Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/aniketkrs/research-papernpx agentmods add skills/aniketkrs/research-paper/get-research-paperWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aniketkrs/research-paper/get-research-paper)<a href="https://agentmods.dev/skills/aniketkrs/research-paper/get-research-paper"><img src="https://agentmods.dev/badge/skills/aniketkrs/research-paper/get-research-paper/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aniketkrs/research-paper/get-research-paper"><img src="https://agentmods.dev/badge/skills/aniketkrs/research-paper/get-research-paper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00159 | $0.02365 |
| Opus 5 | $0.00079 | $0.01182 |
| Sonnet 5 | $0.00032 | $0.00473 |
| Haiku 4.5 | $0.00016 | $0.00236 |
Grade A, and why
get-research-paper scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 abibliography.yamlready for theresearch-paperskill.
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]"
What ships with it
20 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- examples/sample-results.md 10.0 KB
- instructions/core.md 8.2 KB
- instructions/freshness.md 8.7 KB
- manifest.json 4.6 KB
- prompts/ranking.md 5.9 KB
- prompts/search-strategy.md 6.3 KB
- prompts/summarization.md 5.8 KB
- schemas/paper-result.json 4.7 KB
- sources/arxiv.md 5.4 KB
- sources/google-scholar.md 4.6 KB
- sources/pubmed.md 4.8 KB
- sources/semantic-scholar.md 5.8 KB
- sources/source-priority.md 6.3 KB
- templates/briefing.md 4.7 KB
- templates/paper-summary.md 3.8 KB
- templates/reading-list.md 3.9 KB
- toolchains/arxiv_search.py 13 KB runs code
- workflows/handoff-to-writer.md 5.8 KB
- workflows/search.md 8.3 KB
- workflows/synthesis.md 4.6 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 222 lines · 159 tokens per session scan A 1b090c03be27
get-research-paper is a skill published in the GitHub repository aniketkrs/research-paper (4 stars, last pushed 3mo ago), licensed MIT. It adds 159 tokens to every session and 2,365 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
ml-paper-writing
Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.
aaai-reproducibility
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across…
acl-reproducibility
Use when strengthening reproducibility evidence for an ACL paper reviewed through ACL Rolling Review, covering the Responsible NLP checklist end to end, hyperparameter and compute reporting, prompt and decoding disclosure for LLM experiments, data contamination auditing, variance across runs, and checklist-to-paper…
aaai-experiments
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
aaai-topic-selection
Use when deciding whether a project is a strong AAAI submission across its broad AI scope, should be reframed or routed to a dedicated track such as AI for Social Impact or AI Alignment, or should instead go to IJCAI, NeurIPS, ICML, ICLR, AISTATS, UAI, ACL, CVPR, KDD, CHI, ICRA, or another specialist venue.
acl-experiments
Use when designing or auditing experiments for an ACL paper, covering tuned LLM baselines, multi-dataset and multilingual evaluation, statistical significance and variance, human evaluation with agreement reporting, contamination and prompt-sensitivity controls, ablations, and error-analysis expectations in NLP…