How do I install the Agentkit SEO skill?

Run npx skillmds@latest add gabrielmoreira/agentkit-seo in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Agentkit SEO safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Agentkit SEO?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Agentkit SEO free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Agentkit SEO?

gabrielmoreira (@gabrielmoreira) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Agentkit SEO by gabrielmoreira — Agent Skill

Name: Agentkit SEO
Rating: 4.2 (5 reviews)
Author: gabrielmoreira

Agentkit SEO

Route broad or ambiguous AgentKit SEO work to the right module while keeping context scoped. Use when a request spans multiple surfaces, asks for overall digital-presence strategy, involves provider or install architecture, needs agent-context planning, or the correct platform skill is unclear.

gabrielmoreira Updated Sep 9, 2026 17 repo stars

File contents

AgentKit SEO

Overview

Use this skill as the orchestrator for the whole repository. Its main job is to select the right module skill, avoid loading irrelevant platform rules, and sequence cross-platform work in a sane order.

Routing workflow

Identify the target surface from the request.
Load only the matching module skill unless the user explicitly asks for a cross-platform pass.
If the request spans multiple surfaces, start with agentkit-seo-agent-context-optimization so the factual source of truth is stable before editing platform outputs.
If the request involves technical issues with the skill system, consult the main repository documentation.

For broad requests with no clear surface:

Active applications or job-description tailoring: route to agentkit-seo-cv-ats.
Recruiter discovery or profile search: route to agentkit-seo-linkedin.
Proof-of-work, repositories, or developer credibility: route to agentkit-seo-github or agentkit-seo-web-portfolio, based on the supplied asset.
Audience building, posting strategy, or public conversation loops: route to agentkit-seo-x-twitter.
Conflicting, scattered, or cross-platform facts: route to agentkit-seo-agent-context-optimization first.

Token discipline

Route to one module by default.
Load the agent context file before platform references only when facts, consistency, or cross-surface rewriting matter.
Prefer public URL inspection, local search, or a compact pasted section over asking the user to dump every asset into the prompt.
Summarize inspected inputs and ask for the smallest missing input set.
Do not expand into algorithm explanation unless the user asks why.

Intake workflow

If the user already has an agent context file, ask for or use its explicit path before rewriting platform assets.
If the task spans multiple surfaces, or the user's facts are scattered, recommend creating or repairing the agent context file first.
Do not block a narrow one-off edit on a full context file when the supplied material is already enough.
For public URLs, fetch or inspect public material when tools allow it and cite which source was used.
For private or login-gated surfaces, ask the user for pasted section text, screenshots, exports, or a local text file instead of guessing.
If critical facts are missing, ask only for the minimum extra inputs needed to proceed.

Module map

LinkedIn work: agentkit-seo-linkedin
GitHub work: agentkit-seo-github
CV or ATS work: agentkit-seo-cv-ats
Web portfolio work: agentkit-seo-web-portfolio
X or Twitter work: agentkit-seo-x-twitter
Personal source-of-truth context work: agentkit-seo-agent-context-optimization

More Information

Main Repository: https://github.com/agentkit-seo/agentkit-seo
Documentation: https://agentkit-seo.github.io/
Modules: Includes specialized logic for GitHub, LinkedIn, CV/ATS, Portfolios, and X/Twitter.

---name: agentkit-seodescription: Route broad or ambiguous AgentKit SEO work to the right module while keeping context scoped. Use when a request spans multiple surfaces, asks for overall digital-presence strategy, involves provider or install architecture, needs agent-context planning, or the correct platform skill is unclear.--- # AgentKit SEO ## Overview Use this skill as the orchestrator for the whole repository. Its main job is to select the right module skill, avoid loading irrelevant platform rules, and sequence cross-platform work in a sane order. ## Routing workflow 1. Identify the target surface from the request. 2. Load only the matching module skill unless the user explicitly asks for a cross-platform pass. 3. If the request spans multiple surfaces, start with `agentkit-seo-agent-context-optimization` so the factual source of truth is stable before editing platform outputs. 4. If the request involves technical issues with the skill system, consult the main repository documentation. For broad requests with no clear surface: - Active applications or job-description tailoring: route to `agentkit-seo-cv-ats`. - Recruiter discovery or profile search: route to `agentkit-seo-linkedin`. - Proof-of-work, repositories, or developer credibility: route to `agentkit-seo-github` or `agentkit-seo-web-portfolio`, based on the supplied asset. - Audience building, posting strategy, or public conversation loops: route to `agentkit-seo-x-twitter`. - Conflicting, scattered, or cross-platform facts: route to `agentkit-seo-agent-context-optimization` first. ## Token discipline - Route to one module by default. - Load the agent context file before platform references only when facts, consistency, or cross-surface rewriting matter. - Prefer public URL inspection, local search, or a compact pasted section over asking the user to dump every asset into the prompt. - Summarize inspected inputs and ask for the smallest missing input set. - Do not expand into algorithm explanation unless the user asks why. ## Intake workflow - If the user already has an agent context file, ask for or use its explicit path before rewriting platform assets. - If the task spans multiple surfaces, or the user's facts are scattered, recommend creating or repairing the agent context file first. - Do not block a narrow one-off edit on a full context file when the supplied material is already enough. - For public URLs, fetch or inspect public material when tools allow it and cite which source was used. - For private or login-gated surfaces, ask the user for pasted section text, screenshots, exports, or a local text file instead of guessing. - If critical facts are missing, ask only for the minimum extra inputs needed to proceed. ## Module map - LinkedIn work: `agentkit-seo-linkedin` - GitHub work: `agentkit-seo-github` - CV or ATS work: `agentkit-seo-cv-ats` - Web portfolio work: `agentkit-seo-web-portfolio` - X or Twitter work: `agentkit-seo-x-twitter` - Personal source-of-truth context work: `agentkit-seo-agent-context-optimization` ## More Information - **Main Repository**: [https://github.com/agentkit-seo/agentkit-seo](https://github.com/agentkit-seo/agentkit-seo) - **Documentation**: [https://agentkit-seo.github.io/](https://agentkit-seo.github.io/) - **Modules**: Includes specialized logic for GitHub, LinkedIn, CV/ATS, Portfolios, and X/Twitter.

Frequently asked questions