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 skills add itechmeat/llm-code --skill perplexitygit clone --depth 1 https://github.com/itechmeat/llm-codeWrote 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/itechmeat/llm-code/perplexity)<a href="https://agentmods.dev/skills/itechmeat/llm-code/perplexity"><img src="https://agentmods.dev/badge/skills/itechmeat/llm-code/perplexity/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/itechmeat/llm-code/perplexity"><img src="https://agentmods.dev/badge/skills/itechmeat/llm-code/perplexity.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00051 | $0.02599 |
| Opus 5.5 | $0.00020 | $0.01040 |
| Sonnet 5.5 | $0.00010 | $0.00520 |
| Haiku 4.5 | $0.00005 | $0.00260 |
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 1mo 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 — 360 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Perplexity API
Build AI applications with real-time web search and grounded responses.
Quick Navigation
- Models & pricing:
references/models.md - Search API patterns:
references/search-api.md - Chat completions guide:
references/chat-completions.md - Browser sessions API:
references/browser.md - Embeddings API:
references/embeddings.md - Structured outputs:
references/structured-outputs.md - Filters (domain/language/date/location):
references/filters.md - Media (images/videos/attachments):
references/media.md - Pro Search:
references/pro-search.md - Prompting best practices:
references/prompting.md
When to Use
- Need AI responses grounded in current web data
- Building search-powered applications
- Research tools requiring citations
- Real-time Q&A with source verification
- Document/image analysis with web context
Installation
Install: pip install perplexityai (Python) or npm install @perplexityai/perplexity (TypeScript/JavaScript).
Authentication
# macOS/Linux
export PERPLEXITY_API_KEY="your_api_key_here"
# Windows
setx PERPLEXITY_API_KEY "your_api_key_here"
SDK auto-reads PERPLEXITY_API_KEY environment variable.
Quick Start — Chat Completion
from perplexity import Perplexity
client = Perplexity()
completion = client.chat.completions.create(
model="sonar-pro",
messages=[{"role": "user", "content": "What is the latest news on AI?"}]
)
print(completion.choices[0].message.content)
Note (v0.28.0): The Python client includes a custom JSON encoder to support additional types in request payloads.
Quick Start — Search API
from perplexity import Perplexity
client = Perplexity()
search = client.search.create(
query="artificial intelligence trends 2024",
max_results=5
)
for result in search.results:
print(f"{result.title}: {result.url}")
Release Highlights (0.34.1 -> 0.38.0)
- Streaming:
responses.createnow yields named SSE events and discriminates theResponseStreamEventunion, which matters for typed stream consumers. - Search context:
search_context_sizewas briefly exposed onsearch.create, removed in0.35.1, then reintroduced in0.37.0for both the Search API and theweb_searchtool to control retrieved context size. - Background responses: the SDK adds background-task support and
responses.retrieve, so long-running response workflows can be polled instead of only streamed inline. - Reasoning effort:
xhighis available where the API supports reasoning-effort controls. - Sandbox tool:
0.36.0adds the Responses API sandbox built-in tool;0.38.0adds afilessubresource for retrieving sandbox-produced files. Gate both like other executable/tooling surfaces.
What ships with it
10 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.
- references/browser.md 970 B
- references/chat-completions.md 7.5 KB
- references/embeddings.md 2.2 KB
- references/filters.md 6.4 KB
- references/media.md 6.3 KB
- references/models.md 2.9 KB
- references/pro-search.md 5.7 KB
- references/prompting.md 5.9 KB
- references/search-api.md 7.3 KB
- references/structured-outputs.md 3.9 KB
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.
- 1mo ago First seen · 360 lines · 51 tokens per session scan A 3a57ec3c5407
perplexity is a skill published in the GitHub repository itechmeat/llm-code (24 stars, last pushed 24d ago), licensed MIT. It adds 51 tokens to every session and 2,599 once invoked, about $0.0002 per session on Opus 5.5. 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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