nature-academic-search

name	nature-academic-search
description	Multi-source literature search, citation verification, MeSH search strategy, citation file management (.nbib/.ris/.bib conversion), and reference management (BibTeX, related articles, ID conversion) via MCP tools (PubMed, CrossRef, arXiv, Scopus, ScienceDirect). Use when the user needs coordinated multi-step literature workflows beyond a single MCP call.
version	2.0.0
author	Community contribution, refactored into static/dynamic layers

Academic Search — Router

This skill is split into two layers:

• A static layer under static/ that holds versioned, reusable content fragments (the MCP tool inventory and shared modules, and source routing plus operational rules).
• A dynamic layer (this file plus manifest.yaml) that detects which workflow the user needs and loads that workflow, reaching for shared modules and scripts only when a step needs them.

Do not try to apply the search logic from memory or from this router. Always load fragments from disk as described below.

Routing protocol

Follow these five steps every time the skill is invoked.

1. Load the manifest and the core layer

Read 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.

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 that is the standard execution order across all workflows.
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/format-converter.py / scripts/preflight.py for the tooling.

Why this split

• The static layer is versioned and reviewable; the workflow files and shared modules were already factored this way.
• The dynamic layer keeps each invocation cheap: only the workflow the user needs enters context, instead of all five plus every module.
• The router itself is short on purpose. Update fragments and references, not this file, when adding scope.
• This structure mirrors the other nature-* skills (nature-writing, nature-polishing, nature-reader, nature-paper2ppt, nature-figure, nature-citation, nature-response, nature-data).