deep-research
This skill enables deep research by integrating the hyperresearch CLI into Claude Code or OpenAI Codex projects.
Community author
- Agents
- Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode, claude.ai and API
- License
- MIT (permissive)
- Pin
- 7790041pinned Oct 9, 2026
- Context cost
- about 1,000 tokenswhen the skill loads
- GitHub stars
- 3,806on jordan-gibbs/hyperresearch
- Scripts
- None found
What it does
“Deep research with hyperresearch, for Claude Code and OpenAI Codex. Use when the user asks for deep research, a research report, a literature review, or a multi-source analysis with verified citations. Checks that the hyperresearch CLI is installed, sets it up in the current project for the agent you are running in, then hands off to the hyperresearch pipeline (a tier-adaptive 16-step pipeline with a persistent source vault). Not for quick lookups one or two searches can answer.”
Generated summary from the skill's own text
This skill enables deep research by integrating the hyperresearch CLI into Claude Code or OpenAI Codex projects. It runs a 16-step research pipeline with source verification and persistent citation management, designed for comprehensive multi-source analysis rather than quick searches.
When to use it
- User requests a deep research report or literature review
- Multi-source analysis with verified citations needed
- Comprehensive investigation of a complex topic required
- Research project requiring persistent source vault management
When not to
- Quick factual lookup or single-source answer suffices
- hyperresearch CLI not installed and unavailable to install
- Sandboxed read-only environment without network access
Install
These commands install from the publisher's repository and need no account.
skills CLI
npx skills add jordan-gibbs/hyperresearch --skill deep-researchInstalls from the repository's default branch, which may have changed since the commit we checked.
GitHub CLI 2.90 or later
gh skill install jordan-gibbs/hyperresearch deep-research@7790041c8705568effea2b018048160c89f848f4Installs the commit we checked (7790041).
Copy by hand
Download the folder at 7790041 and put it in .claude/skills/deep-research for Claude Code and in .agents/skills/deep-research for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.
Copy for your agent
A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.
Prompt
Install the agent skill "deep-research" by jordan-gibbs. Source, pinned to commit 7790041c8705568effea2b018048160c89f848f4: https://github.com/jordan-gibbs/hyperresearch/tree/7790041c8705568effea2b018048160c89f848f4/skills/deep-research 1. Download that folder at exactly this commit. Do not use the default branch. 2. Copy every file unchanged, keeping the folder structure, into .claude/skills/deep-research/ for Claude Code and .agents/skills/deep-research/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist. 3. Do not edit the files, and do not run any script in the folder unless I ask you to. 4. When you are done, list the files you copied and where you put them. Listing and checks: https://www.agentnative.dev/skills/jordan-gibbs/deep-research
SKILL.md at the pin
--- name: deep-research description: Deep research with hyperresearch, for Claude Code and OpenAI Codex. Use when the user asks for deep research, a research report, a literature review, or a multi-source analysis with verified citations. Checks that the hyperresearch CLI is installed, sets it up in the current project for the agent you are running in, then hands off to the hyperresearch pipeline (a tier-adaptive 16-step pipeline with a persistent source vault). Not for quick lookups one or two searches can answer. license: MIT compatibility: Requires Python 3.11+ and the hyperresearch CLI (pip install hyperresearch), plus network access for fetching sources. Works in Claude Code and OpenAI Codex CLI; under Codex the session needs a writable workspace with network enabled. --- # Deep research with hyperresearch This skill is a bootstrap. The research pipeline itself is an entry skill plus 16 step procedures and a set of subagents, which the `hyperresearch` Python package renders and installs into the project. This file does not contain the pipeline. Do not try to run the research from here, and do not answer the research question from your own knowledge: the pipeline is the deliverable. ## 1. Check the CLI Run: ```bash hyperresearch --version ``` If the command is not found, stop and tell the user: > hyperresearch is not installed. Install it with `pip install hyperresearch` > (Python 3.11 to 3.14), then ask again. You may run `pip install hyperresearch` yourself only if the user says to. ## 2. Pick your branch You know which agent you are. Follow exactly one branch. - **Claude Code** (you have `Skill` and `Task` tools): section 3A. - **OpenAI Codex** (you edit files with `apply_patch`, spawn custom agents, and skills are invoked as `$name`): section 3B. If you genuinely cannot tell, look at the working directory: a `.codex/` or `.agents/` directory and no `.claude/` means Codex; the reverse means Claude Code. Still unsure: ask the user which one they are using. ## 3A. Claude Code If `.claude/skills/hyperresearch/SKILL.md` does not exist in the working directory, run: ```bash hyperresearch install . --json ``` This creates the vault (`.hyperresearch/`, `research/`), adds a short block to `CLAUDE.md`, and installs the entry skill, the 16 step skills, the subagents and a PreToolUse hook under `.claude/`. It is safe to re-run; it no-ops on files that are already current. Tell the user in one line what was installed. Then invoke the installed router with the user's research request, verbatim: ``` Skill(skill: "hyperresearch", args: "<the user's research request>") ``` From then on, follow the `hyperresearch` skill. It owns the query, the tier choice, and every step. If the `hyperresearch` skill is not available yet (Claude Code loads new subagents at session start, and some versions do the same for skills), tell the user that setup is done and ask them to restart Claude Code in this directory and run: ``` /hyperresearch <their research request> ``` ## 3B. OpenAI Codex If `.agents/skills/hyperresearch/SKILL.md` does not exist in the working directory, run: ```bash hyperresearch install . --target codex --json ``` This creates the vault (`.hyperresearch/`, `research/`), adds a short block to `AGENTS.md`, and installs the entry skill at `.agents/skills/hyperresearch/`, the step procedures under `.hyperresearch/codex/steps/`, the custom agents under `.codex/agents/`, and a Stop hook in `.codex/hooks.json`. It is safe to re-run. Tell the user in one line what was installed. If the install (or any later `hyperresearch fetch`) fails with a permission or network error, the session is sandboxed read-only or offline. Stop and tell the user to restart Codex with a writable workspace and network access, for example: ```bash codex --sandbox workspace-write -c sandbox_workspace_write.network_access=true ``` Then hand off. Codex discovers skills when a session starts, so a skill installed a moment ago may not be listed yet. The robust path is to read the entry skill directly and follow it: 1. Read `.agents/skills/hyperresearch/SKILL.md` in full (for example `cat .agents/skills/hyperresearch/SKILL.md`). 2. Follow it with the user's research request, verbatim, as the query. It is the same procedure `$hyperresearch <request>` would load. It owns the query, the tier choice, and every step, and each step tells you which procedure file under `.hyperresearch/codex/steps/` to read next. If `$hyperresearch` already appears in your skill list, invoking it with the request is equivalent. In later sessions the user can start a run directly with `$hyperresearch <question>`. Two things differ from Claude Code, and the entry skill covers both: there is no browser lane (blocked fetches stay queued and are listed for the user at the end), and the Stop hook, once Codex trusts the project's hooks, will not let the session finish while a run is mid-pipeline.
From jordan-gibbs/hyperresearch at 7790041, shown as plain text under its license: MIT (permissive). The license text is in skills/deep-research/SKILL.md.
View SKILL.md on GitHub at 7790041Files
- SKILL.md5.0 KB · dcb993145238
- agents/
- openai.yaml309 B · 5018e2140e02
2 files, 5.3 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.
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