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This skill collection guides structured research from outline to report. It generates an item and field framework, launches independent agents to research each item in parallel, then compiles a markdown report that covers all fields while marking uncertain values. The pipeline serves market analysts, product managers, and academic researchers who need systematic benchmarks, competitive analysis, or literature surveys with built-in human oversight at each stage.
Compatible AgentsThe repository documents support for these agents. The skills may also work with other agents that can load SKILL.md files, but they may need some setup or small changes.
Installs: Installs the complete English research-en skill bundle, enables OpenCode web search for the current shell, and installs the required OpenCode web-search agent and modules. · OpenCode
Before you start
Git
Python with pip
A shell that supports export
The destination directories ~/.claude/skills/ and ~/.config/opencode/agents/ must exist.
Run from: Clone from the desired parent directory; run all subsequent steps from the deep-research-skills repository root in the same terminal.
In the directory where the repository should be created, clone it and enter the repository.
git clone https://github.com/Weizhena/deep-research-skills.git
cd deep-research-skills
Install the complete English skill bundle using the documented OpenCode destination.
cp -r skills/research-en/* ~/.claude/skills/ # or research-zh for Chinese
Enable web search for the current shell. The README states this is required for websearch in OpenCode.
export OPENCODE_ENABLE_EXA=1
Install the required OpenCode web-search agent and modules.
Installs: Installs the complete Chinese research-zh skill bundle, enables OpenCode web search for the current shell, and installs the required OpenCode web-search agent and modules. · OpenCode
Before you start
Git
Python with pip
A shell that supports export
The destination directories ~/.claude/skills/ and ~/.config/opencode/agents/ must exist.
Run from: Clone from the desired parent directory; run all subsequent steps from the deep-research-skills repository root in the same terminal.
In the directory where the repository should be created, clone it and enter the repository.
git clone https://github.com/Weizhena/deep-research-skills.git
cd deep-research-skills
Install the complete Chinese skill bundle using the documented OpenCode destination.
Codex — English bundle with automatic configuration
Installs: Installs the complete English research-codex-en skill bundle and required Codex web-researcher components, then configures Codex using the repository script. · Codex
Before you start
Git
Bash
Python 3 for the configuration script
Python with pip
Run from: Clone from the desired parent directory; run all subsequent steps from the deep-research-skills repository root in the same terminal.
In the directory where the repository should be created, clone it and enter the repository.
git clone https://github.com/Weizhena/deep-research-skills.git
cd deep-research-skills
Create the Codex skill and agent directories and install the complete English bundle.
Codex — Chinese bundle with automatic configuration
Installs: Installs the complete Chinese research-codex-zh skill bundle and required Codex web-researcher components, then configures Codex using the repository script. · Codex
Before you start
Git
Bash
Python 3 for the configuration script
Python with pip
Run from: Clone from the desired parent directory; run all subsequent steps from the deep-research-skills repository root in the same terminal.
In the directory where the repository should be created, clone it and enter the repository.
git clone https://github.com/Weizhena/deep-research-skills.git
cd deep-research-skills
Create the Codex skill and agent directories and install the complete Chinese bundle.
[PROJECT]: project directory beneath the current working directory
[ITEM NAMES]: one or more specific research objects to add
An existing [PROJECT]/outline.yaml file
Check the repository for this skill’s setup.
Use the research-add-items skill in the current working directory containing [PROJECT]/outline.yaml. Add [ITEM NAMES] as research objects, avoid duplicates, and show the proposed update for confirmation before saving it.
[PROJECT]: project directory beneath the current working directory
[FIELD NAMES AND DESCRIPTIONS]: the fields to consider adding
An existing [PROJECT]/fields.yaml file
Check the repository for this skill’s setup.
Use the research-add-fields skill in the current working directory containing [PROJECT]/fields.yaml. Propose fields from [FIELD NAMES AND DESCRIPTIONS], let me choose their categories and detail_level values, show the proposed additions for confirmation, and then save the confirmed fields.