how to use autoreason for on-page SEO / GEO
you have a blog post sitting at position 6 for a 2,400/mo keyword, 1.4% CTR, pulling 180 visits a month that converts at 0.8%. you want all three numbers to improve without rewriting the page from scratch. most marketers would prompt an LLM with "rewrite this for SEO" and publish whatever comes back.
the problem with asking AI to rewrite its own work is it never says "this is already good." it invents missing sections, drifts from the original angle with every pass, and strips out the lines that were ranking.
autoreason fixes that with adversarial isolation. every role in the loop is a fresh agent that cant see what the others wrote, so the output doesnt collapse into the same generic advice showing up in the 10 posts already outranking you.
> incumbent is your current page, the hero, the subhead, the H2 structure, the section order
> strawman is a fresh agent that sees only the page + target keyword + top 3 SERP competitors + what your ICP asked about in sales calls, it writes critiques like "H2 on line 142 is a restatement not an entity, the example in section 3 doesnt match the ICP vocabulary from the transcripts." no rewriting, just finding problems
> author B is a fresh agent that sees the task + the original + the critique and writes a revised version
> synthesizer is a fresh agent that sees original + B in random order and merges the strongest parts of both
> judge panel of 3 fresh agents does a blind ranked-choice vote on A, B, and AB using Borda count, convergence at streak=2 so it doesnt loop forever
for on-page work the knowledge layer is what keeps this grounded in your business instead of generic SEO advice:
> Google Search Console so the agent knows which queries youre getting impressions on but losing CTR, which keywords youre ranking for without optimizing for, and which pages are declining month over month
> Ahrefs or Moz data on the top 3 ranking competitors, their internal link patterns, the anchor text they use, the entities they cover that you dont
> GA4 conversion data so the judges can score variants on "would the ICP reading this still convert" not just "does it look better"
> sales call transcripts and support tickets so the agent writes in the language your customers use, not the language your marketing team assumes they use
> your own top-performing pages so the synthesizer can merge in patterns that work for your domain instead of copying whatever is on the SERP right now
this works the same way for service pages, free tool pages, and programmatic SEO templates:
> service pages: loop the "we do X for Y" page, judges score on "would a prospect forward this internally" using won-deal language from your CRM as ground truth
> free tool pages (the ones youre vibe coding with Claude): loop the landing copy around the tool, judges score against the queries driving impressions in GSC and how competing tool pages structure above the fold
> programmatic SEO templates: loop the template, not each page, judges score a sample of 20 filled pages for entity coverage, uniqueness, and conversion fit. fix the template once, 10,000 pages improve
> AI overviews and LLM citations (GEO): judges are actual LLMs prompted with the target query, checking whether your page gets cited. if it doesnt, the critic flags buried claims and weak entity definitions and the loop rewrites until it does
you still push the winner live and watch it in Search Console for 14 days before calling it. autoreason just narrows the search space so you´re shipping strong candidates instead of whatever ChatGPT cleaned up this morning.
results feed back every run so the next one is sharper
these 5 GitHub repos replaced my $2,400/month trading setup
you're spending thousands on software anyone can fork
the repos behind those tools are sitting on GitHub for free
here's what i actually run:
1. fredapi (1K ★)
Bloomberg charges $2,000/mo for macro data
this pulls every Fed dataset into Python with one API key
GDP, CPI, rates, employment - pair it with Claude and you're set
https://t.co/Hy9AVDePVo
///
2. ccxt (42K ★)
i was paying $50/mo per exchange just for API access
ccxt connects 107 exchanges through one interface
JS; Python; PHP; Go; C#
the industry standard since day one
https://t.co/BTkIEnV0zN
///
3. freqtrade (47K ★)
killed my $200/mo bot subscription in one afternoon
backtesting, hyperopt, FreqAI, live on 20+ exchanges
7 years of weekly commits. Telegram control. your strategies stay yours
https://t.co/RcSK7fykR5
///
4. OpenBB (40K ★)
equities, options, crypto, fixed income, macro - one terminal
plugs into Python, Excel, REST API, MCP for AI agents
my $500/mo data feed couldn't do half of this
https://t.co/NRCD6IHm52
///
5. goose (40K ★)
by Block (Jack Dorsey). Rust. Apache 2.0
full AI coding agent. any LLM. 3,000+ MCP tools. runs locally
the $200/mo i was spending on Claude Code now costs me $0
https://t.co/on8T7xhZ2A
///
bookmark this and thank me later
MOST PEOPLE DON'T KNOW THIS
There are Python libraries giving free market data for 170,000+ tickers.
Stocks.
Crypto.
Forex.
Economic indicators.
No Bloomberg. No expensive APIs.
Here are 12 libraries every quant dev should bookmark👇
i cancelled $2,000/month in trading subscriptions
replaced every single one with open-source repos
here's the full stack:
1. TradingView Pro ($30/mo) → lightweight-charts
14K stars. by TradingView themselves. 45KB. free
https://t.co/Zj8BoF0kbj
2. Bloomberg Terminal ($2,000/mo) → fredapi + Claude
every macro dataset the Fed publishes. free API
https://t.co/QOsmACH9tB
3. backtest platform ($100/mo) → prediction-market-backtesting
NautilusTrader fork with Polymarket + Kalshi adapters
https://t.co/ezKB2PSBUq
4. real-time dashboard → polyrec
terminal UI: Chainlink oracle, Binance feed, orderbook depth
70+ indicators. auto CSV logging. strategy backtester
https://t.co/fYj5aFUTS4
5. bot framework (7 strategies) → Polymarket-Trading-Bot
53K lines TypeScript. arbitrage, momentum, market making,
AI forecast, whale copy-trade, convergence
https://t.co/xNSLjlIEZd
6. strategy reverse engineering → polybot
execution + market data infrastructure. paper trading
Kafka, ClickHouse, Grafana. full analytics pipeline
https://t.co/s3fjSwXV6z
7. paper trading for AI agents → polymarket-paper-trader
real order books. exact fee model. slippage tracking
your Claude agent gets $10K paper money and trades
https://t.co/oXMxD9uhKI
8. token savings → rtk
CLI proxy. cuts Claude Code tokens by 60-90%
Rust. single binary. 10 AI tools supported
https://t.co/WKnP7dfvuj
9. Claude Code itself ($200/mo) → goose
35K stars. by Block (Jack Dorsey). Rust
works with any LLM. full agent loop. free
https://t.co/md2P9CJ4Ia
10. wallet tracking + copy trading → Kreo
track top Polymarket wallets. auto copy trades
the only tool on this list i actually pay for
because it makes more than it costs
https://t.co/rVKQ107tBV
total before: ~$2,600/month
total now: $0 + Kreo
bookmark this. you'll need it
@cbclone@phamduydong179 Não dài phát biểu có thể khôn hơn đc ko. Tích cực là ntn? Cứ phải ca ngơi sự sáng suốt của đảng??? Trái chiều là tiêu cực? Góp ý, đòi hỏi quyền lợi xứng đáng cũng ko đc? Tư duy nô lệ nó ăn sâu vào mái rồi.
@Tranconglan75@admvhv Bản chất con người là vậy, khác ở chỗ nó có cơ chế kiểm soát và theo dõi. Đông lào mọi chuyển cứ để đảng cs lo, y kiến là ăn phản động, 3/ liền
@tigerTrantddl @TrungDaoQuan Nó tính thuế dựa trên lợi nhuận hoặc khoán tuỳ vào người kinh doanh muốn lựa chọn nào lợi cho họ. Ko biết thì nên im lặng đừng tỏ vẻ nguy hiểm.