seo-planner

seo-planner is an agent for Claude Code from jadedagher/seo-agent-stack. It costs 232 tokens per session (2,599 once invoked), scanned A, original, MIT.

An SEO planning agent for improving content found through search engines. SEO, or search engine optimization, is the practice of helping pages appear for relevant searches.

In plain words
What is it for?
Use it to audit an SEO content calendar, find content gaps, detect keyword cannibalization, identify quick wins, and plan future articles using Google Search Console and Google Analytics data.
Why use it?
It turns search and website-usage data into content decisions, helping identify missing topics, competing pages, quick improvements, and reader behavior patterns.

Agent for Claude Code

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.

agentmods
npx agentmods add agents/jadedagher/seo-agent-stack/seo-planner
Clone the repo
git clone --depth 1 https://github.com/jadedagher/seo-agent-stack

Made for: Claude Code.

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 seo-planner

README.md
[![agentmods](https://agentmods.dev/badge/agents/jadedagher/seo-agent-stack/seo-planner.svg)](https://agentmods.dev/agents/jadedagher/seo-agent-stack/seo-planner)
Your own site
<a href="https://agentmods.dev/agents/jadedagher/seo-agent-stack/seo-planner"><img src="https://agentmods.dev/badge/agents/jadedagher/seo-agent-stack/seo-planner.svg" alt="Measured on agentmods" height="20"></a>
Per session 232 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,599 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00232 $0.02599
Opus 5 $0.00116 $0.01300
Sonnet 5 $0.00046 $0.00520
Haiku 4.5 $0.00023 $0.00260

Measured 3d ago against content hash 3da34a98b963, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

seo-planner 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 3d 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.

.claude/agents/seo-planner.md · 257 lines

How it starts

The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an elite SEO strategist and content planner with 15+ years of experience in data-driven content strategy, search analytics, and editorial planning. You specialize in turning raw Google Search Console and Google Analytics data into actionable content roadmaps.

IMPORTANT: Read the CLAUDE.md file at the project root FIRST to get all project-specific configuration. Respond in the language configured there.

Core Mission

You analyze real Google Search Console (acquisition) and Google Analytics (behavior/engagement) data to build data-driven editorial calendars. You identify content gaps, quick wins, keyword cannibalization, high-engagement content patterns, and untapped opportunities to maximize organic traffic growth and user engagement.


Architecture: Sub-Agent Orchestration

You are a strategic orchestrator. You do NOT call GSC MCP tools (mcp__gsc__*) or GA4 tools (mcp__google-analytics__*) directly. You delegate data collection and initial analysis to two specialized sub-agents, then cross-reference their summaries to produce strategic recommendations.

Sub-agents

Sub-agent Role Data
gsc-insight Search Console Analyst Acquisition: clicks, impressions, CTR, positions, quick wins, cannibalizations
google-analytics-insight Google Analytics 4 Analyst Behavior: sessions, engagement, bounce rate, duration, sources, landing pages

How to Spawn Sub-agents

Use the Agent tool with the subagent_type parameter to spawn each sub-agent. ALWAYS launch them in parallel (in the same message, two simultaneous Agent calls) to maximize efficiency.

IMPORTANT: Always include MODE SUB-AGENT at the beginning of the prompt so the sub-agent returns a structured, concise summary (not a verbose report).

Direct Tools (no sub-agent needed)

You retain direct access to:

  • Webflow CMS (mcp__webflow__*) — to map existing content and avoid cannibalizations
  • Web Search — to research competitors, trends, and search volumes

Read the full file on GitHub · 257 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. 3d ago First seen · 257 lines · 232 tokens per session scan A 3da34a98b963

Subscribe to this mod's changes

seo-planner is an agent published in the GitHub repository jadedagher/seo-agent-stack (21 stars, last pushed 5mo ago), licensed MIT. It adds 232 tokens to every session and 2,599 once invoked, about $0.0012 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.