keyword-research

keyword-research is a skill for Claude Code from opencue/cuecards. It costs 37 tokens per session (1,879 once invoked), scanned A, a copy of alert-manager, MIT.

A research tool for finding and grouping search terms related to a topic, product, or service. It evaluates them using measures such as search intent, competition, and available data when connected.

In plain words
What is it for?
Use it to discover keywords, compare them with competitors, score and cluster them, and create a keyword brief for SEO or GEO planning.
Why use it?
It helps turn a broad topic into an ordered list of content opportunities. This reduces guesswork when planning pages or articles for search engines and AI search systems.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md; mentions Codex.

Good fit Use it to discover keywords, compare them with competitors, score and cluster them, and create a keyword brief for SEO or GEO planning.

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

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/opencue/cuecards/keyword-research.svg)](https://agentmods.dev/skills/opencue/cuecards/keyword-research)
Your own site
<a href="https://agentmods.dev/skills/opencue/cuecards/keyword-research"><img src="https://agentmods.dev/badge/skills/opencue/cuecards/keyword-research.svg" alt="Measured on agentmods" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,879 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 84% 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 $0.00037 $0.01879
Opus 5 $0.00018 $0.00940
Sonnet 5 $0.00007 $0.00376
Haiku 4.5 $0.00004 $0.00188

Measured 3d ago against content hash 9ba9c46fb8f2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, 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 3d 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

84% identical to alert-manager — 153 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.

.agents/skills/keyword-research/SKILL.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Keyword Research

Discovers, scores, and clusters keywords for SEO and GEO planning.

Quick Start

Research keywords for [topic/product/service]
What keywords is [competitor URL] ranking for that I should target?

Skill Contract

Expected output: a prioritized keyword brief plus the standard handoff summary for memory/research/.

  • Reads: goals, market inputs, tool data, and prior strategy from AGENTS.md and the shared State Model when available.
  • Writes: a user-facing research deliverable and reusable summary.
  • Promotes: durable keyword priorities, competitor facts, and pending strategy decisions to memory/hot-cache.md, memory/open-loops.md, and memory/research/.
  • Primary next skill: competitor-analysis when the keyword set is ready for market comparison.

Handoff Summary

Emit the standard shape from skill-contract.md §Handoff Summary Format.

Data Sources

Optional integrations: ~~SEO tool, ~~search console. Without tools, ask for seed keywords, audience, goals, and any known metrics. See CONNECTORS.md.

Instructions

When a user requests keyword research, run eight phases and announce each as [Phase X/8: Name]:

  1. Scope — clarify product, audience, business goal, DR, geography, and language.
  2. Discover — seed from core, problem, solution, audience, and industry terms.
  3. Variations — expand with modifiers and long-tail patterns.
  4. Classify — tag by intent (informational, navigational, commercial, transactional).
  5. Score — assign difficulty (1-100) and compute Opportunity = (Volume × Intent Value) / Difficulty, with Intent Value 1 / 1 / 2 / 3.
  6. GEO-Check — flag AI-answer-friendly queries such as questions, definitions, comparisons, lists, and how-tos.
  7. Cluster — group keywords into pillar + cluster topic hubs.
  8. Deliver — output an Executive Summary, Quick Wins / Growth / GEO opportunities, Topic Clusters, Content Calendar, and Next Steps.

Read the full file on GitHub · 135 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. 3d ago First seen · 135 lines · 37 tokens per session scan A 9ba9c46fb8f2

Subscribe to this mod's changes

keyword-research is a skill published in the GitHub repository opencue/cuecards (5 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 1,879 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to alert-manager, differing in 153 lines, and is treated as a copy.

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