| name | remote-sensing-nature-academic-search |
| description | Remote-sensing literature search, citation verification, sensor/platform/dataset query strategy, citation file management (.ris/.bib/.enw conversion), and reference management (BibTeX, related articles, DOI/arXiv lookup) across CrossRef, arXiv, Scopus, ScienceDirect, Semantic Scholar, and domain web sources. Use when the user needs coordinated multi-step literature workflows for remote sensing, Earth observation, geospatial AI, GIScience, photogrammetry, SAR, hyperspectral imaging, LiDAR, satellite missions, benchmark datasets, land-cover mapping, change detection, object detection, segmentation, retrieval, or multimodal remote-sensing foundation models. Also trigger on general literature-search needs during academic writing even without the word "Nature", such as searching for papers/literature, doing a literature review, verifying a citation, converting citation files, and Chinese phrasings like 文献检索、查文献、找文献、 文献综述检索、查论文、引文核对、参考文献管理、文献去重. |
| 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 tool/source inventory for remote-sensing search 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.remote-sensing-query-strategy — build a sensor/platform/dataset/task search strategy.citation-file-mgmt — convert/manage .ris/.bib/.enw files.reference-mgmt — BibTeX, related-article discovery, DOI/arXiv lookup.
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, preflight checks).
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/preflight.py for endpoint checks.
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 (
remote-sensing-nature-writing, remote-sensing-nature-polishing, remote-sensing-nature-reader, remote-sensing-nature-paper2ppt, remote-sensing-nature-figure, remote-sensing-nature-citation, remote-sensing-nature-response, remote-sensing-nature-data).
