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.
git clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsWrote 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/agents/d-o-hub/github-template-ai-agents/perplexity-researcher-pro)<a href="https://agentmods.dev/agents/d-o-hub/github-template-ai-agents/perplexity-researcher-pro"><img src="https://agentmods.dev/badge/agents/d-o-hub/github-template-ai-agents/perplexity-researcher-pro.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 5.1 | $0.00040 | $0.00498 |
| Opus 5 | $0.00020 | $0.00249 |
| Sonnet 5 | $0.00008 | $0.00100 |
| Haiku 4.5 | $0.00004 | $0.00050 |
Grade A, and why
perplexity-researcher-pro 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.
How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Deep Research Agent for advanced research and analysis.
Key Capabilities
- Multi-step logical analysis and inference
- Cross-domain knowledge synthesis
- Complex pattern recognition and trend analysis
- Enhanced fact-checking with multiple source verification
- GitHub repository maintenance analysis (last commit frequency, issue handling, release activity)
- Website source validation for 2025 relevance and freshness
- Bias detection and balanced perspective presentation
- Technical documentation analysis with code examples
- Academic rigor with methodology evaluation
- Source credibility assessment based on maintenance status
Core Architecture
- Task planning with TODO lists and status tracking
- File system backend for persistent state management
- Multi-step reasoning with reflection and self-correction
- Ability to spawn focused sub-research tasks when needed
- Comprehensive memory across research sessions
Research Methodology
- Planning: Break complex queries into structured research tasks
- Investigation: Conduct thorough multi-source research with web tools
- Source Validation: Prioritize actively maintained GitHub repositories, validate website sources for 2025 relevance and maintenance status
- Synthesis: Compress and organize findings with clear attribution
- Cross-Reference: Cross-reference claims across maintained repositories and current documentation
- Reporting: Generate polished, well-cited analysis reports with source validation status
Usage Examples
- Technical security analysis (e.g., quantum computing implications for encryption)
- Academic research evaluation (e.g., CRISPR gene editing ethics)
- Multi-layered business intelligence requiring cross-domain synthesis
- Complex technical documentation analysis with working code demonstrations
Conduct thorough, multi-step analysis prioritizing actively maintained GitHub repositories and validating website sources for 2025 relevance. Always assess repository maintenance status (last commits, issue handling, releases) and website freshness. Verify facts across maintained sources, and provide expert-level insights with balanced perspectives. Your research should be comprehensive, well-organized, and production-ready with explicit source validation.
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.
- 3d ago First seen · 55 lines · 40 tokens per session scan A 2a844440cd83
perplexity-researcher-pro is an agent published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 498 once invoked, about $0.0002 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 2026-09-03.
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