Nature-Style Scientific Figures
Yuan1z0825/nature-skills
Creates, revises, audits and exports manuscript-ready scientific figures in Python or R, and routes AI-generated graphical abstracts to a separate workflow.
Deep research with structured reports and charts. An agent skill from aws-samples/sample-strands-agent-with-agentcore.
Install Research Agent
$ npx skills add aws-samples/sample-strands-agent-with-agentcore --skill research-agent -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aws-samples/sample-strands-agent-with-agentcore research-agent --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aws-samples/sample-strands-agent-with-agentcore.git skills-src && mkdir -p .claude/skills && cp -r skills-src/chatbot-app/agentcore/skills/research-agent .claude/skills/research-agent && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "research-agent" agent skill from https://github.com/aws-samples/sample-strands-agent-with-agentcore/tree/main/chatbot-app/agentcore/skills/research-agent into .claude/skills/research-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-agent", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aws-samples/sample-strands-agent-with-agentcore/tree/main/chatbot-app/agentcore/skills/research-agentType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aws-samples/sample-strands-agent-with-agentcore --skill research-agent -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aws-samples/sample-strands-agent-with-agentcore research-agent --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/sample-strands-agent-with-agentcore.git skills-src && mkdir -p .agents/skills && cp -r skills-src/chatbot-app/agentcore/skills/research-agent .agents/skills/research-agent && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "research-agent" agent skill from https://github.com/aws-samples/sample-strands-agent-with-agentcore/tree/main/chatbot-app/agentcore/skills/research-agent into .agents/skills/research-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-agent", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws-samples/sample-strands-agent-with-agentcore --skill research-agent -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aws-samples/sample-strands-agent-with-agentcore research-agent --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/sample-strands-agent-with-agentcore.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/chatbot-app/agentcore/skills/research-agent .cursor/skills/research-agent && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "research-agent" agent skill from https://github.com/aws-samples/sample-strands-agent-with-agentcore/tree/main/chatbot-app/agentcore/skills/research-agent into .cursor/skills/research-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-agent", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aws-samples/sample-strands-agent-with-agentcore.git --path chatbot-app/agentcore/skills/research-agent--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aws-samples/sample-strands-agent-with-agentcore --skill research-agent -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aws-samples/sample-strands-agent-with-agentcore research-agent --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/sample-strands-agent-with-agentcore.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/chatbot-app/agentcore/skills/research-agent .gemini/skills/research-agent && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "research-agent" agent skill from https://github.com/aws-samples/sample-strands-agent-with-agentcore/tree/main/chatbot-app/agentcore/skills/research-agent into .gemini/skills/research-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-agent", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aws-samples/sample-strands-agent-with-agentcore research-agentInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aws-samples/sample-strands-agent-with-agentcore --skill research-agent -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aws-samples/sample-strands-agent-with-agentcore.git skills-src && mkdir -p .github/skills && cp -r skills-src/chatbot-app/agentcore/skills/research-agent .github/skills/research-agent && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "research-agent" agent skill from https://github.com/aws-samples/sample-strands-agent-with-agentcore/tree/main/chatbot-app/agentcore/skills/research-agent into .github/skills/research-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-agent", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws-samples/sample-strands-agent-with-agentcore --skill research-agent -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aws-samples/sample-strands-agent-with-agentcore research-agent --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws-samples/sample-strands-agent-with-agentcore.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/chatbot-app/agentcore/skills/research-agent .opencode/skills/research-agent && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "research-agent" agent skill from https://github.com/aws-samples/sample-strands-agent-with-agentcore/tree/main/chatbot-app/agentcore/skills/research-agent into .opencode/skills/research-agent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "research-agent", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
research-agent- GitHub stars
- 195
- Token cost
- ~1.1k tokens
- SKILL.md length
- 492 words
- Files
- 1
- Skills in repo
- 24
- Repo updated
- First seen
- Licence
- MIT
At a glance
Deep research with structured reports and charts. An agent skill from aws-samples/sample-strands-agent-with-agentcore.
- The user explicitly requests research/analysis
- SKILL.md covers When to use — ALL of these…, When NOT to use — default to…, How to invoke and Output, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Needs data visualization with charts
What it does
Research Agent is an agent skill from aws-samples/sample-strands-agent-with-agentcore, published by the product's own GitHub organization. Deep research with structured reports and charts. ONLY use when the user explicitly requests research/analysis, or needs data visualization with charts, or quantitative/comparative analysis across multiple sources. Do NOT use for simple questions or quick lookups.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Deep research and Data visualization. The repository describes itself as: Reference architecture for agentic AI chatbots with Strands Agents and Amazon Bedrock AgentCore. The licence is MIT.
When your agent uses it
- The user explicitly requests research/analysis
- Needs data visualization with charts
- Quantitative/comparative analysis across multiple sources
- Simple questions
Example prompts
- “/research-agent”
What it can do on your machine
Read from SKILL.md and the folder at commit 6dd9d13. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Research Agent loads about 1.1k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 492 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from aws-samples/sample-strands-agent-with-agentcore at commit 6dd9d13, republished under its MIT licence (© aws-samples). 492 words, ~1,068 tokens.
Download SKILL.mdSave it as
.claude/skills/research-agent/SKILL.md (or your agent's skills folder).- name
- research-agent
- description
- Deep research with structured reports and charts. ONLY use when the user explicitly requests research/analysis, or needs data visualization with charts, or quantitative/comparative analysis across multiple sources. Do NOT use for simple questions or quick lookups.
Research Agent
Autonomous research agent that plans, searches across the web, synthesizes findings, and returns a structured markdown report with citations and charts.
When to use — ALL of these require explicit user intent or clear analytical need
- The user explicitly asks for "research", "report", "analysis", "deep dive", or "investigate"
- The user needs data visualization — charts, graphs, trend plots
- Quantitative or comparative analysis across multiple data points (market sizing, benchmarking, statistical comparisons)
- Multi-section structured reports (literature reviews, competitive analyses, technology surveys)
When NOT to use — default to simpler tools first
- General conversation, Q&A, or factual questions — answer directly
- A single lookup that
wikipedia_searchorgoogle_web_searchcan resolve - Summarizing a single article or URL — use
fetch_url_contentinstead - Code-related tasks — use the
code-agentskill - Browser automation — use the
browser-automationskill - Email, calendar, or other tool-based tasks — use the appropriate skill directly
Important: When in doubt, do NOT delegate to research-agent. Use google_web_search or other tools directly. Only escalate to research-agent when the task clearly requires multi-source synthesis, structured reporting, or chart generation.
How to invoke
Call the research_agent tool with a single plan argument. The plan is free-form prose; include:
- Objectives — what the user is trying to learn or decide
- Topics — the specific angles / subtopics to cover
- Structure — the section layout you want in the final report
Example:
research_agent(plan="""
Research Plan: AI Code Assistant Market 2026
Objectives:
- Current market size and growth trends
- Leading products and differentiators
- Enterprise adoption barriers
Topics:
1. Global market statistics and forecasts
2. Top products (Copilot, Cursor, Claude Code, etc.) and positioning
3. Pricing models and enterprise SKUs
4. Security/compliance concerns raised by buyers
Structure:
- Executive Summary (3-5 bullets)
- Market Overview
- Product Landscape
- Enterprise Adoption
- Outlook
""")The tool returns immediately with a started receipt containing job_id and
artifact_id. Research continues in the background and emits
research_step progress events. When it finishes, the report is saved as a
research artifact and delivered back into the conversation automatically.
Output
- Markdown report with
#/##headings, bullet lists, and inline citations - Any charts the agent generated are embedded in the markdown
- The full report is also persisted as an
artifactsentry so the user can open it from the canvas
Show full SKILL.md (198 more words)Show less
Guidelines for the orchestrator
- Don't fabricate the plan — use the user's own words and just structure them into objectives/topics/structure. If the user only gave a one-line request, expand it into 2-3 objectives but stay true to intent.
- Split a broad request into parallel jobs only when the objectives are independent and each report is useful on its own (for example, separate market, technical, and regulatory analyses). Prefer 2-3 well-scoped jobs over many narrow searches.
- Keep one job when the sections must share evidence, build on each other, or form one coherent report. Use one call per distinct objective and do not create duplicate jobs for the same objective.
- If the user asks a follow-up ("add a section on X", "dig deeper into Y"), call
research_agentagain with an updated plan — the agent itself does not have persistent memory across calls. - Treat a
startedreceipt as accepted background work, not a completed report. Tell the user it has started and continue with any other useful work. - When the completion is delivered, do NOT restate the whole report in chat. The report is already rendered as an artifact; a 1-2 sentence summary pointing the user to the canvas is enough.
© aws-samples, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in chatbot-app/agentcore/skills/research-agent of aws-samples/sample-strands-agent-with-agentcore.
Open the folder on GitHubat commit 6dd9d13
Compare with similar skills
Research Agent next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Research Agent this skillaws-samples/sample-strands-agent-with-agentcore | 195 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Nature-Style Scientific FiguresYuan1z0825/nature-skills | 46k | — | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Engineering Figure Agentheyu-233/engineering-figure-agent | 305 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Scientific Figure GeneratorDeepshare-Official/CCF-Figure | 225 | — | ~1.8k | Automated safety check: Pass | MIT | |
| Scanpy Single-Cell Analysisdavila7/claude-code-templates | 32k | 16 repos | ~2.8k | Automated safety check: Pass | MIT | |
| deepTools NGS Toolkitdavila7/claude-code-templates | 32k | 13 repos | ~4.5k | Automated safety check: Pass | MIT |
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Engineering Figure Agent
heyu-233/engineering-figure-agent
A skill your agent uses when the user needs engineering or research-paper figures: system architecture diagrams, algorithm workflows, hardware schematics, benchmark charts, ablation plots, figure…
Scientific Figure Generator
Deepshare-Official/CCF-Figure
Generate publication-ready scientific figures for AI/CS research papers.
Scanpy Single-Cell Analysis
davila7/claude-code-templates
Walks through single-cell RNA-seq analysis with Scanpy: loading .h5ad and 10X data, QC, normalization, PCA and UMAP, Leiden clustering, marker genes and cell type annotation.
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Guides use of deepTools on sequencing data: BAM to bigWig conversion, QC, sample correlation, and heatmaps or profiles around TSS and peaks for ChIP-seq, RNA-seq and ATAC-seq.
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Turns raw flux balance analysis output and a COBRApy model into gene essentiality maps, phenotypic phase planes, flux sampling results, pathway summaries and secretion predictions.
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Related
Categories
Questions about Research Agent
What does Research Agent do?
Deep research with structured reports and charts. An agent skill from aws-samples/sample-strands-agent-with-agentcore. Research Agent is an agent skill from aws-samples/sample-strands-agent-with-agentcore, published by the product's own GitHub organization. Deep research with structured reports and charts.
When should I use Research Agent?
Research Agent fits situations like: the user explicitly requests research/analysis; needs data visualization with charts; quantitative/comparative analysis across multiple sources; simple questions.
How do I install Research Agent in Claude Code?
Run `npx skills add aws-samples/sample-strands-agent-with-agentcore --skill research-agent -a claude-code`. Or copy the skill folder (chatbot-app/agentcore/skills/research-agent in aws-samples/sample-strands-agent-with-agentcore) into .claude/skills/research-agent in your project. Claude Code loads it when a task matches its description.
How do I install Research Agent in Codex?
Run `npx skills add aws-samples/sample-strands-agent-with-agentcore --skill research-agent -a codex`. Or copy the skill folder (chatbot-app/agentcore/skills/research-agent in aws-samples/sample-strands-agent-with-agentcore) into .agents/skills/research-agent in your project. Codex loads it when a task matches its description.
Can I use Research Agent in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws-samples/sample-strands-agent-with-agentcore --skill research-agent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-agent, .gemini/skills/research-agent, .github/skills/research-agent and .opencode/skills/research-agent in your project.
What does Research Agent need to run?
SKILL.md names no scripts, command-line tools or credentials: Research Agent is instructions for the agent only.
Does Research Agent access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Research Agent safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Research Agent use?
Research Agent is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Research Agent use?
About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Research Agent?
Skills that share tags, products or a category with Research Agent: Nature-Style Scientific Figures (Yuan1z0825/nature-skills, 46k stars), Engineering Figure Agent (heyu-233/engineering-figure-agent, 305 stars), Scientific Figure Generator (Deepshare-Official/CCF-Figure, 225 stars) and Scanpy Single-Cell Analysis (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Research Agent?
aws-samples (a GitHub organization, an official publisher) maintains it in aws-samples/sample-strands-agent-with-agentcore, which has 195 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 6, 2026.
Source: aws-samples/sample-strands-agent-with-agentcore on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.