What is research-scout?

A research guide for finding useful methods in academic papers, research blogs, and curated newsletters about AI, machine learning, and software engineering.

Use it to mine research for techniques, create idea and anti-pattern cards, design adoption recipes, and define tests for whether a method is worth using.

It turns broad research reading into practical ideas with evidence checks, reproducibility notes, and warnings about unreliable or overhyped findings.

research-scout — Skill for Claude Code and Codex by vasilyu1983

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add vasilyu1983/AI-Agents-public --skill research-scout

Clone the repo

git clone --depth 1 https://github.com/vasilyu1983/AI-Agents-public

Made for: Claude Code, Codex.

Or install ai-agents, the plugin that ships this one along with the rest of its 144 skills.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/research-scout/github.svg)](https://agentmods.dev/skills/vasilyu1983/ai-agents-public/research-scout)

Your own site

<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/research-scout"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/research-scout/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/vasilyu1983/ai-agents-public/research-scout"><img src="https://agentmods.dev/badge/skills/vasilyu1983/ai-agents-public/research-scout.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 6,066 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00039	$0.06066
Opus 5.5	$0.00016	$0.02426
Sonnet 5.5	$0.00008	$0.01213
Haiku 4.5	$0.00004	$0.00607

Measured 22d ago against content hash d5591f2e0609, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

research-scout 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 22d ago.

The scan reads SKILL.md. This mod also ships 9 executable files (scripts/aggregate_research_ideas.py, scripts/generate_arxiv_queries.py, scripts/generate_blog_queries.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/universal/research-scout/SKILL.md · 293 lines

How it starts

The opening of the file, as written. The whole thing — 293 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dev Research Scout

Scans high-signal research sources for methods, frameworks, and ideas worth applying to your own work, and converts the top finds into idea cards with how-to-apply recipes, evidence quality grades, and reproducibility notes.

Supported sources: arXiv, Hugging Face Papers, Semantic Scholar, conference proceedings (NeurIPS / ICML / ICLR / ACL / EMNLP / KDD), industry research blogs (Anthropic / OpenAI / DeepMind / Google Research / Meta AI / Microsoft Research / Apple ML), and curator newsletters (Lilian Weng, Sebastian Raschka, Eugene Yan, Latent Space, Simon Willison, The Batch, Import AI, Interconnects / Nathan Lambert, Davis Summarizes Papers / Davis Blalock).

For a concrete startup area, workflow or domain-specific technical question, use specialist-source-routing.md. It routes PMC, NIH ExPORTER, Free Law Project, USPTO, Ubuntu IRC, PhilPapers, Project Gutenberg, Wikipedia and YouTube alongside the existing GitHub, Hacker News and Stack Exchange owners. These are conditional evidence or product-input sources; they do not expand this skill's default method-source enum or establish commercial demand.

Output is a generative toolkit, not a landscape report: a pattern catalog (methods worth stealing, with how-to-apply), an anti-pattern catalog (research traps — irreproducibility, benchmark gaming, hype), and recipes (extraction, validation-before-adoption, kill criteria).

Key distinction from sibling scouts:

This skill = research-grade idea mining (papers + research blogs + curated synthesis)
research-painpoint-scanner = community-pain mining (Reddit / HN / GitHub Issues / G2 / Stack Overflow)
research-arxiv-scout = arXiv-only deep triage with category taxonomy and attribution; specialist downstream
research-git = public GitHub repo research for skills, practices, and code patterns (separate concern)

Use this skill when the question is "what methods or frameworks are worth stealing from recent research?" — escalate to research-arxiv-scout for arXiv-only work where category taxonomy and attribution matter most.

Read the full file on GitHub · 293 lines

Files

What ships with it

33 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.

Changes

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.

22d ago Changed · +13 lines · +3 tokens per session d5591f2e0609
1mo ago Changed · -140 lines 2164ee603b7c
1mo ago First seen · 420 lines · 36 tokens per session scan A ab0925d0d511

Subscribe to this mod's changes

research-scout is a skill published in the GitHub repository vasilyu1983/AI-Agents-public (101 stars, last pushed 11d ago), licensed MIT. It adds 39 tokens to every session and 6,066 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.

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plotting-agent

Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimentallog.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER…

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outline-agent

Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimentallog.md, template.tex, conferenceguidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citation hints. TRIGGER when the orchestrator…

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paper-autoraters

Run the four paper-quality autoraters from PaperOrchestra (arXiv:2604.05018, App. F.3) — Citation F1 (P0/P1 partition + Precision/Recall/F1), Literature Review Quality (6-axis 0-100 with anti-inflation rules), SxS Overall Paper Quality (side-by-side), and SxS Literature Review Quality (side-by-side). TRIGGER when the…

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