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Deep Search
by
aiwithabidi
· GitHub ↗
· v1.0.0
400
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Install in OpenClaw
/install deep-search
Description
Perplexity-powered AI search with auto model tier selection for quick facts, research, or deep analysis across web, academic, news, YouTube, and Reddit.
README (SKILL.md)
Deep Search 🔍
Multi-tier Perplexity-powered search with automatic Langfuse observability tracing.
When to Use
- Quick facts and simple lookups →
quicktier - Standard research, comparisons, how-to →
protier - Deep analysis, market research, complex questions →
deeptier - Academic paper search, news monitoring, Reddit/YouTube research
Usage
# Quick search (sonar, ~2s)
python3 {baseDir}/scripts/deep_search.py quick "what is OpenClaw"
# Pro search (sonar-pro, ~5-8s)
python3 {baseDir}/scripts/deep_search.py pro "compare Claude vs GPT-4o for coding"
# Deep research (sonar-reasoning-pro, ~10-20s)
python3 {baseDir}/scripts/deep_search.py deep "full market analysis of AI agent frameworks"
# Focus modes
python3 {baseDir}/scripts/deep_search.py pro "query" --focus academic
python3 {baseDir}/scripts/deep_search.py pro "query" --focus news
python3 {baseDir}/scripts/deep_search.py pro "query" --focus youtube
python3 {baseDir}/scripts/deep_search.py pro "query" --focus reddit
Tiers
| Tier | Model | Speed | Best For |
|---|---|---|---|
| quick | sonar | ~2s | Simple facts, quick lookups |
| pro | sonar-pro | ~5-8s | Research, comparisons |
| deep | sonar-reasoning-pro | ~10-20s | Deep analysis, complex questions |
Environment
PERPLEXITY_API_KEY— Required. Perplexity API key.OPENROUTER_API_KEY— Optional. For Langfuse tracing model pricing.
Credits
Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.
📅 Need help setting up OpenClaw for your business? Book a free consultation
Usage Guidance
Before installing or running this skill:
- Expect to supply a Perplexity API key (PERPLEXITY_API_KEY or PPLX_API_KEY); the registry metadata should state this but currently does not — ask the publisher to correct the manifest.
- Review the bundled script locally. It will try to read ~/.openclaw/openclaw.json for keys — if you don't want that, either remove that code or ensure the file contains no sensitive data.
- The script contains hardcoded Langfuse keys and a default LANGFUSE_HOST. These could cause your queries/results to be sent to a tracing/observability endpoint controlled by the publisher (or by the embedded host). If you are concerned about telemetry or data leakage, remove or override those env defaults before running, or run the skill in an isolated environment.
- Ensure you trust the author (agxntsix) and the included langfuse tracing behavior; request clarification on why default secret keys are embedded and what data is sent to Langfuse.
- Consider running the script in an ephemeral container or VM, or inspect network traffic, until you are satisfied the tracing endpoint and keys are safe.
If the publisher can (a) remove embedded keys, (b) update registry metadata to declare required env vars and dependencies, and (c) clearly document tracing behavior and opt-out, the incoherence and privacy concerns would be largely resolved.
Capability Analysis
Type: OpenClaw Skill
Name: deep-search
Version: 1.0.0
The skill bundle appears benign. The `SKILL.md` instructions are clear and do not contain any prompt injection attempts. The `deep_search.py` script performs web searches using the legitimate Perplexity API and includes optional Langfuse tracing to an internal host (`http://langfuse-web:3000`), which is an observability feature, not data exfiltration to an external malicious entity. The script attempts to retrieve the `PERPLEXITY_API_KEY` from environment variables or a specific path within `~/.openclaw/openclaw.json`, which is a common and likely intended mechanism for OpenClaw skills to access API keys for their operation, not an attempt to steal arbitrary secrets.
Capability Assessment
Purpose & Capability
The name/description claim Perplexity-powered, multi-tier web/academic/news/YouTube/Reddit search and the code indeed calls Perplexity's API. However registry metadata declares no required environment variables while SKILL.md and the script require a Perplexity API key (PERPLEXITY_API_KEY or PPLX_API_KEY) and will also try to read ~/.openclaw/openclaw.json for keys. The mismatch between declared requirements and actual behavior is incoherent and should be corrected.
Instruction Scope
SKILL.md instructs running the provided Python script which is consistent with the purpose. The runtime script however: (1) attempts to read the user's OpenClaw config at ~/.openclaw/openclaw.json (not documented in the registry metadata), (2) sets default Langfuse environment keys inside the process (hardcoded secrets), and (3) will attempt to use an optional langfuse client to trace observations — which may transmit query text and results to a tracing endpoint. Reading the user's config file and sending traces are beyond the narrow 'search' description unless explicitly disclosed.
Install Mechanism
This is instruction + bundled script only (no install spec), which is low install-risk. The script requires third-party Python packages (requests; optionally langfuse) but these dependencies are not declared in the manifest. No external archive downloads or installers are used.
Credentials
The SKILL.md and code expect a Perplexity API key (PERPLEXITY_API_KEY or PPLX_API_KEY), but the registry metadata lists none — a concerning omission. The script also unilaterally sets LANGFUSE_SECRET_KEY and LANGFUSE_PUBLIC_KEY defaults (hardcoded secrets) and LANGFUSE_HOST to http://langfuse-web:3000; these embedded keys could enable telemetry/tracing to a third-party Langfuse instance without the user's explicit configuration or consent. The skill also searches for credentials in a local OpenClaw config file (~/.openclaw/openclaw.json), which increases the scope of local data access.
Persistence & Privilege
The skill does not request always: true, does not modify system-wide settings, and does not persistently write configuration. It only sets process-level environment defaults and attempts to read a local config file for an API key. That read is scoped to a single file path (the OpenClaw config) rather than broad filesystem access.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install deep-search - After installation, invoke the skill by name or use
/deep-search - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of deep-search: a multi-tier, Perplexity-powered AI web search tool with automatic routing and focus modes.
- Supports three search tiers: quick (facts), pro (comparisons), and deep (analysis), auto-selected by query complexity
- Integrates focus modes for targeted searching: internet, academic, news, YouTube, and Reddit
- Requires a Perplexity API key; optional OpenRouter API key for enhanced tracing
- Suitable for research, fact-checking, and competitive analysis tasks
- Command-line interface for easy tier and focus selection
Metadata
Frequently Asked Questions
What is Deep Search?
Perplexity-powered AI search with auto model tier selection for quick facts, research, or deep analysis across web, academic, news, YouTube, and Reddit. It is an AI Agent Skill for Claude Code / OpenClaw, with 400 downloads so far.
How do I install Deep Search?
Run "/install deep-search" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Deep Search free?
Yes, Deep Search is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Deep Search support?
Deep Search is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Deep Search?
It is built and maintained by aiwithabidi (@aiwithabidi); the current version is v1.0.0.
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