FrancoStino/keyword-extractor

Keyword Extractor

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

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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

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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

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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

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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

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WORKFLOW

Step 1 — Analyze

Identify:

• main subject
• key topics
• domain terminology
• entities
• concepts

Ignore filler words.

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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.

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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.

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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.

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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.

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FAILURE HANDLING

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

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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.