keywords

keywords is a skill for Claude Code, Codex from ScaleBrick/founder-marketing-skills. It costs 38 tokens per session (1,635 once invoked), scanned A, original, MIT.

A research workflow for finding search phrases that people use on TikTok and Instagram for a particular business. It groups phrases by buying intent and estimates their search demand and competition.

In plain words
What is it for?
Use it to build a content keyword library for tutorials, comparisons, inspiration, or product-related searches. It requires context about the business, audience, and problem being solved.
Why use it?
It helps replace guesses about social content with specific searches from potential customers. The available description does not state that its volume or difficulty figures come from an exact measurement source.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to build a content keyword library for tutorials, comparisons, inspiration, or product-related searches. It requires context about the business, audience, and problem being solved.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/scalebrick/founder-marketing-skills/keywords
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 ScaleBrick/founder-marketing-skills --skill keywords
Clone the repo
git clone --depth 1 https://github.com/ScaleBrick/founder-marketing-skills

Made for: Claude Code, Codex.

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 keywords

README.md
[![agentmods](https://agentmods.dev/badge/skills/scalebrick/founder-marketing-skills/keywords/github.svg)](https://agentmods.dev/skills/scalebrick/founder-marketing-skills/keywords)
Your own site
<a href="https://agentmods.dev/skills/scalebrick/founder-marketing-skills/keywords"><img src="https://agentmods.dev/badge/skills/scalebrick/founder-marketing-skills/keywords/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 keywords

Your own site · 80×15
<a href="https://agentmods.dev/skills/scalebrick/founder-marketing-skills/keywords"><img src="https://agentmods.dev/badge/skills/scalebrick/founder-marketing-skills/keywords.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,635 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 $0.00038 $0.01635
Opus 5 $0.00019 $0.00817
Sonnet 5 $0.00008 $0.00327
Haiku 4.5 $0.00004 $0.00163

Measured 11d ago against content hash 3b0038e5e5fe, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

keywords 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/keywords/SKILL.md · 191 lines

How it starts

The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Keyword Research

You are an SEO strategist finding high-intent search keywords for a business. You use the same framework that powers ScaleBrick's Morgan, the AI VP of Marketing who researches keywords for 10 accounts at scale.

Core principles

  1. Search-first, not viral-first. Every keyword must be something a real person would type into the search bar when looking for help, inspiration, comparisons, tutorials, or tools related to the business niche.

  2. Intent over cleverness. Pick keywords that a buyer of the product would search for. Avoid pure brand awareness fluff that doesn't capture demand.

  3. Compounding library. Treat the keywords as a content library that covers the entire keyword landscape. Not 100 variants of the same phrase. Each keyword should target a meaningfully different cluster.

  4. Concrete, specific, evergreen. Prefer concrete evergreen searches ("how to make a flyer for an event", "free flyer maker no signup") over vague trend chasing.

  5. No hashtags. Keywords are search phrases, not hashtags. No # prefix.

Gather context

Ask the user for:

  1. Business name and what they sell
  2. Who their target audience is
  3. What problem their product solves
  4. Website URL (if available)
  5. Target locale (default: US)
  6. Competitors (if known)

If they've already provided this, don't re-ask.

Research process

Step 1: Generate keyword candidates across four search intents

Aim for this distribution:

Informational (~50%) — learning queries:

  • "how to [achieve goal]"
  • "what is [concept]"
  • "why [pain point]"
  • "best way to [solve problem]"
  • "[topic] for beginners"
  • "[topic] explained"
  • "signs of [condition]"

Commercial (~25%) — evaluation queries:

  • "best [product category]"
  • "[product] vs [product]"
  • "[product] review"
  • "[product] alternative"
  • "is [product] worth it"
  • "[category] comparison"

Transactional (~15%) — ready-to-act queries:

  • "free [tool]"
  • "[tool] template"
  • "[tool] download"
  • "[product] free trial"
  • "[category] app"

Read the full file on GitHub · 191 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 · 191 lines · 38 tokens per session scan A 3b0038e5e5fe

Subscribe to this mod's changes

keywords is a skill published in the GitHub repository ScaleBrick/founder-marketing-skills (95 stars, last pushed 4mo ago), licensed MIT. It adds 38 tokens to every session and 1,635 once invoked, about $0.0002 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 2026-08-30.

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