| name | get-research-paper |
| description | Discovers, retrieves, ranks, and summarizes real existing research papers on any topic. Searches arXiv, Google Scholar, PubMed, Semantic Scholar, and reputable open repositories; returns a curated reading list with verified DOIs, key findings, and citation-ready metadata. Activates on slash commands (`/get-research-paper`, `/find-paper`, `/fetch-paper`, `/papers-on`, `/scholar`) and natural-language requests like "get research paper on …", "find papers about …", "what are the top papers on …". Hands off cleanly to the `research-paper` skill for paper writing. Runtime-neutral — works with Claude Code, OpenCode, Cursor, Cline, Codex, Aider, Amp, and 50+ agents. Use when this capability is needed. |
| metadata | {"author":"aniketkrs"} |
Get Research Paper
A research-discovery skill. Where the research-paper skill writes
papers, this skill finds them. Give it a topic, get a ranked,
de-duplicated reading list of real existing papers with verified DOIs,
key findings, and ready-to-cite metadata.
This file is the entry point. Heavier guidance (per-source
strategies, ranking criteria, summarization prompts) lives in topic
folders and is loaded on demand.
1. When to activate
Slash commands
| Command | What it does |
|---|
/get-research-paper <topic> | Curated reading list (default 10 papers) |
/find-paper <topic> | Alias for /get-research-paper |
/find-papers <topic> | Alias for /get-research-paper |
/fetch-paper <topic> | Alias for /get-research-paper |
/papers-on <topic> | Alias for /get-research-paper |
/scholar <topic> | Quick scholarly summary (5 papers, 2-line summaries) |
Common options:
--n <N> — number of papers (default 10).--years <range> — e.g. 2020-2024, last-5, since-2018.--source <src> — arxiv, scholar, pubmed, semantic-scholar, all (default).--depth <quick|standard|deep> — summary detail.--style <harvard|apa|ieee|...> — pre-format the bibliography.--audience <academic|technical|general> — adjust summary register.--handoff — emit a bibliography.yaml ready for the research-paper skill.
Natural-language patterns
- "get research paper on / about / for [topic]"
- "find research papers on [topic]"
- "find papers on / about [topic]"
- "what are the top papers on [topic]"
- "show me research on [topic]"
- "fetch papers about [topic]"
- "list papers on [topic]"
- "literature on [topic]" (shorter than
/literature-review)
- "scholar [topic]"
Negative activation
Do NOT activate for:
- Requests to write a paper (route to
research-paper).
- Requests to review or critique a draft (route to
research-paper).
- Casual questions ("what is X?") that don't need scholarly sources.
- Pure code / API documentation lookup.
2. Output contract
Every run produces, at minimum:
- Reading list — N papers with:
- Title (full)
- Authors (first 3 + "et al." if more)
- Year
- Venue / journal / preprint server
- DOI / arXiv ID / URL
- 2–4 sentence summary (problem → method → finding → significance)
- Relevance score (1–5) and quality score (per
citation_engine rubric)
- Cite key (lowercase author_year_word) ready for use
- Field briefing (optional, default ON for
--depth deep) — a
1-paragraph synthesis of where the field is and what the dominant
approaches are.
bibliography.yaml — canonical-format file ready to drop into
the research-paper skill.Known-gaps.md block — every paper that couldn't be verified is
surfaced with severity and recommended fix.
See templates/reading-list.md, templates/paper-summary.md,
templates/briefing.md.
3. Core principles
- Anchor to TODAY's date FIRST. Before any search, determine
today's actual date (via
date -u +%Y-%m-%d, runtime context, or
asking the user). Never default to training-cutoff dates. Year
ranges like --years last-3 are computed from today. Full protocol:
instructions/freshness.md.
- Real papers only. Never invent papers, DOIs, authors, or
findings. Use only sources the model can verify (or honestly mark
[UNVERIFIED — offline]).
- De-duplicate aggressively. Same DOI / arXiv ID / first-author + year + title prefix → one entry.
- Rank by relevance and quality. A bad paper that mentions the
topic is less useful than a great paper that's two clicks adjacent.
- Cite-ready by default. Every entry has cite_key + DOI + ready-to-use formatted citation.
- Triangulation. For load-bearing claims, prefer ≥ 2 independent
sources. Note when a finding rests on a single source.
- Honest about limits. Without web tools, the model relies on
training-data knowledge — flag every entry accordingly.
- Hand off cleanly. Output is consumable by the
research-paper
skill via --handoff mode.
4. Top-level workflow
intake → search-strategy → fan-out search → rank+dedupe →
verify → summarize → assemble briefing → output (+ optional handoff)
Each step has a dedicated playbook. Read the file for the step you're
on; persist the artifact; move on. Master pipeline:
workflows/search.md.
5. Source coverage
| Source | When to prefer | Tool |
|---|
| arXiv | CS, ML, AI, physics, math, quant-bio | toolchains/arxiv_search.py (works offline-only via API) |
| Google Scholar | Generic / cross-discipline broad surveys | WebSearch with site:scholar.google.com |
| Semantic Scholar | API-friendly, citation graph, summaries | WebFetch of api.semanticscholar.org |
| PubMed / PubMed Central | Biomedical, life sciences | WebFetch of eutils.ncbi.nlm.nih.gov |
| DBLP | CS authors / venues / publication lists | WebFetch of dblp.org |
| ACM DL | HCI, systems, security, networks | WebSearch with site:dl.acm.org |
| IEEE Xplore | Engineering, signal, hardware | WebSearch with site:ieeexplore.ieee.org |
| OpenReview | NeurIPS, ICLR, ICML reviews + papers | WebFetch of openreview.net |
| Crossref | DOI verification + metadata fill-in | WebFetch of api.crossref.org |
| Retraction Watch | Retraction screening | WebFetch of retractionwatch.com / database |
Per-source strategy details: sources/.
6. Ranking and quality
Each candidate paper is scored on:
- Authority (0–4) — venue quality (peer-review rigor, impact).
- Methodological rigor (0–3) — replicability, sample size, sound stats.
- Recency / relevance (0–3) — fresh + topical, OR foundational + canonical.
- Total (0–10) — used to rank.
Default reading lists keep papers scoring ≥ 5. Higher floors raise
the bar (--quality-floor 7).
Full rubric: prompts/ranking.md (extends the
citation_engine/source-evaluation.md of the research-paper skill).
7. Handoff to research-paper
After producing a reading list:
/get-research-paper "graph neural networks for fraud detection" \
--n 25 --handoff --style ieee --years 2020-2024
Produces:
gnn-fraud-detection/
├── reading-list.md # human-readable curated list
├── bibliography.yaml # ← canonical file for research-paper skill
├── briefing.md # 1-paragraph synthesis
└── Known-gaps.md # any unverifiable items
The user then runs the writer skill with the produced bibliography:
/research "graph neural networks for fraud detection" \
--style ieee --bibliography ./gnn-fraud-detection/bibliography.yaml
The writer reads the curated bibliography directly — no re-search needed.
8. Failure handling
- No web search available → use model-known papers, mark every
entry
[UNVERIFIED — offline], lower the recommended --n to 5–8,
and surface the limitation in the briefing.
- Search returns nothing → broaden the query (drop adjectives,
try synonyms), then return what was found with an honest note.
- Conflicting metadata across sources → prefer the published
(peer-reviewed) version over the preprint; note the relationship.
- Retracted paper detected → drop from the list; flag in
Known-gaps.md.
- Out-of-scope topic → surface a note in the briefing; deliver
best-effort results.
9. Where to look next
- Plan a search →
workflows/search.md
- Per-source strategy →
sources/
- Ranking rubric →
prompts/ranking.md
- Summarization →
prompts/summarization.md
- Output templates →
templates/
- Hand off to writer →
workflows/handoff-to-writer.md
- arXiv search tool →
toolchains/arxiv_search.py
This skill is intentionally smaller than the writer skill. Its job is
discovery and curation; the heavy lifting (writing, methodology,
review) lives in research-paper.
Source: aniketkrs/research-paper — distributed by TomeVault.
