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 skills/g1joshi/agent-skills/perplexitynpx skills add G1Joshi/Agent-Skills --skill perplexitygit clone --depth 1 https://github.com/G1Joshi/Agent-SkillsWrote 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.
[](https://agentmods.dev/skills/g1joshi/agent-skills/perplexity)<a href="https://agentmods.dev/skills/g1joshi/agent-skills/perplexity"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/perplexity.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00017 | $0.00283 |
| Opus 5 | $0.00009 | $0.00142 |
| Sonnet 5 | $0.00003 | $0.00057 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
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 5d 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.
What it actually says
Perplexity
Perplexity is an AI search engine. For developers, the Sonar API provides grounded, cited answers for building search-enabled apps.
When to Use
- Real-time Info: "What is the stock price of Apple?" (LLMs can't answer this without tools).
- Research Apps: Building an app that needs to cite sources.
- Citations: You need reliability and links to original data.
Core Concepts
Sonar API
API access to Perplexity's online models (llama-3-sonar-large-32k-online).
Citations
API returns a list of citations used to generate the answer.
Pro Search
Multi-step reasoning search (Googles multiple times to answer complex queries).
Best Practices (2025)
Do:
- Use for Grounding: If your chatbot needs current events, route those queries to Perplexity.
- Use Search Options: Filter by domain (e.g., search only
reddit.comorstackoverflow.com).
Don't:
- Don't use for creative writing: It is optimized for facts, not fiction.
References
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.
- 5d ago First seen · 44 lines · 17 tokens per session scan A 2a2a12f562b6
perplexity is a skill published in the GitHub repository G1Joshi/Agent-Skills (12 stars, last pushed 6mo ago), licensed MIT. It adds 17 tokens to every session and 283 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 2026-08-30.
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