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.
npx agentmods add commands/maccman/growth-agents/setup-perplexitygit clone --depth 1 https://github.com/maccman/growth-agentsWhat 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 | $0.00000 | $0.01076 |
| Opus 5 | $0.00000 | $0.00538 |
| Sonnet 5 | $0.00000 | $0.00215 |
| Haiku 4.5 | $0.00000 | $0.00108 |
Grade A, and why
setup-perplexity 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When the user triggers this command, walk them through setting up the Perplexity API for this project. Run each step automatically. Speak in plain, friendly language.
What is the Perplexity API?
Perplexity's API gives you access to their Sonar models — AI that answers questions with live web search built in. Unlike standard LLMs, every response is grounded in real-time web results with citations. It's great for research tasks, lead enrichment, competitive intelligence, and anything that benefits from up-to-date information.
Steps
1. Get the API key
Ask the user:
"Do you already have a Perplexity API key? If not, you can grab one at perplexity.ai/settings/api — you'll need to sign up and add a payment method. Once you have it, paste it here."
Wait for them to paste the key before continuing.
2. Add the key to .env
Add the key to the .env file in the repo root:
PERPLEXITY_API_KEY=<their key>
Also add the placeholder to .env.example if it's not already there, under the # Web scraping section:
PERPLEXITY_API_KEY=
3. Install the SDK
This project uses the Vercel AI SDK, so install the Perplexity provider:
pnpm add @ai-sdk/perplexity
4. Smoke-test
Run a quick test to confirm the key works:
pnpm start scripts/perplexity-example.ts
Create the script if it doesn't exist:
import { config } from 'dotenv'
import { createPerplexity } from '@ai-sdk/perplexity'
import { generateText } from 'ai'
config()
async function main() {
const perplexity = createPerplexity({ apiKey: process.env.PERPLEXITY_API_KEY })
const { text, sources } = await generateText({
model: perplexity('sonar'),
prompt: 'What is the current valuation of SpaceX? Answer in one sentence.',
})
console.log('Answer:', text)
console.log('\nSources:')
sources?.forEach((s, i) => console.log(` [${i + 1}] ${s.url}`))
}
main().catch(console.error)
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.
- 2d ago First seen · 144 lines · 0 tokens per session scan A cab80bfb6b09
setup-perplexity is a command published in the GitHub repository maccman/growth-agents (5 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,076 tokens. 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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