keyword-research

keyword-research is a skill for Claude Code from ViryaZheng/recomby-geo. It costs 91 tokens per session (2,307 once invoked), scanned A, a copy of keyword-research, MIT.

A tool for finding and organizing search terms people use online, then grouping them into related topics and content plans. SEO means improving content so it can appear in search results, while GEO here means preparing content for generative search systems.

In plain words
What is it for?
Use it to discover keywords, classify what searchers want, assess ranking difficulty, score opportunities, build topic clusters, and plan content calendars.
Why use it?
It helps replace guesswork with a prioritized view of search demand, competition, user intent, and business relevance.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the recomby-geo plugin — 9 skills, 7 commands shipped together

Good fit Use it to discover keywords, classify what searchers want, assess ranking difficulty, score opportunities, build topic clusters, and plan content calendars.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/viryazheng/recomby-geo/keyword-research
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ViryaZheng/recomby-geo --skill keyword-research
Clone the repo
git clone --depth 1 https://github.com/ViryaZheng/recomby-geo

Made for: Claude Code.

Or install recomby-geo, the plugin that ships this one along with the rest of its 9 skills, 7 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for keyword-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/viryazheng/recomby-geo/keyword-research/github.svg)](https://agentmods.dev/skills/viryazheng/recomby-geo/keyword-research)
Your own site
<a href="https://agentmods.dev/skills/viryazheng/recomby-geo/keyword-research"><img src="https://agentmods.dev/badge/skills/viryazheng/recomby-geo/keyword-research/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for keyword-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/viryazheng/recomby-geo/keyword-research"><img src="https://agentmods.dev/badge/skills/viryazheng/recomby-geo/keyword-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 91 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,307 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 97% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00091 $0.02307
Opus 5 $0.00046 $0.01154
Sonnet 5 $0.00018 $0.00461
Haiku 4.5 $0.00009 $0.00231

Measured 13d ago against content hash 3b45f58f2b75, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

keyword-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

97% identical to keyword-research — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/recomby-geo/skills/keyword-research/SKILL.md · 302 lines

How it starts

The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Keyword Research

Discovers, analyzes, and prioritizes keywords for SEO and GEO content strategies. Identifies high-value opportunities based on search volume, competition, intent, and business relevance.

When This Must Trigger

Use this when the conversation involves any of these situations — even if the user does not use SEO terminology:

Use this whenever the task needs reusable market intelligence that should influence strategy, not just an ad hoc answer.

  • Starting a new content strategy or campaign
  • Expanding into new topics or markets
  • Finding keywords for a specific product or service
  • Identifying long-tail keyword opportunities
  • Understanding search intent for your industry
  • Planning content calendars
  • Researching keywords for GEO optimization

What This Skill Does

  1. Keyword Discovery: Generates comprehensive keyword lists from seed terms
  2. Intent Classification: Categorizes keywords by user intent (informational, navigational, commercial, transactional)
  3. Difficulty Assessment: Evaluates competition level and ranking difficulty
  4. Opportunity Scoring: Prioritizes keywords by potential ROI
  5. Clustering: Groups related keywords into topic clusters
  6. GEO Relevance: Identifies keywords likely to trigger AI responses

Quick Start

Start with one of these prompts.

Basic Keyword Research

Research keywords for [topic/product/service]
Find keyword opportunities for a [industry] business targeting [audience]

With Specific Goals

Find low-competition keywords for [topic] with commercial intent
Identify question-based keywords for [topic] that AI systems might answer

Competitive Research

What keywords is [competitor URL] ranking for that I should target?

Data Sources

Note: All integrations are optional. This skill works without any API keys — users provide data manually when no tools are connected.

With ~~SEO tool + ~~search console connected: Automatically pull historical search volume data, keyword difficulty scores, SERP analysis, current rankings from ~~search console, and competitor keyword overlap. The skill will fetch seed keyword metrics, related keyword suggestions, and search trend data.

Read the full file on GitHub · 302 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 302 lines · 91 tokens per session scan A 3b45f58f2b75

Subscribe to this mod's changes

keyword-research is a skill published in the GitHub repository ViryaZheng/recomby-geo (454 stars, last pushed 2mo ago), licensed MIT. It adds 91 tokens to every session and 2,307 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to keyword-research, differing in 14 lines, and is treated as a copy.