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nature-academic-search

★ 22K repomlN/AIntermediateClaude MCP
🤖 AI Summary

This skill implements a two-layer academic search agent that loads a manifest and static routing rules from disk, then dynamically selects and executes the correct workflow based on user intent. It strictly reads all logic from versioned files rather than relying on memory or hardcoded search behavior.

How to Install

Claude Code:
git clone --depth 1 https://github.com/Yuan1z0825/nature-skills.git && cp nature-skills/skills/nature-academic-search ~/.claude/skills/nature-academic-search -r
# 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](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/academic_

Details

Category AI/ML → ml
SourceYuan1z0825/nature-skills
SKILL.mdView on GitHub →
Repo Stars★ 22.6K
Est. per SkillN/A (shared across 13 skills from this repo)
DifficultyIntermediate
Risk LevelN/A

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