SEO Keyword Clustering
AgriciDaniel/claude-seo
Clusters keywords by how much their search results overlap and designs a hub-and-spoke content plan with an internal link matrix and an interactive cluster map.
Conduct comprehensive keyword research to identify high-value search terms, map search intent, and uncover content gaps for SEO and content marketing.
Install Keyword Research
$ npx skills add seb1n/awesome-ai-agent-skills --skill keyword-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills keyword-research --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/marketing-and-seo/keyword-research .claude/skills/keyword-research && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "keyword-research" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/marketing-and-seo/keyword-research into .claude/skills/keyword-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keyword-research", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/seb1n/awesome-ai-agent-skills/tree/main/marketing-and-seo/keyword-researchType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add seb1n/awesome-ai-agent-skills --skill keyword-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills keyword-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/marketing-and-seo/keyword-research .agents/skills/keyword-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "keyword-research" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/marketing-and-seo/keyword-research into .agents/skills/keyword-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keyword-research", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill keyword-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills keyword-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/marketing-and-seo/keyword-research .cursor/skills/keyword-research && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "keyword-research" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/marketing-and-seo/keyword-research into .cursor/skills/keyword-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keyword-research", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/seb1n/awesome-ai-agent-skills.git --path marketing-and-seo/keyword-research--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add seb1n/awesome-ai-agent-skills --skill keyword-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills keyword-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/marketing-and-seo/keyword-research .gemini/skills/keyword-research && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "keyword-research" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/marketing-and-seo/keyword-research into .gemini/skills/keyword-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keyword-research", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install seb1n/awesome-ai-agent-skills keyword-researchInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add seb1n/awesome-ai-agent-skills --skill keyword-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/marketing-and-seo/keyword-research .github/skills/keyword-research && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "keyword-research" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/marketing-and-seo/keyword-research into .github/skills/keyword-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keyword-research", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill keyword-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills keyword-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/marketing-and-seo/keyword-research .opencode/skills/keyword-research && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "keyword-research" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/marketing-and-seo/keyword-research into .opencode/skills/keyword-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keyword-research", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
keyword-research- GitHub stars
- 206
- Token cost
- ~2.2k tokens
- SKILL.md length
- 1,084 words
- Files
- 1
- Skills in repo
- 101
- Repo updated
- First seen
- Licence
- MIT
At a glance
Conduct comprehensive keyword research to identify high-value search terms, map search intent, and uncover content gaps for SEO and content marketing.
- Works in 6 steps: Collect seed keywords and define scope.… → Expand into long-tail and related… → Gather search metrics for each keyword.… → …
- The user requests keyword research
- SKILL.md covers Workflow, Usage, Examples and Best Practices, plus 1 more section
- Reaches supportbot.io
What it does
Keyword Research is an agent skill from seb1n/awesome-ai-agent-skills. Conduct comprehensive keyword research to identify high-value search terms, map search intent, and uncover content gaps for SEO and content marketing. Use when the user requests keyword research or provides relevant inputs for this workflow.
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Marketing & SEO, covering Keyword research. The repository describes itself as: 103 ready-to-use AI agent skills for Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot, Windsurf, and other Agent Skills-compatible tools. Complete SKILL.md… The licence is MIT.
When your agent uses it
- The user requests keyword research
- Provides relevant inputs for this workflow
Example prompts
- “/keyword-research”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Collect seed keywords and define scope. Gather initial seed keywords from the user's product description, existing content, and business…
- Expand into long-tail and related keywords. Use autocomplete patterns, "People Also Ask" queries, and semantic variations to build a broad…
- Gather search metrics for each keyword. Estimate monthly search volume, keyword difficulty (0–100 scale), cost-per-click for paid…
- Classify search intent for every keyword. Categorize each keyword as informational (learn), navigational (find a specific site)…
- Perform competitor keyword gap analysis. Identify 3–5 organic competitors and compare their ranking keywords against the user's current…
- Deliver a structured keyword strategy report. Organize keywords into thematic clusters mapped to content pillars. Prioritize clusters by a…
What it can do on your machine
Read from SKILL.md and the folder at commit 75865a5. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
supportbot.io
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Keyword Research loads about 2.2k tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 1,084 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from seb1n/awesome-ai-agent-skills at commit 75865a5, republished under its MIT licence (© seb1n). 1,084 words, ~2,161 tokens.
Download SKILL.mdSave it as
.claude/skills/keyword-research/SKILL.md (or your agent's skills folder).- name
- keyword-research
- description
- Conduct comprehensive keyword research to identify high-value search terms, map search intent, and uncover content gaps for SEO and content marketing. Use when the user requests keyword research or provides relevant inputs for this workflow.
- license
- MIT
- metadata.author
- awesome-ai-agent-skills
- metadata.version
- 1.0.0
Keyword Research
This skill enables an AI agent to perform end-to-end keyword research for any niche, product, or content initiative. The agent starts from seed keywords, expands into long-tail variations, classifies search intent, analyzes competitor keyword portfolios, and delivers a prioritized keyword strategy. The output helps content teams, SEO specialists, and product marketers target the right search terms to drive qualified organic traffic.
Workflow
Collect seed keywords and define scope. Gather initial seed keywords from the user's product description, existing content, and business goals. Identify the target market, geographic region, and language. Clarify whether the research is for blog content, landing pages, product pages, or paid campaigns, as this affects intent priorities.
Expand into long-tail and related keywords. Use autocomplete patterns, "People Also Ask" queries, and semantic variations to build a broad keyword list. Generate question-based keywords (who, what, how, why), comparison keywords ("X vs Y"), and modifier keywords (best, top, free, cheap, review). Aim for 50–200 candidate keywords per seed term depending on niche competitiveness.
Gather search metrics for each keyword. Estimate monthly search volume, keyword difficulty (0–100 scale), cost-per-click for paid reference, and trend direction (rising, stable, declining). Pull click-through rate estimates where available. Note seasonal patterns — for example, "tax software" peaks in January–April while "sunscreen" peaks in May–July.
Classify search intent for every keyword. Categorize each keyword as informational (learn), navigational (find a specific site), commercial investigation (compare options), or transactional (buy/sign up). This mapping determines the correct content format: blog posts for informational, comparison pages for commercial, and product/landing pages for transactional.
Perform competitor keyword gap analysis. Identify 3–5 organic competitors and compare their ranking keywords against the user's current keyword portfolio. Highlight keywords where competitors rank but the user does not — these are content gap opportunities. Also flag keywords where the user ranks on page 2 (positions 11–20) that could move to page 1 with targeted optimization.
Deliver a structured keyword strategy report. Organize keywords into thematic clusters mapped to content pillars. Prioritize clusters by a composite score of volume, difficulty, intent alignment, and business value. Include specific content recommendations for each cluster — suggested titles, target word counts, and internal linking opportunities.
Usage
Provide the agent with a seed keyword or topic, your website URL (optional, for gap analysis), and your target audience. The agent returns a full keyword research report with prioritized clusters and content recommendations.
Prompt: Perform keyword research for the topic "AI-powered customer support" targeting SaaS companies in the US market. My site is https://supportbot.io.
Examples
Example 1: SaaS Product Keyword Research
Request: Research keywords for a project management SaaS product targeting remote teams.
Keyword Table:
| Keyword | Monthly Volume | Difficulty | CPC | Intent | Priority |
|---|---|---|---|---|---|
| project management software | 40,500 | 78 | $12.40 | Commercial | Medium |
| best project management tools for remote teams | 3,600 | 45 | $8.20 | Commercial | High |
| how to manage remote team projects | 2,900 | 32 | $3.10 | Informational | High |
| free project management app | 8,100 | 62 | $6.50 | Transactional | Medium |
| asana vs monday vs trello | 5,400 | 55 | $9.80 | Commercial | Medium |
| remote team collaboration tools | 4,200 | 48 | $7.30 | Commercial | High |
| project management for startups | 1,800 | 28 | $5.60 | Commercial | High |
| kanban board software | 6,700 | 58 | $7.90 | Transactional | Medium |
| how to create a project timeline | 3,100 | 22 | $2.40 | Informational | High |
| project management best practices 2025 | 1,200 | 18 | $1.80 | Informational | High |
Cluster Recommendation: Group "best project management tools for remote teams," "remote team collaboration tools," and "project management for startups" into a Remote Work Tools content pillar. Create a comprehensive comparison guide (2,500+ words) as the pillar page, with supporting blog posts for each long-tail variation.
Show full SKILL.md (495 more words)Show less
Example 2: Content Gap Analysis
Request: Compare keyword portfolio of supportbot.io against competitors intercom.com and zendesk.com.
Gap Analysis:
| Keyword | supportbot.io Rank | intercom.com Rank | zendesk.com Rank | Opportunity |
|---|---|---|---|---|
| ai chatbot for customer service | Not ranking | #4 | #7 | Create new pillar page |
| automated ticket routing | Not ranking | #8 | #3 | Create feature page + blog post |
| customer support metrics | #18 | #5 | #2 | Optimize existing page — page 2 → page 1 |
| help desk software comparison | Not ranking | #6 | #1 | Create comparison landing page |
| reduce support ticket volume | #15 | #11 | #9 | Update and expand existing content |
| chatbot vs live chat | Not ranking | #3 | #12 | Create informational blog post |
Recommendations:
- Highest-impact opportunity: Create a pillar page targeting "ai chatbot for customer service" (3,600 vol, difficulty 42). Both competitors rank but neither holds position #1.
- Quick win: The page ranking #18 for "customer support metrics" needs updated statistics, expanded sections on CSAT and NPS, and 3–5 internal links from related content.
Best Practices
- Start with commercial and transactional intent keywords. These drive revenue directly. Layer in informational keywords to build topical authority and capture top-of-funnel traffic over time.
- Target keywords with difficulty scores below your site's Domain Authority. A site with DA 30 should focus on keywords with difficulty under 35 to achieve realistic first-page rankings within 3–6 months.
- Group keywords into clusters, not individual targets. A single page should target a primary keyword plus 5–10 semantically related terms. This matches how search engines understand topics.
- Validate volume estimates with multiple signals. Search volume data from any single tool can be inaccurate by 30–50%. Cross-reference with Google Trends, Search Console impression data, and paid campaign data when available.
- Revisit keyword research quarterly. Search behavior shifts with trends, product launches, and algorithm updates. Re-run gap analysis each quarter to catch emerging opportunities.
- Map every keyword to a specific URL or planned content piece. Keywords without assigned content are wasted research. Maintain a keyword-to-URL mapping sheet as a living document.
Edge Cases
- Zero-volume keywords with high conversion intent. Long-tail keywords like "best CRM for 3-person real estate teams" may show zero volume in tools but drive highly qualified traffic. Estimate value from related keyword clusters and business alignment rather than volume alone.
- Branded competitor keywords. Targeting "Zendesk alternatives" is a valid strategy, but the user should create genuinely comparative content rather than misleading pages. Some brands actively monitor and DMCA misuse of their trademarks.
- Highly seasonal or trending keywords. For topics driven by events (elections, product launches, holidays), standard volume averages are misleading. Use Google Trends to identify the spike window and plan content publication 4–6 weeks before the peak.
- Multilingual or regional keyword variations. The same product may be searched differently by region — "mobile phone" (UK) vs "cell phone" (US). Run separate research per locale and avoid assuming translation equivalence.
- YMYL (Your Money or Your Life) topics. Keywords in health, finance, and legal niches face stricter E-E-A-T requirements. Content must demonstrate author expertise and cite authoritative sources, or it will not rank regardless of keyword targeting.
© seb1n, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in marketing-and-seo/keyword-research of seb1n/awesome-ai-agent-skills.
Open the folder on GitHubat commit 75865a5
Compare with similar skills
Keyword Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Keyword Research this skillseb1n/awesome-ai-agent-skills | 206 | — | ~2.2k | Automated safety check: Pass | MIT | |
| SEO Keyword ClusteringAgriciDaniel/claude-seo | 19k | 2 repos | ~3.3k | Automated safety check: Pass | MIT | |
| Evaluate Skillevery-app/open-seo | 23k | — | ~1.8k | Automated safety check: Notes | MIT | |
| SEO Content Brief GeneratorAgriciDaniel/claude-seo | 19k | 2 repos | ~2.6k | Automated safety check: Pass | MIT | |
| Blog GoogleAgriciDaniel/claude-blog | 2.3k | 1 repos | ~3.3k | Automated safety check: Notes | MIT | |
| FLOW SEO FrameworkAgriciDaniel/claude-seo | 19k | 2 repos | ~1.4k | Automated safety check: Pass | MIT |
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Questions about Keyword Research
What does Keyword Research do?
Conduct comprehensive keyword research to identify high-value search terms, map search intent, and uncover content gaps for SEO and content marketing. Keyword Research is an agent skill from seb1n/awesome-ai-agent-skills. Conduct comprehensive keyword research to identify high-value search terms, map search intent, and uncover content gaps for SEO and content marketing.
When should I use Keyword Research?
Keyword Research fits situations like: the user requests keyword research; provides relevant inputs for this workflow.
How do I install Keyword Research in Claude Code?
Run `npx skills add seb1n/awesome-ai-agent-skills --skill keyword-research -a claude-code`. Or copy the skill folder (marketing-and-seo/keyword-research in seb1n/awesome-ai-agent-skills) into .claude/skills/keyword-research in your project. Claude Code loads it when a task matches its description.
How do I install Keyword Research in Codex?
Run `npx skills add seb1n/awesome-ai-agent-skills --skill keyword-research -a codex`. Or copy the skill folder (marketing-and-seo/keyword-research in seb1n/awesome-ai-agent-skills) into .agents/skills/keyword-research in your project. Codex loads it when a task matches its description.
Can I use Keyword Research in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seb1n/awesome-ai-agent-skills --skill keyword-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/keyword-research, .gemini/skills/keyword-research, .github/skills/keyword-research and .opencode/skills/keyword-research in your project.
What does Keyword Research need to run?
SKILL.md names no scripts, command-line tools or credentials: Keyword Research is instructions for the agent only.
Does Keyword Research access the network?
SKILL.md names 1 domain. In commands or code: supportbot.io; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Keyword Research safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Keyword Research use?
Keyword Research is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Keyword Research use?
About 2.2k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Keyword Research?
Skills that share tags, products or a category with Keyword Research: SEO Keyword Clustering (AgriciDaniel/claude-seo, 19k stars), Evaluate Skill (every-app/open-seo, 23k stars), SEO Content Brief Generator (AgriciDaniel/claude-seo, 19k stars) and Blog Google (AgriciDaniel/claude-blog, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Keyword Research?
seb1n (a GitHub user) maintains it in seb1n/awesome-ai-agent-skills, which has 206 GitHub stars. The repository holds 101 skills in this directory. The repository was last updated on August 9, 2026.
Source: seb1n/awesome-ai-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.