = [] # (post, actionable, accepted, info, score)
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for p in posts:
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v = R.check_post(p) + HL.violaciones(p, args.site, parejas)
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actionable, accepted, info = partition(p, v, args.site)
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# score ranks worst-first on ACTIONABLE severity only — accepted waivers
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# and INFO don't push a post up the list.
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results.append((p, actionable, accepted, info, R.score(actionable)))
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# worst-first: by actionable severity score, then actionable count, then slug
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results.sort(key=lambda t: (-t[4], -len(t[1]), t[0]["slug"]))
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total_posts = len(posts)
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# SUMMARY counts reflect ACTIONABLE violations only (waived items excluded).
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posts_with_rule = Counter()
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for _, actionable, _, _, _ in results:
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for rule in {v.rule for v in actionable}:
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posts_with_rule[rule] += 1
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clean = sum(1 for _, actionable, _, _, _ in results if not actionable)
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accepted_total = sum(len(acc) for _, _, acc, _, _ in results)
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# ---- header ----
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print("=" * 78)
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print(f" SEO AUDIT — {SITIOS[args.site]['host']} source: {src}")
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n_pub = sum(1 for p in posts if p.get("status") == "published")
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n_prog = total_posts - n_pub
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print(f" {n_pub} publicados"
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+ (f" + {n_prog} programados" if n_prog else "")
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+ f" | {clean} clean (no actionable issues)"
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+ (f" | {accepted_total} accepted exception(s) waived" if accepted_total else ""))
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print(f" JSON-LD: handled globally by Edition-main theme — not flagged per post")
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print("=" * 78)
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# ---- summary ----
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print("\nSUMMARY — violations by rule (most posts affected first):\n")
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LABEL = {
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"meta_description.missing": "meta_description MISSING",
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"meta_description.too_long": f"meta_description > {R.META_DESC_MAX}",
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"meta_title.missing": "meta_title missing (falls back to title)",
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"meta_title.too_long": f"meta_title > {R.META_TITLE_MAX}",
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"custom_excerpt.too_long": f"custom_excerpt > {R.CUSTOM_EXCERPT_MAX}",
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"og_title.empty": "og_title empty",
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"og_description.empty": "og_description empty",
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"twitter_title.empty": "twitter_title empty",
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"twitter_description.empty": "twitter_description empty",
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"feature_image.missing": "feature_image missing",
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"feature_image_alt.missing": "feature_image_alt missing",
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"internal_links.too_few": f"internal links < {R.MIN_INTERNAL_LINKS}",
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"title_eq_meta_title": "meta_title == title (info)",
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}
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# severity per rule (look one up from any occurrence, incl. waived ones)
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sev_of = {}
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for _, actionable, accepted, info, _ in results:
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for v in actionable + accepted + info:
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sev_of[v.rule] = v.severity
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for rule, _ in sorted(posts_with_rule.items(),
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key=lambda kv: (-sev_of.get(kv[0], 0), -kv[1])):
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sev = R.SEV_NAME[sev_of.get(rule, 0)]
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print(f" [{sev:4}] {posts_with_rule[rule]:2}/{total_posts} posts "
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f"{LABEL.get(rule, rule)}")
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# ---- per-post table ----
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print("\n" + "-" * 78)
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print("PER-POST (worst first) — score = summed severity (HIGH 3 / MED 2 / LOW 1)\n")
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print(f"{'score':>5} {'slug':45} issues")
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print(f"{'-'*5} {'-'*45} {'-'*20}")
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for p, actionable, accepted, info, sc in results:
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if not actionable:
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note = "✓ clean" + (f" ({len(accepted)} accepted exception)" if accepted else "")
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print(f"{sc:5} {p['slug'][:45]:45} {note}")
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continue
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tags = ", ".join(sorted({v.rule for v in actionable}))
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print(f"{sc:5} {p['slug'][:45]:45} {tags}")
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# ---- detail per non-clean post ----
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print("\n" + "-" * 78)
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print("DETAIL\n")
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for p, actionable, accepted, info, sc in results:
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if not actionable and not info:
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continue
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print(f"• {p['slug']} (score {sc})")
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for v in sorted(actionable, key=lambda x: -x.severity):
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print(f" [{R.SEV_NAME[v.severity]:4}] {v.message}"
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+ (f" → {v.fix}" if v.fix else ""))
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for v in info:
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print(f" [INFO] {v.message}")
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print()
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# ---- accepted exceptions (won't fix — documented) ----
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if accepted_total:
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print("-" * 78)
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print("ACCEPTED EXCEPTIONS (won't fix — documented decisions, NOT in the count)\n")
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for p, actionable, accepted, info, sc in sorted(results, key=lambda t: t[0]["slug"]):
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for v in accepted:
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reason = X.accepted_reason(v.rule, p["slug"])
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print(f"• {p['slug']}")
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print(f" [{R.SEV_NAME[v.severity]:4}] {v.message}")
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print(f" waived: {reason}")
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print()
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# ---- ranked guidance ----
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print("-" * 78)
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print("FIX FIRST (by impact / effort):\n")
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md_missing = posts_with_rule.get("meta_description.missing", 0)
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md_long = posts_with_rule.get("meta_description.too_long", 0)
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links = posts_with_rule.get("internal_links.too_few", 0)
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og = posts_with_rule.get("og_title.empty", 0)
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alt = posts_with_rule.get("feature_image_alt.missing", 0)
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rank = []
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if md_missing:
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rank.append(f"meta_description MISSING on {md_missing} post(s) — HIGH impact, "
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f"controls the Google snippet. Write unique 140–145-char descriptions.")
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if md_long:
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rank.append(f"meta_description > {R.META_DESC_MAX} on {md_long} post(s) — trim so the "
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f"snippet isn't truncated (real ranking/CTR impact).")
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if links:
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rank.append(f"<{R.MIN_INTERNAL_LINKS} internal links on {links} post(s) — add 2–3 contextual "
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f"links to related articles (helps crawl + topical authority).")
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if og:
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rank.append(f"Empty OG/Twitter fields on {og} post(s) — SAFEST AUTO-FIX: mirror "
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f"meta_title/description into og_* and twitter_*. Highest count, lowest risk.")
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if alt:
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rank.append(f"Missing feature_image_alt on {alt} post(s) — quick accessibility + image-SEO win.")
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for i, line in enumerate(rank, 1):
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print(f" {i}. {line}")
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print()
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if __name__ == "__main__":
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main()
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