Workflow·Research

Literature Search

Searches and discovers academic papers across multiple sources (Semantic Scholar, arXiv, Tavily, Exa, AMiner, Google Scholar) with…

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Install this skill Read the source first Free Written by jxtse · unverified publisher
Context cost
1.4k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 5.6 kBtext throughout, nothing executable
Licence
MITfree to use
Last change
no release on file
Servers it uses
Noneruns standalone

What it does

Searches and discovers academic papers across multiple sources (Semantic Scholar, arXiv, Tavily, Exa, Gemini deep research, AMiner, Google Scholar) with adaptive engine selection based on query type. Returns ranked, deduplicated results with metadata (authors, venue, year, citations, abstract, PDF link). Use when the user asks to find papers / literature / publications / preprints / references on a topic, search for related work, look up a specific paper by title or DOI or arXiv ID, find papers by an author, find recent SOTA / state-of-the-art work, survey a research area, or run a deep /…

Installed, it changes the agent in these ways.

What this skill changes about the agent is not written down here yet. The listing was collected from its source, and the description is in its own SKILL.md.

Workflow

Runs a procedure end to end.

literature-searchsemantic-scholararxivpapers
Filed under

Research

The skill itself

This is the whole product. A skill is instructions the model reads, so there is nothing behind the listing you cannot see first — the front matter loads with every session, and the body below it loads when the skill triggers.

SKILL.md5.6 kB · 137 lines
--- name: literature-search description: > Searches and discovers academic papers across multiple sources (Semantic Scholar, arXiv, Tavily, Exa, Gemini deep research, AMiner, Google Scholar) with adaptive engine selection based on query type. Returns ranked, deduplicated results with metadata (authors, venue, year, citations, abstract, PDF link). Use when the user asks to find papers / literature / publications / preprints / references on a topic, search for related work, look up a specific paper by title or DOI or arXiv ID, find papers by an author, find recent SOTA / state-of-the-art work, survey a research area, or run a deep / comprehensive literature search with synthesis. ---
14# Literature Search
15
16Systematic, multi-engine academic paper search.
17
18## When to Use
19
20- User asks "find papers about X"
21- User needs related work for a new project
22- User wants to know the state of the art on a topic
23- User asks for papers from a specific venue/author/year
24
25## Engine Selection
26
27Choose engines based on the search goal:
28
29| Goal | Primary Engine | Supplementary |
30|------|---------------|---------------|
31| **Broad topic survey** | Semantic Scholar | arXiv, Tavily |
32| **Latest preprints** | arXiv (sort by submittedDate) | Semantic Scholar |
33| **Deep research / complex questions** | Gemini deep research | Tavily + Exa |
34| **Specific paper by title** | Semantic Scholar | Google Scholar (via Tavily) |
35| **Papers by author** | Semantic Scholar (author search) | AMiner |
36| **Chinese research community** | AMiner | Semantic Scholar |
37| **Industry/applied papers** | Tavily (deep) | Exa semantic search |
38| **Social buzz / trending papers** | Twitter/X (xreach) | Reddit |
39| **Code implementations** | GitHub (gh search) | Exa (get_code_context) |
40| **Finding similar papers** | Exa (semantic) | Semantic Scholar (citations) |
41
42## Workflow
43
44### Step 1: Understand the Query
45
46Before searching, clarify:
47- **Scope**: Broad survey vs. specific subtopic
48- **Recency**: All time vs. last N years vs. latest only
49- **Venue preference**: Top-tier only? Specific conference?
50- **Quantity**: Top 5 vs. comprehensive survey
51- **Depth**: Quick list vs. deep research with synthesis
52
53### Step 2: Select Search Strategy
54
55**Quick search (single engine):**
56For simple, well-defined queries. Use Semantic Scholar or arXiv directly.
57
58**Multi-engine search (2-3 engines in parallel):**
59For broader topics. Run engines simultaneously, deduplicate results.
60
61**Deep research (Gemini):**
62For complex, multi-faceted research questions. Gemini deep research mode synthesizes across many sources and provides a structured analysis with citations. Use this when:
63- The question spans multiple subfields
64- You need synthesis, not just a list of papers
65- The user explicitly asks for "deep research" or "comprehensive survey"
66
67### Step 3: Execute Search
68
69```bash
70# Semantic Scholar — paper metadata, citations, author search
71# Free, no API key needed
72node scripts/search/semantic-scholar.mjs "query" -n 20
73
74# arXiv — latest preprints, category filtering
75# Free, no API key needed
76node scripts/search/arxiv.mjs "query" -n 15 --sort submittedDate --cat cs.CL
77
78# Tavily — general web search, AI-optimized
79node scripts/search/search.mjs "query site:arxiv.org OR site:aclanthology.org" -n 10
80node scripts/search/search.mjs "query" --deep # deeper search mode
81
82# Exa — semantic search, finding similar content
83mcporter call 'exa.web_search_exa(query: "query", numResults: 10)'
84
85# Gemini — deep research (for complex questions)
86# Use gemini-3.1-pro model with web search grounding
87# Prompt: "Survey the recent literature on [topic]. Identify key papers,
88# main approaches, and open problems. Cite specific papers."
89
90# AMiner — Chinese academic community
91# Uses AMINER_API_KEY
92```
93
94### Step 4: Deduplicate & Rank
95
96Merge results across engines:
971. Deduplicate by title similarity (fuzzy match, >90% = same paper)
982. Rank by: citation count × recency × venue tier × relevance
993. Flag if a paper appears in multiple engines (higher confidence)
100
101### Step 5: Present Results
102
103Format as a ranked list with key metadata:
104
105```
1061. **[Title]** (Venue Year, Citations: N)
107 Authors: [First author] et al.
108 TL;DR: [1 sentence]
109 Why relevant: [connection to user's query]
110
1112. ...
112```
113
114### Step 6: Deep Dive (Optional)
115
116If user wants to go deeper on any paper:
117- Switch to paper-reading skill
118- Or add to Zotero reading queue (use zotero-management skill)
119
120## Search Tips
121
122- **Use specific terminology**: "multi-agent reinforcement learning" > "MARL" > "agents working together"
123- **Combine with venue filter**: Adding venue:ACL or category cs.CL dramatically improves precision
124- **Check citation chains**: A highly-cited paper's references and citers are often gold
125- **Cross-lingual**: For Chinese papers, try both English and Chinese queries
126- **Date filter for SOTA**: Use --sort submittedDate on arXiv to find the latest approaches
127- **Gemini for synthesis**: When you need to understand a field (not just list papers), use Gemini deep research to get a narrative overview first, then drill into specific papers
128
129## Quality Signals
130
131When ranking, weight these signals:
132- **Citation count**: High for established work, less meaningful for papers < 6 months old
133- **Venue tier**: ACL/EMNLP/NeurIPS/ICML > workshops > arXiv-only
134- **Author reputation**: Check if senior authors are established in the field
135- **Code availability**: Papers with code are more verifiable
136- **Reproducibility**: Clear methodology sections and experimental details
137
In the file
SKILL.md834 words
Files1
LicenceMIT
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈180
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
1,220
on trigger
The instruction body, read only when the skill fires.
0.70%
of a 200k window
Ten skills this size would take about 7% of the window before you open a file.
050k100k150k200k context window

1.4k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Middling. Fine to keep on in a project where you use it weekly, worth unloading in one where you never do.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

Adoption
Installsnone yet
Ratingno reviews yet

The procedure it runs

The procedure has not been published here. It is in the skill’s own SKILL.md, which its author has not sent to the marketplace yet.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

It writes no files and reaches no network. All it changes is how the model reasons and writes.

What it asks for
Writes filesno
Network accessno

Read from the allowed-tools line of this skill’s own SKILL.md. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

1 file, 5.6 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md5.6 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 1 file you can review in full before installing. The MIT licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Literature Search · 1.4k tokens when loaded npx mcprush@latest skill add jxtse/literature-search

Writes to .claude/skills/literature-search/ in the current project. Add --global to put it in your home directory instead, for every project.

Which clients pick it up on their own

A skill is a folder of text. A client with a skills folder reads it without being told; everywhere else the same text works, it is just handed to the model rather than found.

Claude Code.claude/skills/
Claude Desktop
ChatGPT
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok.grok/skills/
Zed.agents/skills/
Windsurf.windsurf/skills/
Agent SDK.claude/skills/
HTTP / API
This release
Versionnot versioned
Publishedno release date on file
PriceFree
Referencejxtse/literature-search

Versions

Its author publishes no version number, so there is nothing here to pin to: what you install is the folder as it stands today. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

v
  • No earlier releases have been published to the marketplace.
Pinning

Nothing to pin to: this skill carries no version number of its own. What you install is what the folder holds on the day you install it.

Reviews

no reviews yet · no installs yet

Nobody has reviewed this skill yet. The rating is the mean of the reviews written here, so there is none until somebody writes the first.

Who can post

Only accounts that have had the skill installed for fourteen days, so a review is written after living with it rather than after reading it. Publishers may reply once.

Who wrote it

JX
jxtse

Publishes on mcprush.

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