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Agent skill

Deep Dive

by rohitg00 in rohitg00/awesome-claude-code-toolkit

Claude-native deep research using DAG-based query planning, parallel subagent execution, and gap-driven iteration.

Apache-2.0Auto-check: warningsResearch & Science

Install Deep Dive

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add rohitg00/awesome-claude-code-toolkit --skill deep-dive -a claude-code

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

GitHub CLI
$ gh skill install rohitg00/awesome-claude-code-toolkit deep-dive --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/rohitg00/awesome-claude-code-toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/deep-dive .claude/skills/deep-dive && 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-dive
GitHub stars
2.7k
Token cost
~1.5k tokens
SKILL.md length
655 words
Files
1
Skills in repo
38
Repo updated
First seen
Licence
Apache-2.0

At a glance

Claude-native deep research using DAG-based query planning, parallel subagent execution, and gap-driven iteration.

  • Works in 4 steps: Decompose into a DAG → Execute in dependency order → Gap iteration (max 1 round) → …
  • Tasks that involve Subagents
  • SKILL.md covers How it works, Steps and Rules
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Deep Dive is an agent skill from rohitg00/awesome-claude-code-toolkit. Claude-native deep research using DAG-based query planning, parallel subagent execution, and gap-driven iteration. No external API needed.

Its SKILL.md is about 1.5k 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 Subagents and Deep research. The repository describes itself as: The most comprehensive toolkit for Claude Code -- 135 agents, 35 curated skills, 42 commands, 176+ plugins, 20 hooks, 15 rules, 7 templates, 14 MCP configs, 26 companion apps, 52… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Subagents
  • Tasks that involve Deep research

Example prompts

  • “/deep-dive”

Workflow steps

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

  1. Decompose into a DAG
  2. Execute in dependency order
  3. Gap iteration (max 1 round)
  4. Synthesize

What it can do on your machine

Read from SKILL.md and the folder at commit ebdf1d5. 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 no API keys, tokens, secrets or passwords.

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

Context cost

Deep Dive loads about 1.5k tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 655 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~37
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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: warnings

The automated check found patterns that need a careful read before installing.

  • WarningTells the agent its actions are pre-authorized / not to stop for confirmationSKILL.md:36
    then immediately proceed to execution — do not wait for confirmation.

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 rohitg00/awesome-claude-code-toolkit at commit ebdf1d5, republished under its Apache-2.0 licence (© rohitg00). 655 words, ~1,525 tokens.

Download SKILL.mdSave it as .claude/skills/deep-dive/SKILL.md (or your agent's skills folder).
name
deep-dive
description
Claude-native deep research using DAG-based query planning, parallel subagent execution, and gap-driven iteration. No external API needed.
user-invocable
true
argument
The research question or topic to investigate deeply

Deep Dive

Autonomous deep research using the same DAG-based planning pattern as Google's Deep Research — but running entirely on Claude Code with no external dependencies.

How it works

  1. Plan — decompose the question into a DAG of sub-questions with dependencies
  2. Fan out — run independent sub-questions in parallel via Agent subagents
  3. Gap analysis — each subagent returns findings + identified gaps
  4. Iterate — gaps become new sub-questions, fed back into the DAG
  5. Synthesize — once all nodes complete, produce a final report

Steps

1. Decompose into a DAG

Given the research question, generate a DAG of sub-questions. Each node has:

  • id: short identifier (e.g., q1, q2a)
  • question: the specific sub-question to research
  • depends_on: list of node IDs whose answers are needed first (empty = no dependencies)

Rules for decomposition:

  • Start with foundational/context-setting questions that have no dependencies
  • Build toward analytical/comparative questions that depend on foundational answers
  • Aim for 4-8 nodes. If the topic needs more, cap at 12.
  • Each node should be answerable with 1-3 web searches
  • Questions should be specific enough that a researcher with no other context can answer them

Print the DAG as a table so the first brain can see the plan, then immediately proceed to execution — do not wait for confirmation.

Create a task for each DAG node using TaskCreate (description: the sub-question, status: pending). Also create tasks for "Gap analysis" and "Synthesize report". Update each task to in_progress when its wave launches and completed when the subagent returns. This gives the first brain real-time visibility into progress.

| ID | Question | Depends on |
|----|----------|------------|
| q1 | ...      | —          |
| q2 | ...      | —          |
| q3 | ...      | q1         |
| q4 | ...      | q1, q2     |
2. Execute in dependency order

Process the DAG in topological order:

Wave 1: Mark all Wave 1 node tasks as in_progress. Launch all nodes with no dependencies as parallel Agent subagents. As each subagent returns, mark its task completed. Each subagent gets this prompt:

You are a focused researcher. Answer this ONE question using web search:

Question: [the sub-question]

Instructions:
- Use WebSearch to find current, authoritative information
- Use 1-3 searches maximum
- Be specific and cite what you find

Return your answer in this exact format:

## Findings
[Your answer with specific facts, dates, numbers. Cite sources inline.]

## Gaps
[List anything you couldn't fully answer, contradictions you found, or
follow-up questions that would strengthen the answer. If none, say "None."]

## Sources
[List each source as: Title — URL]

Citation persistence: After each wave completes, append all sources from that wave to a file at /tmp/deep-dive-sources-[topic-slug].json as an array of {"node_id", "title", "url"} objects. This survives context compaction — if subagent results get compressed out of context, the sources file remains the source of truth. Read this file during synthesis to build the final Sources section.

Wave 2+: Once Wave 1 completes, mark all Wave 2+ node tasks as in_progress and launch nodes whose dependencies are now satisfied. Mark each task completed as its subagent returns. Include the findings from dependency nodes in the subagent prompt:

You are a focused researcher. Answer this ONE question using web search:

Question: [the sub-question]

Context from prior research:
[Paste findings from dependency nodes]

[same instructions as above]

Continue until all nodes complete.

Show full SKILL.md (259 more words)Show less
3. Gap iteration (max 1 round)

Mark the "Gap analysis" task as in_progress. After all nodes complete, review the collected gaps across all subagents:

  • If gaps are minor or don't affect the final answer: skip, move to synthesis
  • If any gap is significant enough to change the conclusion: create 1-3 new targeted sub-questions and run them as a final parallel wave

Only do ONE gap iteration round. This is not an infinite loop.

Mark the "Gap analysis" task as completed when done (whether gaps were found or skipped).

4. Synthesize

Mark the "Synthesize report" task as in_progress. Combine all findings into a final report. Mark it completed when the report file is written. Structure:

markdown
## Deep Dive: [Topic]

### Executive Summary
[3-5 sentences: the key takeaway]

### Findings

#### [Theme/Section 1]
[Synthesized findings from relevant nodes, not just copy-paste]

#### [Theme/Section 2]
[...]

### Open Questions
[Anything that couldn't be resolved — be honest about what's still unclear]

### Sources
[Deduplicated list of all sources from all subagents]

Rules

  • Always show the DAG plan first. Print it, then immediately start researching — no confirmation needed.
  • Parallel where possible. Independent questions should always run as concurrent subagents.
  • One gap round max. Don't spiral into infinite research loops.
  • Synthesize, don't concatenate. The final report should read as a coherent document, not a list of subagent outputs stapled together.
  • Be honest about confidence. If the research didn't produce clear answers, say so. Don't fill gaps with speculation.
  • Always persist the final report. After synthesis, save the report as a markdown file in the appropriate project's docs/deep-dive/ directory (create it if needed). Determine the project root from the current working directory or the context of the research request. Use a slugified topic name with date as the filename (e.g., 2026-04-02-jira-docs-from-microservices.md). Never write final reports only to /tmp — they must land in a durable location within the relevant project.

© rohitg00, Apache-2.0. 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-dive of rohitg00/awesome-claude-code-toolkit.

Open the folder on GitHubat commit ebdf1d5

Compare with similar skills

Deep Dive 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 Dive compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Deep Dive this skillrohitg00/awesome-claude-code-toolkit2.7k—~1.5kAutomated safety check: WarnApache-2.0
Web ResearchJuncai22/spring-ai-agent-learning1232 repos~1.1kAutomated safety check: PassApache-2.0
Deep Researchasgeirtj/system_prompts_leaks69k—~3.3kAutomated safety check: PassCC0-1.0
Deep Research312362115/claude107—~6.6kAutomated safety check: PassMIT
ULW Deep Researchcode-yeongyu/oh-my-openagent70k—~14kAutomated safety check: PassCustom licence
Deep ResearchXiaomiMiMo/MiMo-Code14k—~1.2kAutomated safety check: PassMIT

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  • Deep Research

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Categories

Questions about Deep Dive

What does Deep Dive do?

Claude-native deep research using DAG-based query planning, parallel subagent execution, and gap-driven iteration. Deep Dive is an agent skill from rohitg00/awesome-claude-code-toolkit. Claude-native deep research using DAG-based query planning, parallel subagent execution, and gap-driven iteration.

When should I use Deep Dive?

Deep Dive fits situations like: tasks that involve Subagents; tasks that involve Deep research.

How do I install Deep Dive in Claude Code?

Run `npx skills add rohitg00/awesome-claude-code-toolkit --skill deep-dive -a claude-code`. Or copy the skill folder (skills/deep-dive in rohitg00/awesome-claude-code-toolkit) into .claude/skills/deep-dive in your project. Claude Code loads it when a task matches its description.

How do I install Deep Dive in Codex?

Run `npx skills add rohitg00/awesome-claude-code-toolkit --skill deep-dive -a codex`. Or copy the skill folder (skills/deep-dive in rohitg00/awesome-claude-code-toolkit) into .agents/skills/deep-dive in your project. Codex loads it when a task matches its description.

Can I use Deep Dive 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 rohitg00/awesome-claude-code-toolkit --skill deep-dive -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-dive, .gemini/skills/deep-dive, .github/skills/deep-dive and .opencode/skills/deep-dive in your project.

What does Deep Dive need to run?

SKILL.md names no scripts, command-line tools or credentials: Deep Dive is instructions for the agent only.

Does Deep Dive 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 Dive safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): tells the agent its actions are pre-authorized / not to stop for confirmation. Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Deep Dive use?

Deep Dive is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deep Dive use?

About 1.5k tokens (SKILL.md is roughly 6.1k 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 Deep Dive?

Skills that share tags, products or a category with Deep Dive: Web Research (Juncai22/spring-ai-agent-learning, 123 stars), Deep Research (asgeirtj/system_prompts_leaks, 69k stars), Deep Research (312362115/claude, 107 stars) and ULW Deep Research (code-yeongyu/oh-my-openagent, 70k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deep Dive?

rohitg00 (a GitHub user) maintains it in rohitg00/awesome-claude-code-toolkit, which has 2,685 GitHub stars. The repository holds 38 skills in this directory. The repository was last updated on May 12, 2026.

Source: rohitg00/awesome-claude-code-toolkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.