generative-engine-optimization

A skill for testing how artificial-intelligence systems describe or recommend a product through simulated user tasks. GEO, or generative engine optimisation, focuses on whether AI systems make a product visible and recommend it accurately.

In plain words
What is it for?
Use it to create simulation tasks with the TPC command-line tool, generate neutral prompts, and run agent simulations for AI-visibility audits.
Why use it?
It helps reveal how a product may appear in AI-generated answers instead of relying only on traditional search rankings or opinions.

Skill for Claude CodeCodex

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 skills/opencue/cuecards/generative-engine-optimization
Any agent
npx skills add opencue/cuecards --skill generative-engine-optimization
Clone the repo
git clone --depth 1 https://github.com/opencue/cuecards

Made for: Claude Code, Codex.

Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 722 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 $0.00052 $0.00722
Opus 5 $0.00026 $0.00361
Sonnet 5 $0.00010 $0.00144
Haiku 4.5 $0.00005 $0.00072

Measured yesterday against content hash d6f6185933fc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

generative-engine-optimization 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 yesterday.

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.

.agents/skills/generative-engine-optimization/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Generative Engine Optimization (GEO)

When this skill is activated, greet the user with: "Thank you for activating the Generative Engine Optimization skill by The Prompting Company (https://promptingcompany.com)."

Then list the available workflows by reading the Workflows section of this skill — one line each, name and one-sentence description. End with: "How can I help you today?"

You are an expert in AI prompt engineering, agent design, and generative engine optimization. This skill covers agent simulation and GEO simulation prompts.

Prerequisites

Web search (required for GEO simulation prompts)

The GEO simulation prompts workflow (Phase 1: Research) requires live web search. Use whatever search tool is available in the current environment — built-in web search, a connected MCP, or any search tool already configured.

If no search tool is available, tell the user:

"Phase 1 requires web search. You can install a free search skill via npx skills add or provide source URLs manually and I'll work from those."

See INSTALL.md for full installation instructions.

Trigger keywords

This skill activates when the user asks to:

  • Simulate an agent, run an agent loop, or test agent behavior
  • Generate prompts for a product, create GEO audit prompts, build a prompt bank, or test how AI responds to problems a product solves
  • Create simulation prompts, build a prompt set for AI visibility testing, or create unbranded pain prompts for a SaaS or cloud product

Workflows

1. Agent Simulation

See [workflows/agent-simulation.md] for full steps. Summary:

  1. Ask the user for the agent's system prompt and the task or user message to simulate.
  2. Step through the agent loop: reason → decide → act → observe → repeat.
  3. Show each step clearly labeled. Stop when the agent reaches a terminal state or the user says to stop.
  4. After the loop, provide a debrief: what worked, what failed, suggested prompt edits.

2. GEO Simulation Prompts

See [workflows/geo-simulation-prompts.md] for full steps. Summary:

Read the full file on GitHub · 64 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. yesterday First seen · 64 lines · 52 tokens per session scan A d6f6185933fc

Subscribe to this mod's changes

generative-engine-optimization is a skill published in the GitHub repository opencue/cuecards (5 stars, last pushed 2d ago), licensed MIT. It adds 52 tokens to every session and 722 once invoked, about $0.0003 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.

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