| name | gemini-deep-research-browser |
| alias | @dp |
| description | Craft and launch a Gemini Deep Research session via a custom Gem. Use when: @dp, @deep-research, research sprint, investigate topic, market research, technical deep-dive. |
| risk | safe |
| source | K3 Agentic Skills |
| date_added | 2026-05-12 |
@dp — Gemini Deep Research Skill
Alias: @dp [topic]
Crafts and launches a Gemini Deep Research session using a custom Deep Research Architect Gem that you own.
Setup: Create Your Deep Research Gem (One Time)
- Go to
https://gemini.google.com/gems/create
- Name it:
Deep Research Architect
- Paste this system prompt:
You are a Deep Research Query Architect. Your job is to transform vague research topics into high-precision Gemini Deep Research queries.
When a user gives you a topic:
1. Identify the core question and 2-3 critical sub-questions
2. Add year scope (current year), domain constraints, and format requests (tables, code examples, comparisons)
3. Recommend source type:
- Technical/general → No sources needed (web-only)
- User-provided docs → Google Drive attachment
- Prior research notes → NotebookLM attachment
4. Output:
a. The paste-ready research query (3-5 sentences, specific)
b. Source recommendation with reasoning
c. A 3-item plan checklist of what good research will cover
Keep queries tight. Vague queries produce vague reports.
- Save the Gem. Copy its URL — that's your
@dp endpoint.
Workflow (3 Steps)
Step 1 — Craft the Query (Agent)
Expand the user's topic:
- Add year scope (e.g., "2026"), domain constraints
- Request comparison tables or code examples if technical
- Decide source type:
- Project docs / specs → Google Drive
- Prior research notebook → NotebookLM
- General / technical research → None
Open your Gem URL and drop the topic in. It returns a paste-ready research query + plan checklist.
Step 2 — Launch Deep Research (User)
- Open a new Gemini chat:
https://gemini.google.com/app
- Click
+ button left of input → Tools → Deep research
- Paste the query from your Gem
- If sources needed: attach via the Sources button before submitting
- Submit → review the auto-generated plan → click Start research
Step 3 — Retrieve Results (User)
When research completes:
- Export as Google Doc → Share → Export
- Download as
.docx
- Convert to Markdown:
python -m markitdown report.docx > report.md
- Store in your project's research directory
Confirmed UI Notes (May 2026)
| Action | Where |
|---|
| Activate Deep Research | + button → Tools → "Deep research" |
| Attach Google Drive | Sources button → Drive |
| Edit research plan | "Edit plan" before "Start research" |
| Export report | Share icon → Export to Docs |
Curated @dp Prompt Examples
ADK / Model Architecture
@dp Gemini 3.1 model cascading: Flash-Lite drafter → Flash linter → Pro critic — ADK LoopAgent cost and quality tradeoffs 2026
@dp thinking_level None/Low/Medium/High in Gemini 3.1 — token cost, latency, quality per level for multi-agent pipelines
@dp Gemini Batch Mode 50% discount — async batch processing in ADK for non-realtime generation
@dp ARC-AGI-2 benchmark results — what long-horizon agentic tasks Gemini 3.1 Pro handles vs fails at
RAG / Embeddings
@dp sqlite-vec vs pgvector for local vector memory at 10k documents — embedding strategies 2026
@dp Gemini Embedding 2 task prefix patterns vs legacy task_type — migration guide and pitfalls
@dp MRL truncation quality vs storage tradeoffs — 256/768/1536/3072 dims benchmarks 2026
Infrastructure
@dp Jules GitHub agent autonomous PR workflows — deduplication, branch hygiene, CI/CD best practices 2026
@dp Docker dynamic MCP server pattern — runtime secret injection from GCP Secret Manager
@dp ADK DatabaseSessionService SQLite session persistence — call replay and failure logging patterns
Market / Business Research
@dp [your market] competitive landscape 2026 — pricing, features, differentiators comparison table
@dp [your tech stack] security audit patterns — OWASP Top 10 coverage and remediation 2026
Tips
- Be specific upfront. "AI agents" → bad. "ADK 2.0 LoopAgent vs LangGraph cycles — Python, 2026, cost benchmarks" → good.
- Use year scope always. Deep Research's web index is current; anchor it with "2026" to avoid outdated results.
- Review the plan. Before clicking "Start research", Deep Research shows you its research plan. Edit it if a key angle is missing.
- Export immediately. Reports expire from the chat. Export to Docs right after completion.
