| name | product-description-seo |
| description | End-to-end skill for SEO-optimized product descriptions: inventory analysis, generation, quality assurance, catalog update, and deployment. Use whenever the user wants to analyze, write, check, update, or deploy product descriptions — whether for a single product, a category, or an entire catalog. Triggers on: 'product description', 'Produktbeschreibung', 'SEO text', 'catalog text', 'update descriptions', 'which descriptions are missing', 'thin content', 'QA check', 'description quality', or when the user names a product category and wants texts for it. Also triggers on 'deploy' or 'commit' in the context of product descriptions. |
Product Description SEO — End-to-End Workflow
A complete pipeline for turning thin or missing product descriptions into SEO-optimized, structured content. Works with any JSON-based product catalog, any language, any industry.
Quick Reference
| Phase | Task | Tool |
|---|
| 1. Inventory | Analyze catalog, find thin descriptions | scripts/analyze_catalog.py |
| 2. Progress | Check current completion status | scripts/track_progress.py |
| 3. Extraction | Pull category products as batch-ready JSON | scripts/extract_category.py |
| 4. Generation | Write descriptions using 4-paragraph structure | See structure below |
| 5. QA | Automated quality check (8 criteria) | scripts/check_quality.py |
| 6. Update | Write descriptions back to catalog JSON | scripts/update_catalog.py |
| 7. Validation | Verify JSON structure after update | scripts/validate_json.py |
| 8. Rendering | Adapt frontend for multi-paragraph text | Code guidance below |
| 9. Deploy | Feature branch, PR, merge | Git workflow |
Setup
Before first use, create a product-seo-config.json in the working directory to configure the skill for a specific catalog. This is optional — all scripts work without it using sensible defaults.
{
"catalog_path": "path/to/catalog/index.json",
"company": {
"name": "Company Name",
"founded": "1990",
"location": "City, Country",
"expertise": "short description of domain expertise",
"usp": "key selling points for the closing paragraph"
},
"fields": {
"description": "beschreibung",
"category": "kategorieName",
"sku": "sku",
"name": "name",
"status": "status",
"status_active_value": "aktiv"
},
"seo": {
"min_words": 200,
"max_words": 350,
"language": "de",
"primary_keyword_pattern": "{product_name} + {industry_term}",
"banned_words": ["best-in-class", "unparalleled", "revolutionary", "world-leading"]
},
"target_audience": "procurement managers, facility managers, technical buyers",
"tone": "professional, expert, trustworthy — like an experienced technical consultant",
"priorities": {
"1": ["Core Category A", "Core Category B"],
"2": ["Secondary Category C"],
"3": []
}
}
Catalog Format
The catalog must be a JSON file with a products array. Field names are configurable via product-seo-config.json:
{
"products": [
{
"sku": "401",
"name": "Product Name",
"beschreibung": "Current description text...",
"kategorie": "category-slug",
"kategorieName": "Category Display Name",
"preis": 29.99,
"einheit": "piece",
"status": "aktiv",
"slug": "product-name-401"
}
]
}
Only the description field is updated. Everything else stays untouched.
Phase 1: Inventory
Understand the current state of the catalog — which descriptions are too thin, which categories need work.
python scripts/analyze_catalog.py <catalog.json>
python scripts/analyze_catalog.py <catalog.json> --category "Tools"
python scripts/analyze_catalog.py <catalog.json> --min-words 150
Output: per-category statistics (avg word count, products below threshold), top-20 thinnest descriptions, and when filtering by category a JSON export ready for batch prompting.
Phase 2: Progress
Track the completion status of the description update campaign.
python scripts/track_progress.py <catalog.json>
python scripts/track_progress.py <catalog.json> --config product-seo-config.json
Output: progress bar, per-priority breakdown, next-action queue showing which categories and products to tackle next.
Phase 3: Extraction
Pull products from a category as prompt-ready JSON.
python scripts/extract_category.py <catalog.json> "Power Tools" --limit 8
python scripts/extract_category.py <catalog.json> "Power Tools" --thin-first
python scripts/extract_category.py <catalog.json> "Accessories" --offset 8 --limit 8
Category matching is fuzzy — partial matches work. If no match is found, available categories are listed.
Phase 4: Generation
Write descriptions following the 4-paragraph structure. Process 5-8 products per batch maximum to maintain quality.
4-Paragraph Structure
Paragraph 1 — Introduction and Value (50-80 words)
Focus keyword (product name + industry/category term) in the first sentence. What is the product? What problem does it solve? Why does the target audience need it?
The first 155 characters must work standalone as a meta description — complete thought, ending with a period.
Paragraph 2 — Technical Specifications (60-100 words)
Materials, dimensions, weight, capacity, special features. Every technical fact from the existing description must be preserved 1:1. Never omit data, never fabricate specs. If source data is vague, keep it vague.
Paragraph 3 — Application and Practice (40-60 words)
Typical use cases, ideal conditions, when to deploy. Mention 1-2 complementary products from the same catalog (cross-sell). Use CROSS-SELL.md as reference if available.
Paragraph 4 — Quality and Service (30-50 words)
Company expertise, personal consultation, delivery/support promise. Soft CTA: "Contact us for personalized advice." No aggressive sales pressure. Adapt to the company info from config.
Variant Rule
Products with color, size, or material variants must get unique texts. The variant attribute must be mentioned and contextualized — never copy the same text across variants. Example: a red variant could mention visibility advantages; a compact variant could highlight space efficiency.
Tone
- Professional, expert, trustworthy — like an experienced technical consultant
- Formal address (German: "Sie"; English: naturally formal; adapt to language)
- Banned words: best-in-class, unparalleled, revolutionary, sensational, unmatched, premium (without proof), world-leading, perfect, unique (without proof)
- Superlatives only with concrete evidence (e.g., "proven for over 10 years")
- Adapt to
target_audience and tone from config
SEO Keywords
- Primary: [Product Name] + industry/category term
- Secondary: [Category Name], industry-standard terms
- Longtail: "[Product Name] buy/purchase", "[Product Name] for [use case]"
- Maximum 3x focus keyword per text — no keyword stuffing
- Use KEYWORDS.md for category-specific targets if available
Output Format
Save descriptions as a JSON array:
[
{
"sku": "401",
"name": "Product Name",
"beschreibung": "Paragraph 1...\n\nParagraph 2...\n\nParagraph 3...\n\nParagraph 4..."
}
]
Save as updates-<category-slug>.json.
Phase 5: Quality Assurance
Automated check against all requirements:
python scripts/check_quality.py updates-tools.json
python scripts/check_quality.py updates-tools.json --strict
python scripts/check_quality.py updates-tools.json --min-words 150 --max-words 400
Checks per description:
- Word count within configured range (default 200-350)
- 4-paragraph structure (exactly 3x
\n\n separator)
- Focus keyword (product name) in first sentence
- No banned superlatives
- Cross-sell reference present (company name or "combination with")
- Formal address (no informal pronouns in German texts)
- Meta-description-ready first 155 characters
- Plain text only (no HTML, no Markdown, no bullet points)
Fix any failures, re-check. Proceed to Phase 6 only when all checks pass.
Phase 6: Update
Write QA-approved descriptions back to the catalog:
python scripts/update_catalog.py <catalog.json> updates-tools.json
The script:
- Creates an automatic backup (
catalog.json.backup_YYYYMMDD_HHMMSS)
- Matches updates by SKU
- Reports word count before -> after per product
- Flags SKUs not found in catalog
Phase 7: Validation
Verify JSON integrity after the update:
python scripts/validate_json.py <catalog.json>
Checks: valid JSON parse, required fields on every product, no duplicate SKUs, no HTML tags in descriptions, valid slug format.
Phase 8: Rendering
If the frontend renders descriptions as a single element, adapt it for multi-paragraph text. Paragraphs are separated by \n\n in the JSON.
Svelte:
{#each description.split('\n\n') as paragraph}
<p class="description">{paragraph}</p>
{/each}
React:
{description.split('\n\n').map((p, i) => (
<p key={i} className="description">{p}</p>
))}
Vue:
<p v-for="(p, i) in description.split('\n\n')" :key="i" class="description">{{ p }}</p>
Meta description — use the first paragraph, truncated:
const metaDescription = description.split('\n\n')[0].slice(0, 155);
This change only needs to happen once and applies to all products.
Phase 9: Deploy
Standard git workflow — never push directly to main.
git checkout -b product-descriptions/<category-slug>
git add path/to/catalog.json
git commit -m "content: Update product descriptions for <Category>"
gh pr create --title "Content: Product descriptions <Category>"
One PR per category or batch to keep reviews manageable.
Example: Full Run
python scripts/track_progress.py catalog.json
python scripts/extract_category.py catalog.json "Tools" --thin-first
python scripts/check_quality.py updates-tools.json
python scripts/update_catalog.py catalog.json updates-tools.json
python scripts/validate_json.py catalog.json
git checkout -b product-descriptions/tools
git add catalog.json
git commit -m "content: Update product descriptions Tools (8 products)"
gh pr create --title "Content: Product descriptions Tools"
Optional Reference Files
Not required, but improve output quality when present alongside the skill:
| File | Purpose |
|---|
| KEYWORDS.md | Category-specific keyword targets (primary, secondary, longtail) |
| CROSS-SELL.md | Cross-sell matrix defining which categories reference each other |
| product-seo-config.json | Company context, field mappings, priorities |
Templates for KEYWORDS.md and CROSS-SELL.md are included — fill them in for your catalog.
Scripts
| Script | Purpose |
|---|
scripts/analyze_catalog.py | Catalog analysis (thinnest descriptions, word counts) |
scripts/track_progress.py | Progress tracking with priority support |
scripts/extract_category.py | Category extraction for batch prompting (fuzzy match) |
scripts/check_quality.py | Automated QA with 8 configurable checks |
scripts/update_catalog.py | Write descriptions to catalog with automatic backup |
scripts/validate_json.py | JSON structure validation |
Dependencies
- Python 3.10+ for all scripts
- gh CLI (optional) for PR creation in Phase 9