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Literature Discovery
Systematic discovery and landscape mapping of scientific literature with citation analysis and venue quality filtering.
Free
literature-discovery
Example session with this skill installed
Use the literature-discovery skill to map recent research on retrieval-augmented generation (RAG) for enterprise knowledge bases, focusing on the last 5 years and Q1/Q2 venues.
- Read your context and instructions
- Compiled the literature-discovery
Research clusters
| Cluster | Focus | Leading venues | Maturity |
|---|---|---|---|
| Retrieval architectures | Dense/sparse hybrid, late interaction | SIGIR, ACL, EMNLP | Mature |
| Enterprise grounding | Domain adaptation, access control | KDD, VLDB, ICML | Growing |
| Evaluation & benchmarking | RAG-specific metrics, human eval | ACL, TACL | Emerging |
| Long-context vs RAG | Context windows replacing retrieval | ICLR, NeurIPS | Hot |
Seminal papers
- Lewis et al. (2020) — Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (foundational)
- Karpukhin et al. (2020) — Dense Passage Retrieval
- Izacard & Grave (2021) — Fusion-in-Decoder
- Gao et al. (2023) — RAG survey + benchmarks (ACL)
- Asai et al. (2024) — Self-RAG / adaptive retrieval
Leading authors, datasets & metrics
- Institutions: Meta AI, Stanford, U. Waterloo, Berkeley, Tsinghua
- Datasets: Natural Questions, MS MARCO, KILT, HotpotQA, FinanceBench
- Metrics: EM/F1, recall@k, faithfulness, citation precision
Trend
Shift from "bigger retriever" toward
adaptive retrieval + factual-grounding evaluation, especially for private enterprise corpora.
Next steps
- Run
state-of-the-arton the 8 seminal papers for a narrative review. - Run
research-gapto confirm the evaluation gap before committing.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Starting a new research project and don't know where the field stands? This skill discovers and maps the scientific literature for any topic before you commit.
What it does:
- Searches recent publications (configurable 5–10 year window)
- Prioritizes Q1/Q2 journals and top conferences
- Identifies seminal papers and groups results into research clusters
- Detects trends and maps leading authors, institutions, datasets, tools, and metrics
What you get:
A structured literature map instead of an unstructured pile of PDFs, so you can see who's working on what, what's been done, and where the field is heading.
Why buy it:
It replaces hours of manual searching and reading with a ready-made expert workflow. Pair it with "state-of-the-art" and "research gap" to go from "I have a topic" to "I have a defensible contribution."
- Conducting a systematic literature review for a thesis or grant proposal.
- Onboarding a research team to a new technical domain or subfield.
- Identifying potential collaborators and high-impact venues for publication.
- Benchmarking new experimental results against established community datasets and metrics.
Known limitations
Initial search accuracy depends on the precision of the provided research topic and time window. The skill may have a language bias toward English-language publications, but I have tried with Spanish, and it worked very well too.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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