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 ItamarZand88/awesome-agent-conventions --skill seo-keyword-researchgit clone --depth 1 https://github.com/ItamarZand88/awesome-agent-conventionsWrote 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/itamarzand88/awesome-agent-conventions/seo-keyword-research)<a href="https://agentmods.dev/skills/itamarzand88/awesome-agent-conventions/seo-keyword-research"><img src="https://agentmods.dev/badge/skills/itamarzand88/awesome-agent-conventions/seo-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/itamarzand88/awesome-agent-conventions/seo-keyword-research"><img src="https://agentmods.dev/badge/skills/itamarzand88/awesome-agent-conventions/seo-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 | $0.00000 | $0.01942 |
| Opus 5 | $0.00000 | $0.00971 |
| Sonnet 5 | $0.00000 | $0.00388 |
| Haiku 4.5 | $0.00000 | $0.00194 |
Grade A, and why
seo-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 12d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: keyword-research description: 'Use when the user asks to "find keywords", "挖词", or "搜什么词"; prioritizes search volume, keyword difficulty, intent, and topic clusters from provided or connected data. Not for competitor-relative coverage gaps — use content-gap-analysis. 关键词研究/内容选题' version: "9.9.10" license: Apache-2.0 compatibility: "Claude Code and compatible agent-skill hosts" homepage: "https://github.com/aaron-he-zhu/seo-geo-claude-skills" when_to_use: "Use when starting keyword research for a new page, topic, or campaign. Also when the user asks about search volume, keyword difficulty, topic clusters, long-tail keywords, what to write about, 关键词研究, 挖词, 内容选题, or 搜什么词." argument-hint: " [market/language]" metadata: author: aaron-he-zhu version: "9.9.10" geo-relevance: "medium" tags: - seo - geo - keyword-research - search-volume - keyword-difficulty - topic-clusters - search-intent - long-tail-keywords - 关键词研究 - SEO关键词 - キーワード調査 - 키워드분석 - palabras-clave triggers: - "keyword research" - "search volume analysis" - "what should I write about" - "give me keyword ideas" - "how competitive is this keyword" - "Ahrefs keyword explorer alternative" - "Google Keyword Planner alternative" - "关键词分析" - "长尾关键词" - "帮我挖词"
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: topic or seed keyword, target market/language, business goal, site DR, and any user-provided or tool metrics.
- 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, andmemory/research/. - Done when: every shortlisted keyword carries volume + difficulty + intent (or a labeled N/A); keywords are grouped into pillar + cluster hubs; and the deliverable names at least 3 prioritized Quick Win / Growth / GEO opportunities.
- Primary next skill: competitor-analysis when the keyword set is ready for market comparison.
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.
- 12d ago First seen · 122 lines · 0 tokens per session scan A 81bd12a93639
seo-keyword-research is a skill published in the GitHub repository ItamarZand88/awesome-agent-conventions (31 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,942 tokens. 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.
Other skills, from other repositories
image-mosaic
Tiled image mosaic, photo mosaic, image mosaic, collage wallpaper, image grid background, and mozaic asset pipeline from approved real source imagery.
ai-ml-development
AI and machine learning development with PyTorch, TensorFlow, and LLM integration. Use when building ML models, training pipelines, fine-tuning LLMs, or implementing AI features.
case-interview-practice
Interactive consulting case interview practice with structured frameworks, feedback mechanisms, and progressive difficulty. Use when preparing for management consulting interviews, case competitions, or business problem-solving exercises.
i18n-localization
Internationalization and localization for global applications. Use when adding multi-language support, handling regional formats, or preparing apps for global markets.
electron-desktop
Desktop application development with Electron for Windows, macOS, and Linux. Use when building cross-platform desktop apps, implementing native OS features, or packaging web apps for desktop.
finance
Financial analysis expertise for financial modeling (DCF, LBO, M&A), valuation, financial statement analysis, capital allocation, treasury management, and corporate finance decisions. Use when building financial models, analyzing statements, or making investment decisions.