The 0.1.x line under this slug will continue to function but will not receive further updates.
SciVerse academic paper retrieval: structured metadata search, semantic chunk retrieval for RAG, and byte-range content reading. For agent workflows that need citation-grade scientific literature.
When to use
Trigger this skill when the user's request involves any of:
Locating academic papers by structured criteria (authors, year, journal, subjects)
Grounding answers in paper excerpts (RAG / citations)
Expanding the original text around a known doc_id (more bytes before/after a chunk)
Authentication
This skill requires the SCIVERSE_API_TOKEN environment variable
(obtain from https://sciverse.space). Optionally set SCIVERSE_BASE_URL
to override the default API base URL.
Tools
search_papers
Search academic papers by structured filters (title, authors, journal,
year, subjects, etc.).
Use when: "find Hinton's papers from 2020-2023", "Nature papers on
CRISPR".
Not for: natural-language Q&A retrieval (use semantic_search) or
full-text snippets (use read_content).
Returns: list of papers; each entry has doc_id, title, author, abstract,
publication_venue_name, publication_published_year.
Natural-language semantic search returning relevant paper chunks for
RAG-style answering.
Use when: "How does Transformer attention work?", "What are recent
methods for protein structure prediction?".
Not for: precise field filtering (use search_papers) or fetching full
original text (use read_content).
Returns: list of chunks; each entry has chunk_id, doc_id, abstract,
chunk, score, title, offset.
Typical chain: semantic_search → pick chunk → read_content(doc_id,
offset).
Read a UTF-8 byte range of a paper's original text. Typically used with
a doc_id/offset returned by semantic_search to expand context (read
more bytes before or after a chunk).
Returns: text fragment, bytes_returned, next_offset, more (boolean).
