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.
npx skills add pccaza/keyword-research-mcp --skill keyword-researchgit clone --depth 1 https://github.com/pccaza/keyword-research-mcpWrote 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.
[](https://agentmods.dev/skills/pccaza/keyword-research-mcp/keyword-research)<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.
<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>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00069 | $0.01423 |
| Opus 5.5 | $0.00028 | $0.00569 |
| Sonnet 5.5 | $0.00014 | $0.00285 |
| Haiku 4.5 | $0.00007 | $0.00142 |
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 2mo 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.
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 withseed_keywords(up to 20),seed_url(one page), orseed_site(a whole domain). Plain-textlocation(defaultUnited States) andlanguage_code(defaulten). Returns rows sorted by average monthly searches, descending; rows belowmin_avg_monthly_searches(default10) are dropped. Paginate withcursor.resolve_geo_targets— list exact Google Ads locations for a place name. Only needed when a plain-textlocationis 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
-
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.
-
Discover. Call
generate_keyword_ideasonce:- If you have a target site:
seed_site= the domain (orseed_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; keepmin_avg_monthly_searchesandpage_sizeat their defaults.
- If you have a target site:
-
Expand once. Take the 5–10 most relevant results and run
generate_keyword_ideasagain with them asseed_keywords. This surfaces the long-tail around the terms that matter. Paginate the first call withcursoronly if you still need a bigger pool.
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.
- 2mo ago First seen · 107 lines · 69 tokens per session scan A e21c5f798a59
keyword-research is a skill published in the GitHub repository pccaza/keyword-research-mcp (0 stars, last pushed 12d ago), licensed MIT. It adds 69 tokens to every session and 1,423 once invoked, about $0.0003 per session on Opus 5.5. 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.
keyword-research compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| keyword-researchpccaza/keyword-research-mcp | Skill | 0 | 12d ago | MIT | A | 69 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
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