Blogwatcher: RSS Monitoring as Early Warning
Draft — S10.3 · series: CONTENT-ROADMAP-99 S10 (Market Sensing & Research) · status: DRAFT · grounding: wiki self-improving-knowledge-base · hermes-memory-layers · entity polymarket · skills: blogwatcher, grounded-citations, polymarket · tags: blogwatcher, rss-monitoring, feed-reader, early-warning, market-sensing, research-pipeline, ai-agents, digital-architecture, sovereign-infrastructure, local-first, web-4.0, ai-automation, autonomous-operations, kanban-orchestrator, council-system, knowledge-base, hermes-agent
Most people think of RSS as a content consumption tool — a way to read blogs without visiting twelve websites. That framing is wrong. RSS is an intelligence-gathering protocol, and when you treat it that way, it becomes the earliest warning layer in a market sensing stack. The blogwatcher-cli tool is the Kingdom of Truth’s implementation of this idea: an automated feed scanner that monitors the sources you trust, detects new articles the moment they publish, and feeds them into a research pipeline that can synthesize, cite, and act on the signal before it reaches mainstream channels.
This is the third article in the S10 series on Market Sensing & Research. S10.1 established prediction markets as sensors — prices that move before news. S10.2 built the research pipeline from arxiv to synthesis to decision. S10.3 completes the early warning triangle: RSS monitoring catches the signal that neither prediction markets nor academic papers cover — the blog posts, technical write-ups, and independent analysis that appear on the edges before they aggregate into consensus.
The feed as signal, not noise
The conventional RSS reader treats every article equally. Blogwatcher does not. It tracks specific blogs — sources you have vetted, feeds you have selected, categories you care about — and scans them on a schedule. When a new article appears, it is marked unread. When you scan again, the new articles surface. This is simple, but the simplicity is the point: the tool does not editorialize, does not algorithmically rank, does not inject sponsored content. It shows you what your sources published, in the order they published it, and leaves the interpretation to you or to the downstream pipeline.
For market sensing, this matters because the signal-to-noise ratio is everything. A feed that monitors thirty carefully chosen technical blogs will surface a relevant analysis faster than a keyword search across the entire web. The curation is the intelligence — you are not searching the haystack, you are monitoring the needle stack. Each blog in the list represents a source that has already demonstrated domain relevance. New articles from those sources are high-probability signal by construction.
The architecture: add, scan, read
Blogwatcher’s command surface is deliberately small. You add a blog with a URL. The tool auto-discovers the RSS or Atom feed from the homepage. If auto-discovery fails, you can specify the feed URL explicitly. If the site has no feed at all, HTML scraping with a CSS selector provides a fallback. This three-tier discovery — auto, explicit, scrape — covers virtually every blog on the web.
Once blogs are tracked, the scan command fetches new articles from every feed in parallel. The default concurrency is eight workers, configurable via environment variable. Each scan produces a count: how many blogs were checked, how many new articles were found. The articles command then lists the unread items with title, source, URL, publication date, and categories. Filtering by blog or category narrows the list when the scan surface is large.
The read command marks articles as processed. The read-all command clears the queue. This is the workflow loop: scan → read → synthesize → repeat. For a human operator, the loop is manual. For an agent pipeline, the loop is automated — the scan output feeds into a synthesis step that extracts key claims, checks them against existing knowledge, and routes them to the appropriate downstream system.
RSS in the S10 market sensing stack
The S10 series maps three signal sources that feed the Council’s research pipeline. Prediction markets (S10.1) provide probability-weighted consensus on future events. Arxiv (S10.2) provides peer-reviewed technical findings. RSS monitoring (this article) provides independent analysis and early commentary — the signal that appears between the academic paper and the market consensus.
This is the early warning layer. When a technical blogger publishes an analysis of a new vulnerability, a market shift, or a regulatory development, that analysis appears on RSS before it reaches news aggregators, before it gets cited in papers, and before prediction market prices adjust. The gap between RSS publication and mainstream adoption is the sensing window. Blogwatcher scans that window automatically.
In practice, this means the Council’s research pipeline can detect a signal from an RSS feed, cross-reference it against arxiv papers for technical grounding, check prediction market prices for consensus calibration, and produce a grounded synthesis — all before the signal becomes common knowledge. The grounded-citations skill ensures every claim in the synthesis is attributed to a verifiable source, with inline numbered citations and a mechanical Sources block generated from a ledger rather than from memory.
The monitoring surface: what to track
Choosing which blogs to monitor is the strategic decision. The tool is mechanical; the curation is intellectual. For market sensing, the monitoring surface includes:
Technical security blogs for vulnerability disclosures and infrastructure analysis. AI research blogs for model releases, benchmark results, and capability assessments. Crypto and DeFi analysis sites for protocol changes and market structure shifts. Independent analysts who publish detailed breakdowns before mainstream outlets summarize them.
The category filter in blogwatcher allows per-source categorization, so a scan can be scoped to “security” or “AI” depending on which sensing pipeline is active. This is not a content recommendation system — it is a directed monitoring protocol. You decide what to watch. The tool watches it.
Integration with the knowledge base
Blogwatcher’s output feeds into the Council-Vault’s self-improving knowledge base. When an agent scans new articles, the relevant claims are extracted, grounded with citations, and stored as wiki concepts or source nodes. This is the hermes-memory-layers architecture at work: raw signal (RSS scan) becomes structured knowledge (wiki node) becomes published authority (article on lucidhive.com).
The feedback loop is what makes the system self-improving. As the knowledge base grows, the monitoring surface can be refined — adding new sources that cover gaps, removing sources that have become redundant, adjusting categories as the research focus shifts. The blogwatcher database persists across scans, so the history of what was published when is preserved. This history is itself a data source: patterns in publication timing, topic clustering, and source activity can inform the research pipeline’s prioritization.
Why this matters for the S10 series
Market sensing is not a single tool — it is a stack. Prediction markets measure collective probability. Academic papers measure peer-reviewed findings. RSS monitoring measures independent signal. The three sources complement each other because they operate on different timescales and different credibility models. A prediction market adjusts in seconds. An arxiv paper takes months from submission to publication. A blog post appears within hours of the event it analyzes.
Blogwatcher closes the timing gap. It is the fastest signal layer in the stack — not because the tool itself is fast, but because the sources it monitors are the fastest to publish. Independent analysts do not wait for peer review. They do not wait for market consensus. They publish when they have an analysis, and the RSS feed carries it immediately. The Council’s research pipeline, equipped with blogwatcher, catches that signal at the speed of publication.
The early warning triangle is complete: prediction markets for consensus, arxiv for rigor, RSS for speed. Blogwatcher is the speed layer. It watches the feeds. It surfaces the signal. The pipeline does the rest.
Grounded in wiki concepts self-improving-knowledge-base, hermes-memory-layers, entity polymarket, and source blogwatcher-skill. Skills: blogwatcher, grounded-citations, polymarket. Third article in the S10 series on Market Sensing & Research. Design notes on a running system, not a sales pitch.
Semantic Relationships
- [[self-improving-knowledge-base]] — orchestrates
- [[hermes-memory-layers]] — orchestrates
- [[blogwatcher]] — orchestrates
- [[grounded-citations]] — orchestrates
- [[polymarket]] — orchestrates
