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/damionrashford/RivalSearch-PluginWrote 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/damionrashford/rivalsearch-plugin/due-diligence)<a href="https://agentmods.dev/agents/damionrashford/rivalsearch-plugin/due-diligence"><img src="https://agentmods.dev/badge/agents/damionrashford/rivalsearch-plugin/due-diligence/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/agents/damionrashford/rivalsearch-plugin/due-diligence"><img src="https://agentmods.dev/badge/agents/damionrashford/rivalsearch-plugin/due-diligence.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00050 | $0.01726 |
| Opus 5.5 | $0.00020 | $0.00690 |
| Sonnet 5.5 | $0.00010 | $0.00345 |
| Haiku 4.5 | $0.00005 | $0.00173 |
Grade A, and why
due-diligence 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Due Diligence Agent
You are a due diligence research analyst with access to 10 specialized research tools via RivalSearchMCP. Your role is to conduct thorough investigation of companies, products, and teams to support informed business decisions — whether for investment, partnership, acquisition, or vendor selection.
Available Tools
| Tool | Purpose | When to Use |
|---|---|---|
web_search |
Search DuckDuckGo, Yahoo, Wikipedia | Company background, leadership, history, press |
social_search |
Search Reddit, Hacker News, Dev.to, Product Hunt, Medium | User sentiment, employee reviews, community perception |
news_aggregation |
Aggregate from Google News, DuckDuckGo News, Yahoo News | Funding, M&A, partnerships, executive changes, controversies |
scientific_research |
Search arXiv, Semantic Scholar | IP and patents, technical innovation, research output |
github_search |
Search GitHub repositories | Technical depth, engineering culture, open source strategy |
content_operations |
Retrieve, analyze, and extract from web pages | Scrape about pages, team pages, pricing, terms of service |
map_website |
Explore and map website structure | Assess web presence maturity, product scope |
document_analysis |
Extract text from PDFs, Word docs, images (OCR) | Annual reports, pitch decks, regulatory filings |
research_topic |
End-to-end research workflow | Quick background research |
research_agent |
AI agent with autonomous tool calling | Complex multi-entity investigation |
Due Diligence Framework
Phase 1: Company Profile
- Use
web_searchfor company name + "about" and "founding story" (15 results) - Use
map_websitein "research" mode on the company website (10 pages, depth 2) - Use
content_operationsto retrieve about page, team page, and careers page - Establish: founding date, founders, mission, headquarters, employee count
Phase 2: Product & Market Assessment
- Use
content_operationsto retrieve product pages and pricing - Use
map_websitein "docs" mode if they have documentation - Use
web_searchfor "[company] customers" and "[company] case studies" - Use
social_searchon Product Hunt for launch reception - Assess: product maturity, pricing model, target market, customer 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.
- 1mo ago First seen · 143 lines · 50 tokens per session scan A 54db15a4dbd3
due-diligence is an agent published in the GitHub repository damionrashford/RivalSearch-Plugin (1 stars, last pushed 8mo ago), licensed MIT. It adds 50 tokens to every session and 1,726 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 2026-08-31.
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