
Academic Search
FreeStreamline multi-source literature searches and citation management.
Free · Opens the source repo
What Academic Search does
The Academic Search skill is designed to facilitate comprehensive literature searches across multiple academic databases, enabling users to efficiently gather and manage research materials. This skill supports a variety of workflows, including multi-source searches, citation verification, and reference management, making it a valuable tool for researchers, students, and academics. It integrates with several prominent databases such as PubMed, CrossRef, arXiv, Scopus, ScienceDirect, and others, allowing users to access a wide range of scholarly articles and publications.
The skill operates through a structured routing protocol that guides users through the process of selecting the appropriate workflow for their needs. Each workflow is tailored to specific tasks, such as building a MeSH search strategy or managing citation files in various formats like .nbib, .ris, and .bib. By breaking down complex tasks into manageable workflows, users can effectively navigate the often overwhelming landscape of academic literature.
In addition to search capabilities, the Academic Search skill offers features for citation verification and impact audits, helping users to assess the influence of their work and track citations from notable academics. The skill also includes tools for deduplication and citation parsing, ensuring that users can maintain accurate and organized reference lists. This makes it particularly useful for those engaged in systematic reviews or meta-analyses where citation accuracy is critical.
Overall, the Academic Search skill is ideal for anyone involved in academic research who needs a systematic approach to literature retrieval and citation management. Its integration with multiple databases and structured workflows make it a powerful addition to any research toolkit.
When to use it
Use this skill when you need to perform extensive literature reviews or manage citations from various academic sources efficiently.
When not to use it
This skill may not be suitable for casual users or those who only require a single-source search, as its capabilities are optimized for more complex academic workflows.
What you can build with it
Conducting a Systematic Review
Use the multi-source search workflow to gather literature from various databases for a comprehensive systematic review.
Verifying Citations for a Manuscript
Utilize the citation verification workflow to ensure all citations in your manuscript are accurate and properly formatted.
Managing References for a Thesis
Employ the reference management features to organize and convert citation files for your thesis, streamlining your writing process.
How to install Academic Search
View source1. Install with the skills CLI
npx skills add yuan1z0825/nature-skills/nature-academic-search --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by yuan1z0825Academic 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/.bibfiles.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:
- 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. - The workflow fragment — its specific steps.
- 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.
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 six 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).
Frequently asked questions about Academic Search
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