nature-academic-search
- Repo stars 16,057
- Author updated Live
- Author repo nature-skills
- Domain
- Other
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @Yuan1z0825 · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: nature-academic-search
description: >- This skill is split into two layers: Do not try to apply the search logic from memory or from…
category: other
runtime: no special runtime
---
# nature-academic-search output preview
## PART A: Task fit
- Use case: >- This skill is split into two layers: Do not try to apply the search logic from memory or from this router. Always load fragments from disk as described below. Follow these five steps every time the skill is invoked. runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Routing protocol / 1. Load the manifest and the core layer / 2. Detect the workflow” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “>- This skill is split into two layers: Do not try to apply the search logic from memory or from this router. Always load fragments from disk as described below. Follow these five steps every time the skill is invoked. runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “Routing protocol / 1. Load the manifest and the core layer / 2. Detect the workflow” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “Routing protocol / 1. Load the manifest and the core layer / 2. Detect the workflow”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: nature-academic-search
description: >- This skill is split into two layers: Do not try to apply the search logic from memory or from…
category: other
source: Yuan1z0825/nature-skills
---
# nature-academic-search
## When to use
- >- This skill is split into two layers: Do not try to apply the search logic from memory or from this router. Always l…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Routing protocol / 1. Load the manifest and the core layer / 2. Detect the workflow” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "nature-academic-search" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Routing protocol / 1. Load the manifest and the core layer / 2. Detect the workflow
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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.
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/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).
Decide Fit First
Design Intent
How To Use It
Boundaries And Review