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Agent skill

Research Deep

by Weizhena in Weizhena/Deep-Research-skills

Read research outline, launch independent agent for each item for deep research.

MITAuto-check: notesResearch & Science

Install Research Deep

skills CLI
$ npx skills add Weizhena/Deep-Research-skills --skill research-deep -a claude-code

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

GitHub CLI
$ gh skill install Weizhena/Deep-Research-skills research-deep --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/Weizhena/Deep-Research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research-en/research-deep .claude/skills/research-deep && 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
research-deep
GitHub stars
2.3k
Used in
3 other repos
Token cost
~850 tokens
SKILL.md length
184 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Read research outline, launch independent agent for each item for deep research.

  • Works in 5 steps: Auto-locate Outline → Resume Check → Batch Execution → …
  • Tasks that involve Deep research
  • SKILL.md covers Trigger, Workflow and Agent Config
  • Calls python

What it does

Research Deep is an agent skill from Weizhena/Deep-Research-skills. Read research outline, launch independent agent for each item for deep research. Disable task output.

Its SKILL.md is about 850 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: Structured deep research skill for Claude Code/Open Code/Codex with human-in-the-loop control. The licence is MIT.

When your agent uses it

  • Tasks that involve Deep research

Example prompts

  • “/research-deep”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Bash, Read, Write, Glob, WebSearch, Task

Workflow steps

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

  1. Auto-locate Outline
  2. Resume Check
  3. Batch Execution
  4. Wait and Monitor
  5. Summary Report

What it can do on your machine

Read from SKILL.md and the folder at commit 6ce38f6. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read
    • Write
    • Glob
    • WebSearch
    • Task

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python

    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 Deep loads about 850 tokens when it runs. Until then it costs about 29 tokens; SKILL.md has 184 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~29
When it runs · the whole SKILL.md, loaded when a task matches
~850

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read, Write, Glob, WebSearch, Task

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 Weizhena/Deep-Research-skills at commit 6ce38f6, republished under its MIT licence (© Weizhena). 184 words, ~850 tokens.

Download SKILL.mdSave it as .claude/skills/research-deep/SKILL.md (or your agent's skills folder).
name
research-deep
description
Read research outline, launch independent agent for each item for deep research. Disable task output.
allowed-tools
Bash, Read, Write, Glob, WebSearch, Task
user-invocable
true

Research Deep - Deep Research

Trigger

/research-deep

Workflow

Step 1: Auto-locate Outline

Find */outline.yaml file in current working directory, read items list, execution config (including items_per_agent).

Step 2: Resume Check
  • Check completed JSON files in output_dir
  • Skip completed items
Step 3: Batch Execution
  • Batch by batch_size (need user approval before next batch)
  • Each agent handles items_per_agent items
  • Launch web-search-agent (background parallel, disable task output)

Parameter Retrieval:

  • {topic}: topic field from outline.yaml
  • {item_name}: item's name field
  • {item_related_info}: item's complete yaml content (name + category + description etc.)
  • {output_dir}: execution.output_dir from outline.yaml (default: ./results)
  • {fields_path}: absolute path to {topic}/fields.yaml
  • {output_path}: absolute path to {output_dir}/{item_name_slug}.json (slugify item_name: replace spaces with _, remove special chars)

Hard Constraint: The following prompt must be strictly reproduced, only replacing variables in {xxx}, do not modify structure or wording.

Prompt Template:

python
prompt = f"""## Task
Research {item_related_info}, output structured JSON to {output_path}

## Field Definitions
Read {fields_path} to get all field definitions

## Output Requirements
1. Output JSON according to fields defined in fields.yaml
2. Mark uncertain field values with [uncertain]
3. Add uncertain array at the end of JSON, listing all uncertain field names
4. All field values must be in English

## Output Path
{output_path}

## Validation
After completing JSON output, run validation script to ensure complete field coverage:
python ~/.claude/skills/research/validate_json.py -f {fields_path} -j {output_path}
Task is complete only after validation passes.
"""

One-shot Example (assuming researching GitHub Copilot):

## Task
Research name: GitHub Copilot
category: International Product
description: Developed by Microsoft/GitHub, first mainstream AI coding assistant, ~40% market share, output structured JSON to {project_dir}/results/GitHub_Copilot.json

## Field Definitions
Read {project_dir}/fields.yaml to get all field definitions

## Output Requirements
1. Output JSON according to fields defined in fields.yaml
2. Mark uncertain field values with [uncertain]
3. Add uncertain array at the end of JSON, listing all uncertain field names
4. All field values must be in English

## Output Path
{project_dir}/results/GitHub_Copilot.json

## Validation
After completing JSON output, run validation script to ensure complete field coverage:
python ~/.claude/skills/research/validate_json.py -f {project_dir}/fields.yaml -j {project_dir}/results/GitHub_Copilot.json
Task is complete only after validation passes.
Step 4: Wait and Monitor
  • Wait for current batch to complete
  • Launch next batch
  • Display progress
Step 5: Summary Report

After all complete, output:

  • Completion count
  • Failed/uncertain marked items
  • Output directory

Agent Config

  • Background execution: Yes
  • Task Output: Disabled (agent has explicit output file when complete)
  • Resume support: Yes

© Weizhena, 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-en/research-deep of Weizhena/Deep-Research-skills.

Open the folder on GitHubat commit 6ce38f6

Used in 3 other repositories

We found 13 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in Weizhena/Deep-Research-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Research Deep 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.

Research Deep compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research Deep this skillWeizhena/Deep-Research-skills2.3k3 repos~850Automated safety check: NotesMIT
GitHub Deep Researchbytedance/deer-flow83k5 repos~1.3kAutomated safety check: PassMIT
Deep Research WorkflowTokenRhythm/opensquilla7.1k—~1.3kAutomated safety check: PassApache-2.0
X Researchrohunvora/x-research-skill1.2k1 repos~1.6kAutomated safety check: PassNone
Deep Researchsanjay3290/ai-skills43110 repos~683Automated safety check: NotesApache-2.0
Horizontal-Vertical Deep ResearchKKKKhazix/khazix-skills21k—~2.1kAutomated safety check: PassMIT

Similar skills

  • GitHub Deep Research

    bytedance/deer-flow

    Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.

    83k GitHub starsUsed in 5 repos~1.3k tokens
    Research & ScienceAuto-check passed

  • Deep Research Workflow

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    Runs multi-round research in three stages with a persisted state file, evidence tracking and a long-form report with per-claim citations.

    7.1k GitHub stars~1.3k tokensUpdated 4 days ago
    Research & ScienceAuto-check passed

  • X Research

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    General-purpose X/Twitter research agent. An agent skill from rohunvora/x-research-skill.

    1.2k GitHub starsUsed in 1 repo~1.6k tokens
    Research & ScienceAuto-check passed

  • Deep Research

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    431 GitHub starsUsed in 10 repos~683 tokens
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  • Horizontal-Vertical Deep Research

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    Runs a two-axis deep research method on a product, company, concept or person: its full history over time, compared with peers today, delivered as a typeset PDF report.

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  • Academic Research Pipeline

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More from Weizhena/Deep-Research-skills

All 10 skills in this repo

  • Research

    Weizhena/Deep-Research-skills

    Conduct preliminary research on a topic and generate research outline.

    2.3k GitHub starsUsed in 3 repos~1.1k tokens
    Auto-check passed

  • Research Report

    Weizhena/Deep-Research-skills

    Summarize deep research results into markdown report, cover all fields, skip uncertain values.

    2.3k GitHub starsUsed in 3 repos~963 tokens
    Auto-check: notes

  • Research

    Weizhena/Deep-Research-skills

    对目标话题进行初步调研，生成调研outline。用于学术调研、benchmark调研、技术选型等场景. An agent skill from Weizhena/Deep-Research-skills.

    2.3k GitHub starsUsed in 2 repos~603 tokens
    Auto-check passed

  • Research Deep

    Weizhena/Deep-Research-skills

    读取调研outline，为每个item启动独立agent进行深度调研。禁用task output. An agent skill from Weizhena/Deep-Research-skills.

    2.3k GitHub starsUsed in 2 repos~521 tokens
    Auto-check: notes

  • Research Add Fields

    Weizhena/Deep-Research-skills

    Add field definitions to existing research outline. An agent skill from Weizhena/Deep-Research-skills.

    2.3k GitHub starsUsed in 3 repos~238 tokens
    Auto-check: notes

  • Research Add Items

    Weizhena/Deep-Research-skills

    Add items (research objects) to existing research outline. An agent skill from Weizhena/Deep-Research-skills.

    2.3k GitHub starsUsed in 3 repos~204 tokens
    Auto-check: notes

Categories

Questions about Research Deep

What does Research Deep do?

Read research outline, launch independent agent for each item for deep research. Research Deep is an agent skill from Weizhena/Deep-Research-skills. Read research outline, launch independent agent for each item for deep research.

When should I use Research Deep?

Research Deep fits situations like: tasks that involve Deep research.

How do I install Research Deep in Claude Code?

Run `npx skills add Weizhena/Deep-Research-skills --skill research-deep -a claude-code`. Or copy the skill folder (skills/research-en/research-deep in Weizhena/Deep-Research-skills) into .claude/skills/research-deep in your project. Claude Code loads it when a task matches its description.

How do I install Research Deep in Codex?

Run `npx skills add Weizhena/Deep-Research-skills --skill research-deep -a codex`. Or copy the skill folder (skills/research-en/research-deep in Weizhena/Deep-Research-skills) into .agents/skills/research-deep in your project. Codex loads it when a task matches its description.

Can I use Research Deep 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 Weizhena/Deep-Research-skills --skill research-deep -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-deep, .gemini/skills/research-deep, .github/skills/research-deep and .opencode/skills/research-deep in your project.

What does Research Deep need to run?

Going by SKILL.md and its folder, Research Deep needs the command-line tools its instructions call (python). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash, Read, Write, Glob, WebSearch, Task.

Does Research Deep 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 Deep safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Research Deep use?

Research Deep 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 Deep use?

About 850 tokens (SKILL.md is roughly 3.4k 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 Deep?

Skills that share tags, products or a category with Research Deep: GitHub Deep Research (bytedance/deer-flow, 83k stars), Deep Research Workflow (TokenRhythm/opensquilla, 7.1k stars), X Research (rohunvora/x-research-skill, 1.2k stars) and Deep Research (sanjay3290/ai-skills, 431 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research Deep?

Weizhena (a GitHub user) maintains it in Weizhena/Deep-Research-skills, which has 2,312 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on August 23, 2026.

Source: Weizhena/Deep-Research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.