Install
$ agentstack add skill-promptingcompany-agent-skills-generative-engine-optimization Open-source listing — not yet scanned by AgentStack. Follow the source repository for install instructions.
Security review
⚠ Flagged1 finding(s); flagged for manual review. · v0.1.0 How review works →
- • Prompt-injection patterns
- • Secret / credential exfiltration
- • Dangerous shell & filesystem operations
- • Untrusted network calls
- • Known-malicious package signatures
- high Pipes remote content directly into a shell (remote code execution).
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
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
tpc CLI (required for agent simulation)
tpcCLI installed (tpc --version) — if missing, install with:curl -fsSL https://cli.promptingco.com/install.sh | bash- Authenticated:
tpc auth whoami - Active product set:
tpc product list→tpc product switch
curl -fsSL https://cli.promptingco.com/install.sh | bash # install tpc CLI if missing
tpc auth login
tpc org switch
tpc product switch
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:
- 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.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: promptingcompany
- Source: promptingcompany/agent-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.