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Agent skill

Trend Analysis

by jerry609 in jerry609/PaperBot

This skill should be used when the user asks to "analyze trends in a research area", "what is trending in X", "research landscape for topic Y", "topic trend analysis", "emerging themes in machine…

MITAuto-check passedData & Analytics

Install Trend Analysis

skills CLI
$ npx skills add jerry609/PaperBot --skill trend-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jerry609/PaperBot trend-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jerry609/PaperBot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/trend-analysis .claude/skills/trend-analysis && rm -rf skills-src

Use ~/.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/

Facts

Skill name
trend-analysis
GitHub stars
108
Token cost
~904 tokens
SKILL.md length
418 words
Files
1
Skills in repo
4
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when the user asks to "analyze trends in a research area", "what is trending in X", "research landscape for topic Y", "topic trend analysis", "emerging themes in machine…

  • Works in 4 steps: Load research context (optional) → Search for papers → Analyze trends → …
  • Asks to analyze trends in a research area
  • SKILL.md covers Workflow, Degraded Mode and Notes
  • Needs OPENAI_API_KEY and ANTHROPIC_API_KEY

What it does

Trend Analysis is an agent skill from jerry609/PaperBot. This skill should be used when the user asks to "analyze trends in a research area", "what is trending in X", "research landscape for topic Y", "topic trend analysis", "emerging themes in machine learning", "what are researchers working on in Z", or wants to survey a field and identify emerging patterns across multiple papers using PaperBot MCP tools.

Its SKILL.md is about 900 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 Data & Analytics, covering Forecasting and time series and Literature review. It works with arXiv. The repository describes itself as: Academic Personal AI Infrastructure. The licence is MIT.

When your agent uses it

  • Asks to analyze trends in a research area
  • What is trending in X
  • Research landscape for topic Y
  • Topic trend analysis

Example prompts

  • “analyze trends in a research area”
  • “what is trending in X”
  • “research landscape for topic Y”
  • “/trend-analysis”

Requirements

  • A credential in OPENAI_API_KEY
  • A credential in ANTHROPIC_API_KEY

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Load research context (optional)
  2. Search for papers
  3. Analyze trends
  4. Save synthesis

What it can do on your machine

Read from SKILL.md and the folder at commit 9030c5e. 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 these keys or tokens, usually read from environment variables:

    • OPENAI_API_KEY
    • ANTHROPIC_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Trend Analysis loads about 904 tokens when it runs. Until then it costs about 92 tokens; SKILL.md has 418 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~904

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 jerry609/PaperBot at commit 9030c5e, republished under its MIT licence (© jerry609). 418 words, ~904 tokens.

Download SKILL.mdSave it as .claude/skills/trend-analysis/SKILL.md (or your agent's skills folder).
name
trend-analysis
description
This skill should be used when the user asks to "analyze trends in a research area", "what is trending in X", "research landscape for topic Y", "topic trend analysis", "emerging themes in machine learning", "what are researchers working on in Z", or wants to survey a field and identify emerging patterns across multiple papers using PaperBot MCP tools.
tools
paper_search, analyze_trends, get_research_context, save_to_memory

Trend Analysis Workflow

Identify research trends across a topic by collecting papers, analyzing patterns, and saving a synthesis of emerging themes.

Workflow

Step 1: Load research context (optional)

If a research track exists for the topic, call get_research_context to retrieve existing memories and previously found papers.

  • Parameters: query (the research topic), user_id (default "default"), track_id (optional; pass if a specific track ID is known)
  • Returns: dict with papers (list), memories (list), stage (workflow stage string)
  • Use the existing memories as context when synthesizing results in Step 4
  • Skip this step if no prior research context exists for the topic
Step 2: Search for papers

Call paper_search with the topic. Use a broader corpus for trend analysis.

  • Parameters: query (required), max_results (use 20–50 for trend analysis — a larger corpus improves trend signal quality), sources (optional)
  • Returns: list of paper dicts with title, abstract, authors, year, venue
  • If track_id context was loaded in Step 1, merge the existing papers with new results (deduplicate by arxiv_id or doi)

Call analyze_trends with the topic and the list of papers from Step 2.

  • Parameters: topic (the research area string), papers (list of paper dicts from paper_search; pass the full list for best results)
  • Returns: dict with trend_analysis (natural language narrative), topic, paper_count
  • Check for degraded=True — analyze_trends requires a configured LLM API key
Show full SKILL.md (197 more words)Show less
Step 4: Save synthesis

Call save_to_memory with the trend analysis narrative and any additional observations.

  • Parameters: content (the trend_analysis text from Step 3, optionally enhanced with your own observations), kind ("note" for factual observations, "hypothesis" for directional predictions), user_id (default "default"), scope_type ("global" for broad field trends, "track" if scoping to a research area), scope_id (track ID if scope_type="track"), confidence (0.0–1.0)
  • Returns: dict with created or skipped status

Degraded Mode

analyze_trends requires a configured LLM API key. paper_search and get_research_context work without LLM.

When analyze_trends returns degraded=True:

  • The response also contains an error key describing the issue
  • Set OPENAI_API_KEY or ANTHROPIC_API_KEY and restart the MCP server
  • In degraded mode, present the raw search results grouped by year or venue as a manual trend signal; skip Step 3 or surface the paper list to the user directly

Notes

  • For fast trend snapshots, use max_results=20 and skip Step 1
  • For deep research landscape maps, use max_results=50 and integrate prior context from get_research_context
  • When analyzing sub-field trends (e.g., "sparse attention mechanisms"), narrow the query rather than broadening max_results
  • Multiple calls with different topic variants (e.g., "mixture of experts" vs. "sparse expert models") can be combined for a richer landscape view

© jerry609, 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 .claude/skills/trend-analysis of jerry609/PaperBot.

Open the folder on GitHubat commit 9030c5e

Compare with similar skills

Trend Analysis 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.

Trend Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Trend Analysis this skilljerry609/PaperBot108—~904Automated safety check: PassMIT
Literature Reviewneflibata-feng/MyArxiv-Agent12621 repos~5.9kAutomated safety check: NotesMIT
Paper Research on arXivXiaomiMiMo/MiMo-Code14k1 repos~1.5kAutomated safety check: PassMIT
Literature Review AgentAr9av/PaperOrchestra6772 repos~5.2kAutomated safety check: PassCustom licence
Systematic Literature Review Builderbytedance/deer-flow83k2 repos~4.3kAutomated safety check: PassMIT
Outline AgentAr9av/PaperOrchestra6772 repos~1.6kAutomated safety check: PassCustom licence

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Works with

Categories

Questions about Trend Analysis

What does Trend Analysis do?

This skill should be used when the user asks to "analyze trends in a research area", "what is trending in X", "research landscape for topic Y", "topic trend analysis", "emerging themes in machine…. Trend Analysis is an agent skill from jerry609/PaperBot. This skill should be used when the user asks to "analyze trends in a research area", "what is trending in X", "research landscape for topic Y", "topic trend analysis", "emerging themes in machine learning", "what are researchers working on in Z", or wants to survey a field and identify emerging patterns across multiple papers using PaperBot MCP tools.

When should I use Trend Analysis?

Trend Analysis fits situations like: asks to analyze trends in a research area; what is trending in X; research landscape for topic Y; topic trend analysis.

How do I install Trend Analysis in Claude Code?

Run `npx skills add jerry609/PaperBot --skill trend-analysis -a claude-code`. Or copy the skill folder (.claude/skills/trend-analysis in jerry609/PaperBot) into .claude/skills/trend-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Trend Analysis in Codex?

Run `npx skills add jerry609/PaperBot --skill trend-analysis -a codex`. Or copy the skill folder (.claude/skills/trend-analysis in jerry609/PaperBot) into .agents/skills/trend-analysis in your project. Codex loads it when a task matches its description.

Can I use Trend Analysis 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 jerry609/PaperBot --skill trend-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/trend-analysis, .gemini/skills/trend-analysis, .github/skills/trend-analysis and .opencode/skills/trend-analysis in your project.

What does Trend Analysis need to run?

Going by SKILL.md and its folder, Trend Analysis needs credentials named OPENAI_API_KEY and ANTHROPIC_API_KEY. Our summary lists: A credential in OPENAI_API_KEY; A credential in ANTHROPIC_API_KEY.

Does Trend Analysis 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 Trend Analysis 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 Trend Analysis use?

Trend Analysis 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 Trend Analysis use?

About 904 tokens (SKILL.md is roughly 3.6k 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 Trend Analysis?

Skills that share tags, products or a category with Trend Analysis: Literature Review (neflibata-feng/MyArxiv-Agent, 126 stars), Paper Research on arXiv (XiaomiMiMo/MiMo-Code, 14k stars), Literature Review Agent (Ar9av/PaperOrchestra, 677 stars) and Systematic Literature Review Builder (bytedance/deer-flow, 83k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Trend Analysis?

jerry609 (a GitHub user) maintains it in jerry609/PaperBot, which has 108 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on June 16, 2026.

Source: jerry609/PaperBot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.