Perfect Wiki is a knowledge management and documentation tool designed for organizations using Microsoft Teams. It enables teams to create, organize, search, and share internal knowledge bases, FAQs, SOPs, and more, with robust permissions and collaboration features. Perfect Wiki supports unlimited knowledge bases, advanced search, AI-powered chat and summarization, and custom branding, all seamlessly integrated into the Microsoft Teams environment.
Most "LLM wikis" use agents, embeddings, and repeated model calls to organize local notes. I built a deterministic alternative: a pure Python compiler that turns messy markdown into a linked, linted wiki using only the standard library. Along the way, I fixed two real bugs, benchmarked the pipeline on two operating systems, and showed why a compiler is often a better fit than an agent for mechanical text organization.
BioWikiNet is a multilingual dataset describing biodiversity representation across 11 Wikipedia language editions selected for their global reach and relevance to biodiversity-rich regions. The dataset includes 1,266,215 taxonomic articles linked to 751,843 unique taxa from the GBIF Backbone Taxonomy, derived from January 2025 Wikipedia dumps and mapped via Wikidata identifiers. Each record contains article-level metadata (pageviews, edits, editors, creation dates, content metrics) combined with GBIF taxonomic classifications. The dataset provides 6,955,289 taxonomic hyperlinks connecting articles within and across language editions, along with three network-based indices—Species Connectivity Index, Core Index, and Excess Focus Index—that quantify the structural characteristics of taxonomic linkages. BioWikiNet enables transparent, reproducible analyses of biodiversity representation and editorial coverage across linguistic communities, serving as an open resource for biodiversity informatics, conservation culturomics, and multilingual knowledge equity research.
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