Spaces:
Sleeping
Sleeping
| # README and demo research notes | |
| This note records the presentation research behind the `0.1.0a3` README and staged | |
| Hugging Face Space. It is not a benchmark claim and it does not change the taxonomy or | |
| runtime contract. | |
| ## Sources reviewed | |
| The review covered the GitHub monthly trending page and representative high-quality | |
| project READMEs with adjacent presentation problems: | |
| - [GitHub Trending, monthly](https://github.com/trending?since=monthly): current | |
| repository presentation patterns. | |
| - [Polars](https://github.com/pola-rs/polars): performance-oriented data tooling with | |
| a concise value proposition and evidence-linked benchmarks. | |
| - [DuckDB](https://github.com/duckdb/duckdb): immediate installation and runnable | |
| examples before deeper architecture. | |
| - [OpenBB](https://github.com/OpenBB-finance/OpenBB): finance-specific positioning, | |
| clear audience, product surfaces, and documentation paths. | |
| - [FinanceToolkit](https://github.com/JerBouma/FinanceToolkit): finance-oriented | |
| examples, scope, and discoverable feature groups. | |
| - [Hugging Face Docker Spaces](https://huggingface.co/docs/hub/spaces-sdks-docker) | |
| and the [coding-agent setup document](https://huggingface.co/new-space/agents.md): | |
| deployment metadata, Docker runtime expectations, and agent API discovery. | |
| The review was conducted on 2026-09-02. Trending content changes over time; the goal | |
| was to extract durable communication patterns rather than copy rankings or wording. | |
| ## Patterns applied | |
| | observed pattern | application in Relevance | | |
| | --- | --- | | |
| | one-sentence value proposition | “Fast financial-news screening that shows its work.” | | |
| | show a useful result early | the README opens with real quickstart stdout | | |
| | put runnable code before exhaustive reference | a complete one-article example appears near the top | | |
| | explain performance mechanistically | Rust, automata, Rayon, sparse output, and Arrow are mapped to their practical effects | | |
| | separate product surfaces by user goal | the README distinguishes rich, compact, Arrow, and ranking paths | | |
| | link performance claims to evidence | claims are bounded to recorded research stages and environments | | |
| | state boundaries plainly | relevance is separated from sentiment, materiality, prediction, and advice | | |
| | make the demo self-explanatory | the Space has curated examples, evidence highlights, lineage, downloads, and named APIs | | |
| | keep deployment reproducible | the Space exporter creates a deterministic source bundle and SHA-256 manifest | | |
| | avoid decorative clutter | one Space-card emoji; no emoji-heavy package documentation | | |
| ## Marketing standard | |
| The README is intentionally specific rather than superlative. It explains why the | |
| system can be fast and traceable, but it does not claim to be the fastest system in all | |
| settings. It shows the output contract before implementation details and keeps | |
| limitations close to the value proposition. | |
| The intended audience is: | |
| - financial-data and news-ingestion engineers; | |
| - quantitative researchers building candidate-selection pipelines; | |
| - analysts who need literal evidence and provenance; | |
| - researchers comparing exact retrieval with model-based classifiers; and | |
| - teams that need a deterministic first-stage filter before more expensive NLP. | |
| ## Items intentionally omitted | |
| - unqualified “blazing fast” or “state of the art” language; | |
| - benchmark numbers without the host, stage, dataset, and repetition design; | |
| - claims that rule-based relevance is semantically complete; | |
| - claims that a relevant article predicts price direction; | |
| - a published package badge or live Space badge before either artifact exists. | |