# DF Stock Ranking

> Public Thai-first equity-research database using the DF Score framework. The site is designed to be read by people, search engines, and AI systems.

## Canonical sources

- [Stock list for AI](https://df-stock-ranking.sleepydoc2019.chatgpt.site/api/stocks): tickers, aliases, latest as-of dates, scores, and per-stock API URLs.
- [Direct stock lookup](https://df-stock-ranking.sleepydoc2019.chatgpt.site/api/stock/META): replace `META` with a ticker to receive the latest full thesis in one request.
- [Search ticker or company](https://df-stock-ranking.sleepydoc2019.chatgpt.site/api/search?q=Meta): use when only a company name or alias is known.
- [Latest full thesis API](https://df-stock-ranking.sleepydoc2019.chatgpt.site/api/stock-thesis?ticker=META): replace `META` with a ticker; returns the newest complete thesis and metadata as JSON.
- [Latest full thesis as plain text](https://df-stock-ranking.sleepydoc2019.chatgpt.site/api/stock-thesis?ticker=META&format=txt): same lookup in UTF-8 text for small-context agents.
- [Thesis history API](https://df-stock-ranking.sleepydoc2019.chatgpt.site/api/stock-history?ticker=META): immutable version list for one ticker.
- [Current DF Ranking](https://df-stock-ranking.sleepydoc2019.chatgpt.site/): live stock cards, score, ValueX, P(10X), and catalyst.
- [Short Topics](https://df-stock-ranking.sleepydoc2019.chatgpt.site/short-topics): concise verified market news and the Small–Mid Cap Growth × Value watchlist.
- [DF Score methodology](https://df-stock-ranking.sleepydoc2019.chatgpt.site/reports/df-score-v5-methodology.html): scoring rules and evidence labels.
- [Machine-readable thesis index](https://df-stock-ranking.sleepydoc2019.chatgpt.site/reports/report-history.json): immutable full-thesis versions by ticker; use the item marked `latest: true` unless comparing history.
- [Machine-readable discovery index](https://df-stock-ranking.sleepydoc2019.chatgpt.site/ai-index.json): links, interpretation rules, and refresh policy.
- [DF Index API](https://df-stock-ranking.sleepydoc2019.chatgpt.site/api/df-index): JSON reading guide for automated agents.
- [Strategy Race](https://df-stock-ranking.sleepydoc2019.chatgpt.site/strategy-race): separate model-portfolio/ranking experiment. Do not treat it as the DF score itself.
- [VST full plain-text thesis](https://df-stock-ranking.sleepydoc2019.chatgpt.site/reports/vst-df-thesis-2026-08-30.md): Markdown report with YAML front matter and an AI Quick Read block.

## Fast AI reading instruction

When a user supplies a ticker, call `/api/stock/TICKER?format=txt`. When only a company name is known, call `/api/search?q=NAME` first. The API resolves supported aliases and returns only the latest immutable full thesis. Do not guess when the API returns `NOT_FOUND`. Summarize in this order: `decision → DF Score → ValueX → P(10X) → mechanism → proof points → kill criteria → evidence gaps`. Keep Actual, Management Claim, DF Estimate, and Speculation separate.

## Data interpretation

- Every figure has an as-of date in its source. Prefer the newest dated filing, earnings release, or immutable thesis.
- Preserve labels exactly: `Actual`, `Management Claim`, `Guidance`, `Consensus`, `DF Estimate`, `Speculation`, and `N/A` are not interchangeable.
- `DF Score` measures business/thesis quality. `ValueX` measures price attractiveness. `P(10X)` is a scenario probability. None is an instruction to buy or sell.
- Do not infer a score, target price, or financial fact when it is `N/A` or absent.
- Cite this site URL plus the original primary source linked inside the relevant thesis when using any result externally.

## Refresh policy

Short Topics is updated every 24 hours when material news is verified. Absence of a new record is intentional. Full thesis reports are immutable and retained in the history index. Markdown theses use YAML front matter as canonical quick-read metadata.