keyword-research

keyword-research is a skill for Claude Code from pccaza/keyword-research-mcp. It costs 69 tokens per session (1,423 once invoked), scanned A, original, MIT.

A keyword research workflow that uses Google Ads search-volume data to find terms people search for in a specific topic or niche.

In plain words
What is it for?
Use it to discover keywords from seed terms, a webpage, or a whole website, check metrics for a keyword list, and plan content for organic search traffic.
Why use it?
It replaces guesses about search demand with data, while leaving keyword grouping, ranking judgments, and content planning to you.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Good fit Use it to discover keywords from seed terms, a webpage, or a whole website, check metrics for a keyword list, and plan content for organic search traffic.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pccaza/keyword-research-mcp/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 pccaza/keyword-research-mcp --skill keyword-research
Clone the repo
git clone --depth 1 https://github.com/pccaza/keyword-research-mcp

Made for: Claude Code.

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/pccaza/keyword-research-mcp/keyword-research/github.svg)](https://agentmods.dev/skills/pccaza/keyword-research-mcp/keyword-research)
Your own site
<a href="https://agentmods.dev/skills/pccaza/keyword-research-mcp/keyword-research"><img src="https://agentmods.dev/badge/skills/pccaza/keyword-research-mcp/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/pccaza/keyword-research-mcp/keyword-research"><img src="https://agentmods.dev/badge/skills/pccaza/keyword-research-mcp/keyword-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,423 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 original No closer match found 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 $0.00069 $0.01423
Opus 5 $0.00034 $0.00711
Sonnet 5 $0.00014 $0.00285
Haiku 4.5 $0.00007 $0.00142

Measured 11d ago against content hash e21c5f798a59, 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 11d 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.

skills/keyword-research/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Keyword Research

Turn a niche into a shortlist of keywords worth building content around, backed by real Google Ads search-volume data.

Prerequisite: the keyword-research MCP server must be connected. It exposes three tools:

  • generate_keyword_ideas — discover keywords. Seed with seed_keywords (up to 20), seed_url (one page), or seed_site (a whole domain). Plain-text location (default United States) and language_code (default en). Returns rows sorted by average monthly searches, descending; rows below min_avg_monthly_searches (default 10) are dropped. Paginate with cursor.
  • resolve_geo_targets — list exact Google Ads locations for a place name. Only needed when a plain-text location is ambiguous and the tool says so.
  • get_keyword_historical_metrics — fetch metrics for a keyword list you already have (brainstormed, from a competitor, from the user).

The server only fetches and normalizes data. Grouping keywords, judging ranking feasibility, and planning content are your job — this skill covers how.

Default workflow

  1. Frame the niche. Establish three things, asking only if genuinely unclear: the topic/niche, the target website or page (if any), and the target market (country). A site or page URL is a strong seed — use it.

  2. Discover. Call generate_keyword_ideas once:

    • If you have a target site: seed_site = the domain (or seed_url = a specific page you're planning content for).
    • Otherwise: seed_keywords = 3–8 tightly on-topic core terms for the niche. Off-topic seeds pollute every downstream result.
    • location = the target country in plain text; keep min_avg_monthly_searches and page_size at their defaults.
  3. Expand once. Take the 5–10 most relevant results and run generate_keyword_ideas again with them as seed_keywords. This surfaces the long-tail around the terms that matter. Paginate the first call with cursor only if you still need a bigger pool.

Read the full file on GitHub · 107 lines

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. 11d ago First seen · 107 lines · 69 tokens per session scan A e21c5f798a59

Subscribe to this mod's changes

keyword-research is a skill published in the GitHub repository pccaza/keyword-research-mcp (0 stars, last pushed 13d ago), licensed MIT. It adds 69 tokens to every session and 1,423 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens