This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Product upvotes vs the next 3
Waiting for data. Loading
Product comments vs the next 3
Waiting for data. Loading
Product upvote speed vs the next 3
Waiting for data. Loading
Product upvotes and comments
Waiting for data. Loading
Product vs the next 3
Loading
Agenda Intelligence MD
Turn AI summaries into intelligence briefs
Agenda Intelligence MD is different from generic summarization tools: it gives AI agents a structured markdown protocol for public agenda analysis. Instead of only saying “what happened,” agents classify signal vs noise, explain what changed, why it matters, who is affected, what remains uncertain, possible scenarios, and what to watch next. It also supports schema/CLI validation, making outputs more consistent, reviewable, and useful for research and monitoring workflows.
Hey Product Hunt 👋
I built Agenda Intelligence MD because I kept seeing the same problem in AI research agents: They can summarize public information, but they often stop too early. A summary tells you what happened. A useful intelligence brief should also tell you:
whether this is noise - a weak signal - a signal - a structural shift, or a trigger event -what changed - why it matters - who is affected - what remains uncertain - what scenarios are possible - what to watch next
Agenda Intelligence MD is an open-source PyPI package and markdown protocol that helps AI agents produce more structured public agenda analysis instead of generic summaries.
Install: ```bash pip install agenda-intelligence-md ``` It is built for AI agent developers, research workflows, policy/risk analysis, regulatory monitoring, sanctions tracking, geopolitical monitoring, and other cases where “summarize the news” is not enough.
This is an early open-source launch, so I’d really value feedback from the PH community: 1. Is the positioning clear?
2. Would this be useful in your agent or research workflow?
3. What fields are missing from the brief structure?
4. What examples should I add to the docs?
5. What would make this easier to adopt?
Thanks for checking it out — comments, critique, GitHub stars, issues, and real use cases are very welcome.
About Agenda Intelligence MD on Product Hunt
“Turn AI summaries into intelligence briefs”
Agenda Intelligence MD was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #141 on the daily leaderboard. Agenda Intelligence MD is different from generic summarization tools: it gives AI agents a structured markdown protocol for public agenda analysis. Instead of only saying “what happened,” agents classify signal vs noise, explain what changed, why it matters, who is affected, what remains uncertain, possible scenarios, and what to watch next. It also supports schema/CLI validation, making outputs more consistent, reviewable, and useful for research and monitoring workflows.
On the analytics side, Agenda Intelligence MD competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Agenda Intelligence MD performed against the three products that launched closest to it on the same day.
Who hunted Agenda Intelligence MD?
Agenda Intelligence MD was hunted by Vassiliy Lak. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Agenda Intelligence MD including community comment highlights and product details, visit the product overview.
Vassiliy Lak