Results for “scientific-discovery”

Use to build Science's data, code, and materials availability — mandatory deposition in approved repositories, accession numbers, a compliant data-availability statement, and materials/reagent sharing.

Evaluate scientific claims and evidence quality by assessing experimental design, identifying biases and confounders, and applying evidence grading frameworks like GRADE and Cochrane Risk of Bias.

Challenge system assumptions against accumulated evidence. Triages observations and tensions, detects patterns, generates proposals. The scientific method applied to knowledge systems. Triggers on "/rethink", "review observations", "challenge assumptions", "what have I learned".

Use before starting any new work to check for existing knowledge. This skill provides a systematic search and retrieval process for finding relevant knowledge from memory systems (PARA, Gigabrain, OpenStinger, existing skills) before starting work, preventing redundant effort and leveraging prior learning.

Open Science Release Packager

Debugging is the scientific method under time pressure.

Retrieve deterministic search results, metadata, and full-document Markdown from arXiv, PubMed/PMC, and US policy corpora with daily freshness checks.

Create publication-ready scientific figures with multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and journal-specific formatting using matplotlib, seaborn, and plotly.

基于 anchor 论文、topic 关键词或当前 wiki 状态，产出一份排好序的候选论文 shortlist，供用户或上游 skill 决定是否进一步 `/ingest`。当用户问 "接下来该读什么"、"找和这篇相似的论文"、"推荐相关工作"、"这个方向周围有什么" 时触发；`/ingest --discover` 也会内部调用本 skill。本身不 ingest，只提出候选。

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques