keyword-research

keyword-research is a skill for Claude Code from RightBlogger/bloggingskills. It costs 93 tokens per session (817 once invoked), scanned A, original, MIT.

A research workflow that turns a topic idea into search terms for a blog post or group of related posts. It selects one main term, groups related terms by what people intend to find, and records readers' questions.

In plain words
What is it for?
Use it to choose a blog topic's main search term, organise supporting terms, and plan content around informational, commercial, or other search intentions.
Why use it?
It prevents writers from choosing phrases that sound right but do not match how people search. It also accounts for differences between countries and languages.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the blogging-skills plugin — 12 skills shipped together

Good fit Use it to choose a blog topic's main search term, organise supporting terms, and plan content around informational, commercial, or other search intentions.

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

Made for: Claude Code.

Or install blogging-skills, the plugin that ships this one along with the rest of its 12 skills.

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/rightblogger/bloggingskills/keyword-research/github.svg)](https://agentmods.dev/skills/rightblogger/bloggingskills/keyword-research)
Your own site
<a href="https://agentmods.dev/skills/rightblogger/bloggingskills/keyword-research"><img src="https://agentmods.dev/badge/skills/rightblogger/bloggingskills/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/rightblogger/bloggingskills/keyword-research"><img src="https://agentmods.dev/badge/skills/rightblogger/bloggingskills/keyword-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 817 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 $0.00093 $0.00817
Opus 5 $0.00046 $0.00409
Sonnet 5 $0.00019 $0.00163
Haiku 4.5 $0.00009 $0.00082

Measured 11d ago against content hash bff86226b774, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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 · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Keyword research

You take a seed topic and return a keyword set a writer can actually use: one primary keyword, related terms sorted by intent, and the real questions readers ask. You pick the phrase people search, not the phrase that sounds tidy.

Initial assessment

  • If .agents/blog-context.md exists, read it first. It tells you the site's niche, audience, and the country and language to target. Honor those over any default. If no country or language is given and the context does not set one, ask before guessing, or note your assumption in the output.
  • Confirm the seed topic and the target country and language before you start. A keyword that wins in the US can be dead in the UK, and search volume splits by language.

Treat a keyword as a concept, not a string

A keyword is the idea a reader is searching for, not a fixed run of characters to repeat. The writer will inflect it, reorder it, and weave it into sentences later. "best running shoes for flat feet" might appear as "if you have flat feet, the right running shoe" in the draft. Research the concept and the intent behind it. Never hand off a phrase to be stuffed verbatim.

Method

  1. Pick one primary keyword. Choose the proven phrase real people type, not the one that reads cleanest. Favor a term with steady demand and a difficulty the site can plausibly rank for. One post targets one primary idea.
  2. Group related terms by search intent. Sort the supporting terms into informational (how, why, what), commercial or comparison (best, vs, review, alternatives), transactional (buy, price, coupon, near me), and navigational (a brand or product name). This grouping is what tells the writer which sections the post needs.
  3. Surface the real questions. List the questions a reader would type into Google, ChatGPT, or Perplexity. Pull them from autocomplete, "People also ask", related searches, and forum threads. These often become headings or an FAQ.
  4. Note competitiveness and volume qualitatively. You do not need exact numbers. Mark each term as roughly high, medium, or low demand, and flag which ones a smaller site can realistically win. Say so plainly.

Read the full file on GitHub · 73 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 · 73 lines · 93 tokens per session scan A bff86226b774

Subscribe to this mod's changes

keyword-research is a skill published in the GitHub repository RightBlogger/bloggingskills (2 stars, last pushed 2mo ago), licensed MIT. It adds 93 tokens to every session and 817 once invoked, about $0.0005 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.

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