Skip to content
cccskills
FreePublished on GitHub

keyword-extractor

Extracts up to 50 highly relevant SEO keywords from text. Use when user wants to generate or extract keywords for given text.

The English summary is being prepared. Showing the original description.

See how to install

Files included (1)

  • SKILL.md4.2 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

12-agent academic paper writing pipeline. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見.

The English summary is being prepared. Showing the original description.

bouclem/skills7Updated May 31, 2026

Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.

The English summary is being prepared. Showing the original description.

bouclem/skills7Updated May 31, 2026

Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.

The English summary is being prepared. Showing the original description.

bouclem/skills7Updated May 31, 2026

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

The English summary is being prepared. Showing the original description.

bouclem/skills7Updated May 31, 2026

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

The English summary is being prepared. Showing the original description.

bouclem/skills7Updated May 31, 2026

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

The English summary is being prepared. Showing the original description.

bouclem/skills7Updated May 31, 2026

See all skills by bouclem

Report a problem with this skill