A command for turning research findings into a ranked opportunity map and an ordered plan for gaining ground on competitors. It focuses on the opportunity size, the method for capturing it, and the order of execution.

Use it to combine client and research data, identify growth opportunities, choose a capture method for each, and produce a sequenced takeover plan.

It turns a diagnosis into concrete priorities instead of leaving the team with only a description of current problems.

growth-plan — Command for Claude Code by prashishh

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.

Clone the repo

git clone --depth 1 https://github.com/prashishh/seo-geo-report-engine

Made for: Claude Code.

Or install seo-geo-report-engine, the plugin that ships this one along with the rest of its 33 skills, 8 commands, 5 agents.

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/prashishh/seo-geo-report-engine/growth-plan/github.svg)](https://agentmods.dev/commands/prashishh/seo-geo-report-engine/growth-plan)

Your own site

<a href="https://agentmods.dev/commands/prashishh/seo-geo-report-engine/growth-plan"><img src="https://agentmods.dev/badge/commands/prashishh/seo-geo-report-engine/growth-plan/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/prashishh/seo-geo-report-engine/growth-plan"><img src="https://agentmods.dev/badge/commands/prashishh/seo-geo-report-engine/growth-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 925 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00023	$0.00925
Opus 5	$0.00012	$0.00463
Sonnet 5	$0.00005	$0.00185
Haiku 4.5	$0.00002	$0.00093

Measured 10d ago against content hash 117bb8d2e6a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

growth-plan 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 10d 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.

commands/growth-plan.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/growth-plan

The prescription pass for $1 (defaults to the active project, resolve with ./bin/mkt config show). Where /discovery-audit answers "where do we stand," this answers "so what do we build to win, in what order, to get on top of the competition." It runs the opportunity-map skill over the diagnostic evidence and produces research/opportunity-map.md: a sized opportunity map, a capture plan with a chosen mechanism per opportunity, and a flank-then-moat takeover thesis.

This is the step the framework used to do only when a brief forced it. Now it is standard: every engagement gets a ranked, mechanism-driven, falsifiable plan, not just a diagnosis.

Steps

Load context + evidence. ./bin/mkt config show --project $1. Read client.yml (the goal, the competitor set, DR/market) and everything already in projects/$1/research/: competitor analysis, keyword map, geo-audit / ai-citation-log, technical audit, backlinks, VOC. If the diagnostics are thin, run /discovery-audit $1 first (or at least competitor-analysis + keyword-research + geo-audit).
Run opportunity-map (methodology: playbooks/opportunity-capture.md):
- Discover the four gaps (demand, AI-citation, format, segment). Fill missing evidence with live pulls: Ahrefs keyword-gap + competitor organic keywords + KD/DR (budget-aware, save to data/), and the web-research probe for GEO open fields and competitor facts.
- Size and rank each cluster Demand x Winnability x Fit; label Greenfield / Contested / Fortress / Trap. Use GA4/GSC to sanity-check fit where access exists; otherwise flag fit as an assumption to validate.
- Pick one capture mechanism per opportunity (programmatic SEO, comparison hub, GEO/AEO play, free tool, education cluster, refresh, local, earned mentions), on evidence not habit. Flag any cluster that depends on data the client does not have as a build-blocker.
- Sequence the takeover flank-then-moat: quick wins -> beachhead expansion -> compounding moat (brand demand, proprietary data/tools, earned authority). Name the ONE competitor you flank and the weakness you exploit; state what you deliberately do NOT attack (the fortress) and why.

Read the full file on GitHub · 59 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.

10d ago First seen · 59 lines · 23 tokens per session scan A 117bb8d2e6a6

Subscribe to this mod's changes

growth-plan is a command published in the GitHub repository prashishh/seo-geo-report-engine (5 stars, last pushed 2mo ago), licensed MIT. It adds 23 tokens to every session and 925 once invoked, about $0.0001 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 2026-08-31.

Marketing and SEO Planning geo marketing marketing-agents seo

seo-geo

SEO/GEO end-to-end along the SITE loop: survey demand and competitors, implement content, tune quality/tech/on-page, and evaluate authority/rankings/reports/memory (--phase survey|implement|tune|evaluate). Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 58 tokens

narrative

Run a brand-narrative & messaging (TALE) workflow: trace the current message and positioning truth, architect the durable message house/voice/story canon, land it consistently across every surface, and evaluate resonance with tests and drift monitoring. Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 59 tokens

social

Run an organic-social (ECHO) workflow: channel portfolio and voice dossiers, platform-native content and calendars, the social-quality gate with a pre-publish go/no-go, community/inbox/crisis operations, and the listening/SOV/dark-social measurement loop. Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 64 tokens

Run a paid-ads (ROAS) workflow: audience segments, account structure, ad creative, experiment design, pre-launch signal QA + the account-audit gate, measurement, and attribution. Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 50 tokens

email

Run an email-marketing (SEND) workflow: deliverability/consent setup, segmentation, email creative, lifecycle flows, newsletter monetization, send-testing, and the email-quality audit gate. Not sure? Use /aaron-marketing:auto.