PP: Deep Research

A command for sending a question to Perplexity’s deep-research mode, which investigates a topic across multiple sources and perspectives.

In plain words
What is it for?
Use it for academic research, market analysis, or other complex questions requiring detailed, sourced findings in Chinese.
Why use it?
It provides a repeatable way to request a more comprehensive investigation when the task can take longer.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/escapewu/perplexity-ai/research
Clone the repo
git clone --depth 1 https://github.com/escapeWu/perplexity-ai

Made for: Claude Code.

Per session 14 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 194 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00014 $0.00194
Opus 5 $0.00007 $0.00097
Sonnet 5 $0.00003 $0.00039
Haiku 4.5 $0.00001 $0.00019

Measured 3d ago against content hash 26879cd5a09e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

PP: Deep Research 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 3d 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.

.claude/commands/pp/research.md · 26 lines

What it actually says

Overview Use Perplexity deep research mode for the most comprehensive and thorough investigation.

Features

  • Most comprehensive research mode
  • Extensively explores multiple sources and perspectives
  • Takes longer but provides the most thorough answers
  • Best for academic research, market analysis, and complex investigations

Steps

  1. Use mcp__perplexity-mcp__research tool with the user's query.
  2. Set mode: "deep research" explicitly.
  3. Do NOT set model parameter (deep research mode does not accept model).
  4. Set language: "zh-CN" for Chinese responses.
  5. Present the results with detailed analysis and sources.

Query: $ARGUMENTS

Changes

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.

  1. 3d ago First seen · 26 lines · 0 tokens per session scan A 26879cd5a09e

Subscribe to this mod's changes

PP: Deep Research is a command published in the GitHub repository escapeWu/perplexity-ai (164 stars, last pushed 14d ago), licensed MIT. It adds 14 tokens to every session and 194 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.