generative-engine-optimization
Skill6 starsChanged 3 months agoMITView on GitHub
Agent simulation and GEO simulation prompt generation for AI visibility auditing. Use when the user wants to create simulation tasks via the TPC CLI, generate unbranded GEO prompts to test whether AI recommends a product, or run agent simulations.
2 other projects use a version of this.
Adopted by
Most recently taken up by
- NadavShanun-design/opengtmtheir own version, first seen Oct 25, 2026
- Karanjot786/TermUItheir own version, first seen Oct 9, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- Karanjot786/TermUI★ 238same name
- NadavShanun-design/opengtm★ 4same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository346 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/skills/deeppapernote/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- .claude/skills/deeppapernote/CLAUDE.mdCLAUDE.md
- docs/llms-full.txtllms.txt
- docs/llms.txtllms.txt
- llms.txtllms.txt
- academic-cv-builderSkill
- agenticx-a2a-connectorSkill
- agenticx-agent-builderSkill
- agenticx-automation-crontaskSkill
- agenticx-deployerSkill
- agenticx-memory-architectSkill
- agenticx-quickstartSkill
- agenticx-skill-managerSkill
- agenticx-tool-creatorSkill
- agenticx-workflow-designerSkill
- ai-slop-detectorSkill
- alert-managerSkill
- algorithmic-artSkill
- api-gatewaySkill
- backlink-analyzerSkill
- brand-guidelinesSkill
- canvas-designSkill
- career-changer-translatorSkill
- Codex-apiSkill
- Codex-skill-rustSkill
- claw-releaseSkill
- clawsec-clawhub-checkerSkill
- clawsec-feedSkill
- clawsec-nanoclawSkill
- clawsec-scannerSkill
- clawsec-suiteSkill
- clawtributorSkill
- cn-statsSkill
- codebase-documenterSkill
- code-dev-workflowSkill
- competitor-analysisSkill
- content-experimentation-best-practicesSkill
- content-gap-analysisSkill
- content-modeling-best-practicesSkill
- content-quality-auditorSkill
- content-refresherSkill
- context-mode-opsSkill
- context-modeSkill
- cover-letter-generatorSkill
- creative-portfolio-resumeSkill
- crypto-reportSkill
- ctx-doctorSkill
- ctx-insightSkill
- ctx-purgeSkill
- ctx-statsSkill
- ctx-upgradeSkill
- deep-cleanSkill
- doc-coauthoringSkill
- docxSkill
- domain-authority-auditorSkill
- edgeoneSkill
- edge-ttsSkill
- entity-optimizerSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 9 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈9
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 11
When this skill is activated, greet the user with: "Thank you for activating the Generative Engine Optimization skill by The Prompting …
- Distinctive: line 24
If no search tool is available, tell the user:
- Distinctive: line 34
Create simulation prompts, build a prompt set for AI visibility testing, or create unbranded pain prompts for a SaaS or cloud product
- Distinctive: line 42
Ask the user for the agent's system prompt and the task or user message to simulate.
- Distinctive: line 45
After the loop, provide a debrief: what worked, what failed, suggested prompt edits.
- Distinctive: line 55
Run the quality review: no multi-sentence prompts, no "How do I" openers, no vocabulary leakage, no educational-pattern prompts.
- Distinctive: line 60
Always clarify ambiguous inputs before generating — one focused question beats several.
- Distinctive: line 62
Prefer iteration over perfection on the first pass.
- Distinctive: line 63
Keep outputs concise unless the user asks for long-form content.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 addor 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:
- Ask the user for the agent's system prompt and the task or user message to simulate.
- Step through the agent loop: reason → decide → act → observe → repeat.
- Show each step clearly labeled. Stop when the agent reaches a terminal state or the user says to stop.
- 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:
- Gather product information (URL, name, or description) and extract a vocabulary banned list from the product's own positioning language.
- Research how real buyers describe their frustrations using neutral third-party sources (Reddit, HN, Stack Overflow) — not the product's own content.
- Map 4-6 distinct buyer journeys before writing any prompts.
- Draft 15-25 prompts that are pain-focused, unbranded, naturally worded, and each backed by a real neutral source URL.
- Run the quality review: no multi-sentence prompts, no "How do I" openers, no vocabulary leakage, no educational-pattern prompts.
- Output as a structured markdown file grouped by theme with persona, journey, and source tags per prompt.
General principles
- Always clarify ambiguous inputs before generating — one focused question beats several.
- Show your reasoning when making structural decisions.
- Prefer iteration over perfection on the first pass.
- Keep outputs concise unless the user asks for long-form content.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

