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.
GOD MODE deep research skill. An agent skill from shobcoder/shob.
Install Deep Research
$ npx skills add shobcoder/shob --skill deep-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install shobcoder/shob deep-research --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/shobcoder/shob.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research-knowledge .claude/skills/deep-research && rm -rf skills-srcUse ~/.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/
Install the "deep-research" agent skill from https://github.com/shobcoder/shob/tree/main/skills/research-knowledge into .claude/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/shobcoder/shob/tree/main/skills/research-knowledgeType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add shobcoder/shob --skill deep-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install shobcoder/shob deep-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shobcoder/shob.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/research-knowledge .agents/skills/deep-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "deep-research" agent skill from https://github.com/shobcoder/shob/tree/main/skills/research-knowledge into .agents/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add shobcoder/shob --skill deep-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install shobcoder/shob deep-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shobcoder/shob.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/research-knowledge .cursor/skills/deep-research && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "deep-research" agent skill from https://github.com/shobcoder/shob/tree/main/skills/research-knowledge into .cursor/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/shobcoder/shob.git --path skills/research-knowledge--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add shobcoder/shob --skill deep-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install shobcoder/shob deep-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shobcoder/shob.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/research-knowledge .gemini/skills/deep-research && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "deep-research" agent skill from https://github.com/shobcoder/shob/tree/main/skills/research-knowledge into .gemini/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install shobcoder/shob deep-researchInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add shobcoder/shob --skill deep-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/shobcoder/shob.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/research-knowledge .github/skills/deep-research && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "deep-research" agent skill from https://github.com/shobcoder/shob/tree/main/skills/research-knowledge into .github/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add shobcoder/shob --skill deep-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install shobcoder/shob deep-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shobcoder/shob.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/research-knowledge .opencode/skills/deep-research && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "deep-research" agent skill from https://github.com/shobcoder/shob/tree/main/skills/research-knowledge into .opencode/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
deep-research- GitHub stars
- 577
- Token cost
- ~2.1k tokens
- SKILL.md length
- 625 words
- Files
- 1
- Skills in repo
- 6
- Repo updated
- First seen
- Licence
- MIT
At a glance
GOD MODE deep research skill. An agent skill from shobcoder/shob.
- Works in 6 steps: Query Decomposition → Multi-Source Search Strategy → Deep Crawl and Extraction → …
- Any question that demands depth
- SKILL.md covers Trigger, Core Philosophy, Architecture and Phase 1 — Query Decomposition, plus 10 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Deep Research is an agent skill from shobcoder/shob. GOD MODE deep research skill. Multi-phase autonomous research loop: query decomposition → multi-source crawling → claim cross-referencing → conflict resolution → structured synthesis with inline citations. Use for any question that demands depth, sourcing, and verifiable accuracy.
Its SKILL.md is about 2.1k 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: Shob – an AI agent that delivers high-quality coding & automation work. The licence is MIT.
When your agent uses it
- Any question that demands depth
- Verifiable accuracy
Example prompts
- “/deep-research”
Workflow steps
6 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 14831ba. 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 yaml and 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 Research loads about 2.1k tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 625 words of instructions outside code blocks.
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 shobcoder/shob at commit 14831ba, republished under its MIT licence (© shobcoder). 625 words, ~2,117 tokens.
Download SKILL.mdSave it as
.claude/skills/deep-research/SKILL.md (or your agent's skills folder).- name
- deep-research
- description
- GOD MODE deep research skill. Multi-phase autonomous research loop: query decomposition → multi-source crawling → claim cross-referencing → conflict resolution → structured synthesis with inline citations. Use for any question that demands depth, sourcing, and verifiable accuracy.
- user-invocable
- true
Deep Research — GOD MODE
Trigger
/deep-research <query> or when user says "research this deeply", "go deep on",
"full research report on", "investigate this thoroughly".
Core Philosophy
Raw search results are noise. Verified synthesis is signal. Every claim needs a source. Every conflict needs a resolution. A great deep research report is a structured intelligence brief, not a search summary.
Architecture
Query
└── Phase 1: Decompose → Sub-questions
└── Phase 2: Parallel Search → Raw Sources
└── Phase 3: Crawl & Extract → Claims
└── Phase 4: Cross-Reference → Verify / Conflict
└── Phase 5: Synthesize → Report
└── Phase 6: Quality Gates → DeliverPhase 1 — Query Decomposition
Break the user's query into 3–7 atomic sub-questions. Each must be:
- Independently searchable
- Non-overlapping with others
- Ordered from foundational to advanced
Example:
Query: "Is Company X profitable?"
Sub-questions:
- What is Company X's current revenue model?
- What are its reported ARR and revenue figures?
- What is its burn rate and cost structure?
- What do investors say about its path to profitability?
- How does it compare to competitors on unit economics?
Phase 2 — Multi-Source Search Strategy
For each sub-question, issue 2–4 targeted searches using varied query angles:
[primary term] [year]
[primary term] site:official OR filetype:pdf
[primary term] analysis OR breakdown OR report
[primary term] vs [competitor]Source Priority Tiers:
| Tier | Type | Trust Weight |
|---|---|---|
| 1 | Official docs, SEC filings, company blogs, government data, peer-reviewed papers | 1.0 |
| 2 | Major news outlets (Reuters, Bloomberg, FT), industry analysts (Gartner, CB Insights) | 0.85 |
| 3 | Tech blogs, newsletters, podcasts | 0.65 |
| 4 | Forums, Reddit, social media | 0.40 |
Minimum sources per report: 8 unique domains Target for complex topics: 15–25 sources
Phase 3 — Deep Crawl and Extraction
For each source, fetch the full page (not just the snippet), then extract structured claims:
- Numerical facts (stats, dates, prices, percentages)
- Named entities (people, companies, products)
- Causal claims ("X caused Y because Z")
- Comparative claims ("A is better than B")
Tag each claim with source URL, publish date, tier rating, and a paraphrase or verbatim quote under 15 words.
Extraction template per source:
source: https://example.com/article
published: 2026-04-12
tier: 2
claims:
- text: "Company reached $100M ARR in Q1 2026"
type: numerical
confidence: high
- text: "CEO stated profitability target by 2027"
type: causal
confidence: mediumPhase 4 — Cross-Reference and Conflict Resolution
4a. Claim Clustering
Group identical or related claims across sources. If 3+ Tier 1–2 sources agree, mark as Verified.
4b. Conflict Detection
Flag claims where sources contradict each other:
CONFLICT DETECTED
Claim A: "Revenue is $50M ARR" — Source A, 2026-01
Claim B: "Revenue is $80M ARR" — Source B, 2026-03
Resolution: Use most recent Tier 1–2 source. Note discrepancy in report.4c. Gap Detection
If a sub-question has zero Tier 1–2 sources, mark it [unverified] and flag it in the report.
4d. Confidence Scoring
Confidence = (sum of tier_weights x recency_factor) / num_claims
recency_factor:
< 30 days: 1.0
30–90 days: 0.9
3–12 months: 0.75
> 1 year: 0.60Phase 5 — Report Synthesis
Report Structure
# [Topic] — Deep Research Report
> Researched: [date] | Sources: [N] | Confidence: [X]% | Sub-questions: [N]
---
## Executive Summary
2–4 sentence synthesis of the most important findings.
Lead with the single most important fact.
---
## Table of Contents
1. [Sub-question 1 title](#anchor)
2. [Sub-question 2 title](#anchor)
...
N. Conflicts and Uncertainties
N+1. Sources
---
## 1. [Sub-question Title]
### Finding
One clear, direct answer to the sub-question.
### Evidence
- [Claim] — Source: [Name], [Date], Tier 1
- [Claim] — Source: [Name], [Date], Tier 2
- [Claim] — Source: [Name], [Date], unverified
### Confidence: [X]% | Coverage: [N] sources
---
## [Repeat for each sub-question]
---
## Conflicts and Uncertainties
| Topic | Claim A | Claim B | Resolution |
|-------|---------|---------|------------|
| Revenue | $50M (Source A) | $80M (Source B) | Use Source B (more recent) |
---
## Knowledge Gaps
- [Field X]: No Tier 1–2 sources found. Flagged as unverified.
- [Field Y]: Only sources older than 12 months available.
---
## Research Metadata
| Metric | Value |
|--------|-------|
| Total sources | N |
| Tier 1–2 sources | N |
| Sub-questions answered | N / N |
| Average confidence | X% |
| Date range of sources | YYYY-MM to YYYY-MM |
| Conflicts detected | N |
| Gaps flagged | N |
---
## Sources
| # | URL | Type | Tier | Date | Used For |
|---|-----|------|------|------|----------|
| 1 | https://... | Official | 1 | 2026-05-01 | Revenue data |
| 2 | https://... | News | 2 | 2026-04-10 | Funding round |Show full SKILL.md (281 more words)Show less
Phase 6 — Quality Gates
Run all checks before delivering the report. Fail = do not deliver until resolved.
| Gate | Requirement | Action if Fail |
|---|---|---|
| Source minimum | 8+ unique domains | Run additional search passes |
| Tier coverage | 40%+ Tier 1–2 sources | Flag low-quality sourcing in report |
| Conflict resolution | All conflicts documented | Add to conflicts table |
| Gap flagging | All unanswered sub-questions noted | Add to gaps section |
| Citation accuracy | Every claim has a source | Remove or flag orphan claims |
| Recency | 50%+ sources within 12 months | Flag stale data in report |
Output Modes
Use a flag in the trigger to switch modes:
| Flag | Mode | Description |
|---|---|---|
| (none) | Standard | Full report as specified above |
[academic] | Academic | Adds abstract, methodology, limitations, further research |
[brief] | Quick Brief | Executive summary + top 5 facts + source list. Max 300 words |
[compare] | Comparison | Side-by-side table of N items across shared dimensions |
Iteration Protocol
If confidence is below 70% after the first pass:
ITERATION 2:
- Re-run searches with refined queries
- Target gaps identified in Phase 4
- Fetch Tier 1 sources directly (company.com, arxiv.org, gov sites)
- Update confidence scores
- Note in report: "This section required 2 research iterations"
Maximum iterations: 3
If confidence remains below 60% after 3 iterations, deliver with prominent uncertainty warnings.Anti-Hallucination Rules
- Never invent a statistic. If a number is not sourced, write
[no data found]. - Never paraphrase into a stronger claim. If a source says "may reach", do not write "will reach".
- Never merge two sources' claims into one sentence without attributing both.
- Never omit a conflict because it is inconvenient — surface it in the conflicts table.
- Date every claim. Undated claims receive a recency penalty in confidence scoring.
- If uncertain, say so explicitly using
[unverified]or[disputed]inline tags. - Never reproduce more than 15 words verbatim from any single source.
Trigger Examples
/deep-research What is the current state of fusion energy?
/deep-research [academic] Impact of LLMs on scientific paper quality
/deep-research [compare] React vs Vue vs Svelte for large-scale apps
/deep-research [brief] What caused the 2023 banking crisis?Skill Outputs
| File | Description |
|---|---|
{topic}/report.md | Full research report |
{topic}/sources.yaml | Structured source list with tier ratings |
{topic}/claims.yaml | All extracted claims with provenance |
{topic}/conflicts.md | Conflict log with resolutions |
{topic}/metadata.json | Confidence scores, coverage stats, iteration log |
© shobcoder, 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-knowledge of shobcoder/shob.
Open the folder on GitHubat commit 14831ba
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Deep Research this skillshobcoder/shob | 577 | — | ~2.1k | Automated safety check: Pass | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 83k | 5 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Deep Research WorkflowTokenRhythm/opensquilla | 7.1k | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| X Researchrohunvora/x-research-skill | 1.2k | 1 repos | ~1.6k | Automated safety check: Pass | None | |
| Deep Researchsanjay3290/ai-skills | 430 | 10 repos | ~683 | Automated safety check: Notes | Apache-2.0 | |
| ResearchWeizhena/Deep-Research-skills | 2.3k | 3 repos | ~1.1k | Automated safety check: Pass | MIT |
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Deep Research Workflow
TokenRhythm/opensquilla
Runs multi-round research in three stages with a persisted state file, evidence tracking and a long-form report with per-claim citations.
X Research
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Deep Research
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Execute autonomous multi-step research using Google Gemini Deep Research Agent.
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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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Categories
Questions about Deep Research
What does Deep Research do?
GOD MODE deep research skill. An agent skill from shobcoder/shob. Deep Research is an agent skill from shobcoder/shob. GOD MODE deep research skill.
When should I use Deep Research?
Deep Research fits situations like: any question that demands depth; verifiable accuracy.
How do I install Deep Research in Claude Code?
Run `npx skills add shobcoder/shob --skill deep-research -a claude-code`. Or copy the skill folder (skills/research-knowledge in shobcoder/shob) 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 shobcoder/shob --skill deep-research -a codex`. Or copy the skill folder (skills/research-knowledge in shobcoder/shob) 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 shobcoder/shob --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?
SKILL.md names no scripts, command-line tools or credentials: Deep Research is instructions for the agent only.
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 2.1k tokens (SKILL.md is roughly 8.5k 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: 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, 430 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Deep Research?
shobcoder (a GitHub organization) maintains it in shobcoder/shob, which has 577 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on September 18, 2026.
Source: shobcoder/shob on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.