mcpField
A
agentkit-seo

agentkit-seo

github.com/rohitg00Marketing & growth2.8k124 installsUpdated 24w ago
Repository

About agentkit-seo

AgentKit SEO is a skill that routes repository-level SEO work to focused modules for LinkedIn, GitHub, CVs, portfolios, and X/Twitter. It prioritizes a single relevant module and uses context optimization first when work spans platforms or facts are scattered.

Key features

  1. 01Route requests to specialized modules
  2. 02Cover LinkedIn, GitHub, CVs, portfolios, and X/Twitter
  3. 03Use context optimization for cross-platform work
  4. 04Gather only the missing inputs needed

Use cases

  1. 01Tailor a CV for an active application
  2. 02Improve discoverability on LinkedIn or GitHub
  3. 03Coordinate consistent updates across profiles

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/rohitg00/awesome-claude-code-toolkit --skill agentkit-seo

After installing, type/agentkit-seoin Claude Code to confirm it loaded.

Details

From the project README

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

Comments

Markdown supported