Agent skill

Deep Research

by coreyhaines31 in coreyhaines31/makerskills

When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or…

MITAuto-check passedResearch & Science

Install Deep Research

skills CLI
$ npx skills add coreyhaines31/makerskills --skill deep-research -a claude-code

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

GitHub CLI
$ gh skill install coreyhaines31/makerskills deep-research --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/coreyhaines31/makerskills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/deep-research .claude/skills/deep-research && 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
deep-research
GitHub stars
851
Token cost
~1.4k tokens
SKILL.md length
536 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or…

  • Works in 7 steps: Frame the question → Plan the sources → Execute discovery → …
  • Do a deep dive on X
  • SKILL.md covers Step 1 — Frame the question, Step 2 — Plan the sources, Step 3 — Execute discovery and Step 4 — Synthesize, plus 5 more sections
  • Needs NOTION_API_KEY

What it does

Deep Research is an agent skill from coreyhaines31/makerskills. When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any "I need to actually understand X." Combines web search, URL fetch, agent-browser, last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives…

Its SKILL.md is about 1.4k 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, Web search and Browser automation. It works with Notion, Reddit and YouTube. The repository describes itself as: AI agent skills for the personal operator's craft — decisions, research, second-brain, content rotation, scenario modeling, and meta-skills to author more. Works with Claude… The licence is MIT.

When your agent uses it

  • Do a deep dive on X
  • Whats actually happening with X
  • Due diligence on X
  • Validate this market. Differs from a one-shot web search: this is multi-pass with verification

Example prompts

  • “I need to actually understand X.”
  • “/deep-research,”
  • “research X,”
  • “/deep-research”

Requirements

  • A credential in NOTION_API_KEY

Workflow steps

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

  1. Frame the question
  2. Plan the sources
  3. Execute discovery
  4. Synthesize
  5. Output the brief
  6. Archive
  7. Surface

What it can do on your machine

Read from SKILL.md and the folder at commit cc31579. 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 markdown).

    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:

    • NOTION_API_KEY

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

Context cost

Deep Research loads about 1.4k tokens when it runs. Until then it costs about 220 tokens; SKILL.md has 536 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~220
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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 coreyhaines31/makerskills at commit cc31579, republished under its MIT licence (© coreyhaines31). 536 words, ~1,414 tokens.

Download SKILL.mdSave it as .claude/skills/deep-research/SKILL.md (or your agent's skills folder).
name
deep-research
description
When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any "I need to actually understand X." Combines web search, URL fetch, agent-browser, last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on "/deep-research," "research X," "investigate X," "do a deep dive on X," "look into X," "what's actually happening with X," "due diligence on X," "validate this market." Differs from a one-shot web search: this is multi-pass with verification.
metadata.version
0.2.1

/deep-research — Multi-source research with archive

Plans, executes, and synthesizes research from multiple sources. Archives the output so the corpus compounds.

Step 1 — Frame the question

Restate the research question in one tight sentence. If ambiguous, ask the user:

  • What's the decision this research will inform?
  • What's the minimum useful answer? (Saves over-researching.)
  • Any sources to prioritize or avoid?

Output: **Research question:** <one sentence>

Step 2 — Plan the sources

Pick from this menu based on the question type. Note which sources you'll hit and why.

SourceWhen to useHow (tool names vary by agent)
Web search (Google)Authoritative articles, docs, official statementsYour agent's web search (e.g. WebSearch in Claude Code)
/last30daysWhat people are actually saying right now — Reddit, X, YouTube, HN, web recencyThe last30days skill, if installed. Otherwise skip it and note the gap
Specific URLsWhen the user hands over starting URLsYour agent's URL fetch (e.g. WebFetch), or curl + defuddle
Browsable pages (auth-walled, JS-heavy)Pricing pages, product tours, profilesagent-browser CLI (any agent with a shell)
MemoryPrior research / decisions / context the user already capturedyour agent's memory, or grep ${MAKERSKILLS_MEMORY:-${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/memory}/
NotionIf the topic touches a known Notion workspaceDirect Notion API (key in $NOTION_API_KEY, see reference_notion_api.md)
Research archivePrior /deep-research runs that touched this topicgrep ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/

Run discovery passes in parallel where possible. Sequential only when one source needs another's output (e.g., agent-browser a URL discovered by web search).

Step 3 — Execute discovery

Run each chosen source. For each result, capture:

  • The source (URL or system)
  • 1–3 sentence summary of what was said
  • Date / recency
  • Confidence in the source (high/medium/low)

Don't synthesize yet — just collect.

Step 4 — Synthesize

  1. Group findings by theme or sub-question
  2. Contradiction check — flag anywhere sources disagree. Don't average them; surface the disagreement.
  3. Confidence: high (multiple independent sources agree), medium (one strong source or several weak), low (single anecdote or speculation)
  4. Gaps: what would change the answer? What's NOT in the corpus?
Show full SKILL.md (209 more words)Show less

Step 5 — Output the brief

Use this template:

markdown
# Research: <question>

**Date:** <YYYY-MM-DD>
**Decision this informs:** <one line>
**Confidence overall:** high / medium / low

## TL;DR
<2–4 sentences with the answer>

## Key findings

### 1. <Finding>
<2–4 sentences>. Sources: [1], [3], [5]

### 2. <Finding>
...

## Contradictions / uncertainty
- <where sources disagree, with each side cited>

## Gaps
- <what's missing from the corpus>
- <what to research next to close the gap>

## Recommended next steps
1. <action>
2. <action>

## Sources
[1] <Title> — <URL or system> (<date>) — <confidence>
[2] ...

Step 6 — Archive

Archives live in ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/ (create the directory if missing). Never write archives inside the skill's own folder — skill installs and upgrades re-sync from source and wipe anything saved there. Migration: if this skill's folder contains an old references/research-archive/ with user entries, move those files into the archive directory first.

Write the brief to <archive dir>/<YYYY-MM-DD>-<slug>.md so it's grep-able forever. Slug = kebab-case of the topic.

Also append a one-line entry to <archive dir>/INDEX.md (create if missing):

markdown
- 2026-06-15 — [<topic>](./<filename>.md) — <one-line TL;DR>

Step 7 — Surface

After archiving:

  • Show the full brief in chat
  • Tell the user the archive path
  • Offer: "Push to Notion or save to a project's docs?"

Composes with

  • business-brainstorm — calls this skill during the market validation step
  • /domain — when research includes "is the .com available"
  • /last30days — one of the data sources

Notes on quality

  • Always cite. Every claim in the brief needs a source pointer.
  • Recency matters — note dates on each source. For fast-moving topics (AI, startups), de-weight sources >12 months old.
  • Don't trust a single source for high-stakes claims. Re-search until you have at least 2 independent corroborations or surface the uncertainty.
  • No padding. If the answer is one paragraph, return one paragraph. The template is a maximum, not a minimum.

© coreyhaines31, 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/deep-research of coreyhaines31/makerskills.

Open the folder on GitHubat commit cc31579

Compare with similar skills

Deep Research 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.

Deep Research compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Deep Research this skillcoreyhaines31/makerskills851—~1.4kAutomated safety check: PassMIT
Agent ReachPanniantong/Agent-Reach95k—~1.4kAutomated safety check: PassMIT
Ray Trend Searchimraywang/rayskills159—~2.1kAutomated safety check: PassCustom licence
Argo Search and Verificationtaxueseek/argo188—~1.2kAutomated safety check: PassMIT
Insane Searchfivetaku/gptaku-plugins-codex128—~5.6kAutomated safety check: PassMIT
Researcheralecs5am/ralphy138—~1.9kAutomated safety check: PassApache-2.0

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Questions about Deep Research

What does Deep Research do?

When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or…. Deep Research is an agent skill from coreyhaines31/makerskills." Combines web search, URL fetch, agent-browser, last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion.

When should I use Deep Research?

Deep Research fits situations like: do a deep dive on X; whats actually happening with X; due diligence on X; validate this market. Differs from a one-shot web search: this is multi-pass with verification.

How do I install Deep Research in Claude Code?

Run `npx skills add coreyhaines31/makerskills --skill deep-research -a claude-code`. Or copy the skill folder (skills/deep-research in coreyhaines31/makerskills) into .claude/skills/deep-research in your project. Claude Code loads it when a task matches its description.

How do I install Deep Research in Codex?

Run `npx skills add coreyhaines31/makerskills --skill deep-research -a codex`. Or copy the skill folder (skills/deep-research in coreyhaines31/makerskills) into .agents/skills/deep-research in your project. Codex loads it when a task matches its description.

Can I use Deep Research 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 coreyhaines31/makerskills --skill deep-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deep-research, .gemini/skills/deep-research, .github/skills/deep-research and .opencode/skills/deep-research in your project.

What does Deep Research need to run?

Going by SKILL.md and its folder, Deep Research needs credentials named NOTION_API_KEY. Our summary lists: A credential in NOTION_API_KEY.

Does Deep Research 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 Deep Research 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 Deep Research use?

Deep Research 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 Deep Research use?

About 1.4k tokens (SKILL.md is roughly 5.7k 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 Deep Research?

Skills that share tags, products or a category with Deep Research: Agent Reach (Panniantong/Agent-Reach, 95k stars), Ray Trend Search (imraywang/rayskills, 159 stars), Argo Search and Verification (taxueseek/argo, 188 stars) and Insane Search (fivetaku/gptaku-plugins-codex, 128 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deep Research?

coreyhaines31 (a GitHub user) maintains it in coreyhaines31/makerskills, which has 851 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on October 8, 2026.

Source: coreyhaines31/makerskills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.