nature-academic-search
Multi-source literature search, citation verification, strict independent other-citation audits, article-level citation metric tables, influential citer profiling with citation-context extraction, MeSH search strategy, citation file management (.nbib/.ris/.bib conversion), and reference management (
By yuan1z0825 · 10,509 installs
npx skills add yuan1z0825/nature-skills --skill nature-academic-search
Source repository · Upstream listing
Academic Search — Router
Routing protocol
For local citation file conversion with complete supplied records, load
references/workflows/wf4 citation file mgmt.md and its format reference directly.
Source lookup, API setup, and network preflight apply only when retrieval or verification is
needed; do not require them for a requested offline conversion.
For a new task, load the core and matching resources below. Reuse already loaded guidance on follow ups; load more only when the task needs it.
1. Load the manifest and the core layer
Read [manifest.yaml](manifest.yaml). It declares the workflow axis, the allowed values, and the file paths each value maps to.
Also read every file listed under always load :
static/core/tools.md — the MCP tool inventory (core search, extended search, PubMed utilities) and the shared module map.
static/core/routing and ops.md — the T1→T2→T3 source routing quick guide, environment setup, error handling, and limitations.
2. Detect the workflow
Map the user's need to one or more workflow values:
multi source search — find literature across sources.
citation verification — verify citations extracted from a document.
mesh strategy — build a MeSH/PubMed search strategy.
citation file mgmt — convert/manage .nbib / .ris / .bib files.
reference mgmt — BibTeX, related article discovery, ID conversion.
strict other citation impact audit — determine strict independent other citations, build article level citation metric tables, identify high profile citers (academy members, presidents/deans, talent award holders, fellows, field leaders), and extract how they cited the target paper.
A combined request (for example search then export) may need more than one. State the detected workflow(s) in one short line before proceeding.
3. Load the matching workflow fragment(s)
Read the file mapped for each detected workflow (under references/workflows/ ). Do not read every workflow. Each workflow file links to the shared modules it needs.
4. Run the workflow using the loaded material
Apply the loaded material in this order:
1. Core tools and routing ( core/tools.md , core/routing and ops.md ) — which MCP tool for which need, and the T1→T2→T3 fallback chain for source retrieval.
2. The workflow fragment — its specific steps.
3. Shared modules and scripts on demand (dedup, citation parser, search strategy, RIS/BibTeX format, format converter).
Report specific tool failures and continue with remaining tools; broaden terms when there are no results; fall back to manual generation from MCP fetched metadata if a script fails twice.
5. Reach for references only when needed
The files under references/ (and scripts/ ) are deep references, not defaults. Open them on demand per the references.on demand table in the manifest — for example references/source tiers.md for the full reliability classification, references/dedup engine.md / references/citation parser.md / references/search strategy.md / references/ris bibtex format.md for the shared modules, and scripts/academic search.py (no MCP fallback discovery search) / scripts/format converter.py / scripts/preflight.py for the tooling.