nature-academic-search
>-
pinned to #74a3227updated 2 weeks ago
Ask your AI client: “install skills/nature-academic-search”.
Requires the metahub MCP server installed in your client. Set up MCP.
mh install skills/nature-academic-searchmetahub onboarded this repo on the author's behalf.
If you own github.com/Yuan1z0825/nature-skills on GitHub, claim the listing to take over publishing. Your claim preserves the existing eval history and badges; only the curator label is replaced with verified-publisher on your next publish.
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27,825
Last commit
2 weeks ago
Latest release
published
- #codex-skills
- #nature
- #nature-skills
About this skill
Pulled from SKILL.md at publish time.
This skill is split into two layers:
Evaluation report
WarningsAutomated checks the publisher passed at publish time — structure, docs, safety, and whether the artifact behaves as claimed.74a3227· 2 weeks ago
Documentation
41Description qualitywarn
15 words · 25 chars — manifest description is empty; graded the GitHub repo description instead
A skill's manifest description doubles as its trigger — add one to SKILL.md (15+ words, e.g. “use this skill when …”).
README is present and substantial
14,082 chars · 15 sections · 21 code blocks
Tags / topics declared
3 total — codex-skills, nature, nature-skills
README has usage / example sections
no labeled section but 21 code blocks document usage
Homepage / docs URL declared
no homepage declared (registry will use the repo URL) — info-only, not blocking
Release history
1- releasecurrent74a3227warn2 weeks ago
Contents
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/.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).
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Related
Verification Before Completion
Evidence before assertions, always
Writing Plans
Turn specs into phased implementation plans
Test-Driven Development
Red → green → refactor discipline for any feature or bugfix
mh install skills/nature-academic-search