视觉画布设计
canvas-design
基于设计原则创作静态视觉作品,用于海报与品牌图形。
research-paper-data【文档与办公】Search scholarly literature and research data through discoverable providers, including public metadata APIs, optional user-configured sources, legal open-access full-text discovery, identifier resolution, and citation/reference triage. Use when the user asks for paper search, topic or author literature discovery, DOI/arXiv/PMID/PMCID lookup, dataset…
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this skill to search scholarly metadata, resolve persistent identifiers, and find legal open-access full text using providers that are visible in the current runtime. Prefer capability discovery and provenance over assuming a specific service, credential, or edition.
When OPENCODE_CONFIG_DIR is set, first look for
$OPENCODE_CONFIG_DIR/research-capabilities.json. Treat that file as the
edition's provider declaration. If it is missing, continue with public defaults
listed below.
Read references/public-apis.md when making direct API requests or debugging a
source-specific response. Use scripts/academic_search.py for broad topic,
author, affiliation, ORCID, or OpenAlex/Crossref discovery when Python is
available.
Provider declarations use:
public: no user secret required.user-configured: requires a visible user-provided setting, usually an
environment variable.managed: an edition-provided provider; use only when its declared base URL
and auth requirements are visible in the current runtime.Default public sources:
scripts/academic_search.py for broad topic,
author, affiliation, ORCID, and citation-aware search. Treat OpenAlex results
as discovery candidates; resolve selected DOI/arXiv/PMID records through an
authoritative source before claiming final metadata or OA availability.Optional user-configured sources:
UNPAYWALL_EMAIL is visible.OPENALEX_API_KEY for a higher OpenAlex request budget; the
search script supports it for work, author, and ORCID lookups. Basic anonymous
queries remain available within the source's current limits.--mailto to
scripts/academic_search.py or use OPENALEX_MAILTO, CROSSREF_MAILTO, or
RESEARCH_CONTACT_EMAIL when visible.research-capabilities.json and their required configuration is visible.Use legal open-access/source-discovery paths only. Do not use paywall bypass, credential sharing, scraped account credentials, or undeclared hidden secrets.
research-capabilities.json when present.user-configured or managed provider.scripts/academic_search.py first for
ranked discovery when Python is available; then resolve selected
identifiers through Crossref, arXiv, Europe PMC, or DataCite.--author, --affiliation,
--orcid, --author-id, or --list-authors; report ambiguity instead
of guessing.python scripts/academic_search.py "<query>" --limit 5 --compact for
broad discovery smoke tests and quick triage. Use JSON output for downstream
parsing.id, published, updated, authors, categories, and PDF link.For searches, provide:
Best matches: short ranked list with title, year, authors, venue, DOI or
other identifier, and source.Full text: legal PDF/full-text candidates or a clear not-found statement.Coverage notes: skipped optional sources, ambiguity, rate limits, or source
failures.Next step: one focused recommendation, such as resolving one DOI, searching
arXiv variants, or downloading an OA PDF with user approval.For identifier resolution, provide one record when confident, or a small candidate set when not confident. Never fabricate abstracts, citations, PDFs, or author names when the source does not provide them.