Agent skill

Open Researcher Guide

by wentorai in wentorai/research-plugins

Open pipeline for generating deep research trajectories with LLMs

MITAuto-check passedResearch & Science

Install Open Researcher Guide

skills CLI
$ npx skills add wentorai/research-plugins --skill open-researcher-guide -a claude-code

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

GitHub CLI
$ gh skill install wentorai/research-plugins open-researcher-guide --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/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research/deep-research/open-researcher-guide .claude/skills/open-researcher-guide && 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
open-researcher-guide
GitHub stars
298
Used in
1 other repo
Token cost
~1k tokens
SKILL.md length
109 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Open pipeline for generating deep research trajectories with LLMs

  • Works in 4 steps: Question Decomposition → Iterative Search and Reading → Knowledge Graph Building → …
  • Tasks that involve Deep research
  • SKILL.md covers Overview, Pipeline Stages, Configuration and Trajectory Inspection, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Open Researcher Guide is an agent skill from wentorai/research-plugins. Open pipeline for generating deep research trajectories with LLMs

Its SKILL.md is about 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. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Deep research

Example prompts

  • “/open-researcher-guide”

Requirements

  • Python 3

Workflow steps

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

  1. Question Decomposition
  2. Iterative Search and Reading
  3. Knowledge Graph Building
  4. Synthesis and Report

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. 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 (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    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

Open Researcher Guide loads about 1k tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 109 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~22
When it runs · the whole SKILL.md, loaded when a task matches
~1k

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 wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 109 words, ~1,013 tokens.

Download SKILL.mdSave it as .claude/skills/open-researcher-guide/SKILL.md (or your agent's skills folder).
name
open-researcher-guide
description
Open pipeline for generating deep research trajectories with LLMs

OpenResearcher Guide

Overview

OpenResearcher is a fully open pipeline for long-horizon deep research trajectory synthesis. It breaks complex research questions into sub-questions, iteratively searches and reads literature, builds internal knowledge representations, and synthesizes comprehensive answers. Unlike single-shot approaches, it models the researcher's thought process — reading, questioning, connecting, and refining understanding over multiple rounds.

Pipeline Stages

1. Question Decomposition
python
from open_researcher import OpenResearcher

researcher = OpenResearcher(llm_provider="anthropic")

# Complex research question
result = researcher.research(
    "How do retrieval-augmented generation systems handle "
    "knowledge conflicts between parametric and retrieved knowledge, "
    "and what are the current mitigation strategies?"
)

# Automatically decomposes into sub-questions:
# SQ1: What types of knowledge conflicts occur in RAG?
# SQ2: How are conflicts detected?
# SQ3: What resolution strategies exist?
# SQ4: How effective are these strategies?
2. Iterative Search and Reading
python
# Each sub-question triggers:
# - Academic search (OpenAlex, arXiv)
# - Paper reading (abstract + key sections)
# - Evidence extraction
# - Follow-up question generation

# Configuration
researcher = OpenResearcher(
    search_backends=["openalex", "arxiv"],
    max_iterations=5,           # Research rounds per sub-question
    papers_per_iteration=10,    # Papers to read per round
    follow_up_questions=True,   # Generate follow-up questions
)
3. Knowledge Graph Building
python
# Internally builds a knowledge representation:
# - Claims linked to source papers
# - Relationships between concepts
# - Contradictions flagged

# Access the knowledge graph
kg = result.knowledge_graph
print(f"Concepts: {len(kg.nodes)}")
print(f"Relations: {len(kg.edges)}")
print(f"Contradictions: {len(kg.contradictions)}")
4. Synthesis and Report
python
# Multi-section synthesis
report = result.report

# Sections:
# 1. Introduction and scope
# 2. Sub-question answers with evidence
# 3. Cross-cutting themes
# 4. Open questions and future directions
# 5. Full bibliography

report.save("research_report.md")
report.export_bibliography("refs.bib")

Configuration

python
researcher = OpenResearcher(
    llm_provider="anthropic",
    model="claude-sonnet-4-20250514",
    search_config={
        "backends": ["openalex", "arxiv"],
        "max_results_per_query": 20,
    },
    reading_config={
        "sections": ["abstract", "introduction", "methods", "conclusion"],
        "max_tokens_per_paper": 3000,
    },
    synthesis_config={
        "style": "academic",           # academic, technical, accessible
        "include_contradictions": True,
        "cite_inline": True,
    },
)

Trajectory Inspection

python
# Inspect the research trajectory
trajectory = result.trajectory

for step in trajectory:
    print(f"Round {step.round}: {step.action}")
    print(f"  Query: {step.query}")
    print(f"  Papers read: {step.papers_read}")
    print(f"  Key findings: {step.findings[:100]}...")
    print(f"  Follow-ups: {step.follow_up_questions}")

Use Cases

  1. Literature surveys: Comprehensive multi-round research
  2. Research proposals: Evidence gathering for grant applications
  3. State-of-the-art reports: Current landscape analysis
  4. Tutorial generation: Deep topic explanations with citations

References

© wentorai, 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 skills/research/deep-research/open-researcher-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Open Researcher Guide 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.

Open Researcher Guide compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Open Researcher Guide this skillwentorai/research-plugins2981 repos~1kAutomated safety check: PassMIT
GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
Deep Research WorkflowTokenRhythm/opensquilla7.1k—~1.3kAutomated safety check: PassApache-2.0
Deep Researchsanjay3290/ai-skills4329 repos~683Automated safety check: NotesApache-2.0
Horizontal-Vertical Deep ResearchKKKKhazix/khazix-skills21k—~2.1kAutomated safety check: PassMIT
Academic Research PipelineImbad0202/academic-research-skills51k—~15kAutomated safety check: PassCustom licence

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Questions about Open Researcher Guide

What does Open Researcher Guide do?

Open pipeline for generating deep research trajectories with LLMs. Open Researcher Guide is an agent skill from wentorai/research-plugins.

When should I use Open Researcher Guide?

Open Researcher Guide fits situations like: tasks that involve Deep research.

How do I install Open Researcher Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill open-researcher-guide -a claude-code`. Or copy the skill folder (skills/research/deep-research/open-researcher-guide in wentorai/research-plugins) into .claude/skills/open-researcher-guide in your project. Claude Code loads it when a task matches its description.

How do I install Open Researcher Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill open-researcher-guide -a codex`. Or copy the skill folder (skills/research/deep-research/open-researcher-guide in wentorai/research-plugins) into .agents/skills/open-researcher-guide in your project. Codex loads it when a task matches its description.

Can I use Open Researcher Guide 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 wentorai/research-plugins --skill open-researcher-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/open-researcher-guide, .gemini/skills/open-researcher-guide, .github/skills/open-researcher-guide and .opencode/skills/open-researcher-guide in your project.

What does Open Researcher Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: Open Researcher Guide is instructions for the agent only. Our summary lists: Python 3.

Does Open Researcher Guide access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Open Researcher Guide 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 Open Researcher Guide use?

Open Researcher Guide 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 Open Researcher Guide use?

About 1k tokens (SKILL.md is roughly 4.1k 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 Open Researcher Guide?

Skills that share tags, products or a category with Open Researcher Guide: GitHub Deep Research (bytedance/deer-flow, 84k stars), Deep Research Workflow (TokenRhythm/opensquilla, 7.1k stars), Deep Research (sanjay3290/ai-skills, 432 stars) and Horizontal-Vertical Deep Research (KKKKhazix/khazix-skills, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Open Researcher Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

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