Keyword Extractor

Extracts max 50 relevant keywords from text and formats them in a strict machine-ready structure.

QUICK START

Jump to any section: 1. CORE MANDATE – Output rules and formatting 2. WHEN TO USE – Trigger conditions for this skill 3. KEYWORD QUALITY RULES – Priorities and forbidden keywords 4. WORKFLOW – Step-by-step generation and processing 5. FAILURE HANDLING – Short text or edge cases

CORE MANDATE

Return exactly one comma-separated line of keywords, following these rules: - max 50 keywords
- ordered by relevance
- all lowercase
- no duplicates or near-duplicates
- mix of single words and 2–4 word phrases
- no numbering, bullets, explanations, or trailing period

When to Use

Use this skill when the user wants to generate or extract SEO-friendly keywords or tags from text including: - Extracting keywords or tags for any given text or paragraph
- Creating comma-separated keywords or tags suitable for SEO, search, or metadata
- Generating topic-specific keywords or tags based on the content’s main subjects and concepts

This skill should be triggered for all text-based keyword extraction requests, regardless of phrasing, as long as the goal is SEO, tagging, or metadata generation.

Do NOT trigger this skill for:
- Summaries or paraphrasing requests
- Text analysis without keyword generation

KEYWORD QUALITY RULES

Prefer noun phrases over verbs or adjectives. Prefer keywords useful for: - SEO and search - tagging - metadata

Prioritize: - domain terminology - meaningful nouns - search phrases - entities - technical concepts

Avoid weak keywords like: - things and various topics - general concepts - important ideas - methods

IMPORTANT: Each keyword must strictly represent a phrase that a user would type into a search engine

WORKFLOW

Step 1 — Analyze

Identify: - main subject - key topics - domain terminology - entities - concepts

Ignore filler words.

Step 2 — Generate Keywords

Generate up to 50 strictly SEO-friendly keywords directly from the text.

Include: - core topics - domain terminology - related concepts - common search queries

Allowed formats: - single words - 2 word phrases - 3 word phrases - 4 word phrases

Example: machine learning, neural networks, deep learning models, ai algorithms, data science tools

Avoid vague keywords, filler phrases, adjectives without nouns like: important methods, different ideas, various techniques, things

Keywords must not exceed 4 words.

Step 3 — Rank

Order keywords by SEO importance using these signals: 1. main topic of the text 2. high-value domain terminology 3. technologies, tools, or entities mentioned 4. common search queries related to the topic 5. supporting contextual topics

Most important keywords should always appear first.

Step 4 — Normalize

Ensure: - lowercase, comma separated, no duplicates - ≤50 keywords - Remove near-duplicate keywords that represent the same concept. - Keep only the most common search phrase. - If two keywords represent the same concept, keep only the more common search phrase.

Step 5 — Validate

Before returning output ensure: - keyword_count <= 50 - no duplicates and near-duplicates - all lowercase and comma separated - no trailing period - each keyword is a clear searchable topic - keywords do not exceed 4 words

If any rule fails regenerate the list.

FAILURE HANDLING

If text is very short, infer likely topics and still generate keywords. Never exceed 50 keywords.

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.