Skip to content
cccskills
FreePublished on GitHub

deep-research

Use when user requests research requiring multiple sources, comprehensive analysis, or synthesis across topics - technical research, domain knowledge gathering, market analysis, or learning about complex subjects

The English summary is being prepared. Showing the original description.

See how to install

Files included (5)

  • SKILL.md5.0 KB
  • design.md2.0 KB
  • query-analyzer-prompt.md3.6 KB
  • research-agent-prompt.md3.1 KB
  • synthesizer-prompt.md3.7 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Deep Research

Autonomous multi-agent research system. Dispatches parallel sub-agents, stores findings to files, synthesizes into briefs or reports.

Core principle: Planning → Parallel research agents → File-based findings → Synthesis = high quality research with minimal context usage.

When to Use

digraph when_to_use {
    "User requests research?" [shape=diamond];
    "Quick factual lookup?" [shape=diamond];
    "Use single search tool directly" [shape=box];
    "Multiple sources or synthesis needed?" [shape=diamond];
    "deep-research" [shape=box];

    "User requests research?" -> "Quick factual lookup?" [label="yes"];
    "Quick factual lookup?" -> "Use single search tool directly" [label="yes"];
    "Quick factual lookup?" -> "Multiple sources or synthesis needed?" [label="no"];
    "Multiple sources or synthesis needed?" -> "deep-research" [label="yes"];
}
```text

**Use for:** Technical research, domain knowledge, market analysis, architectural patterns, comparing approaches,
learning complex topics

**Don't use for:** Single fact lookups, specific URL fetches, questions answerable in one search

## The Process

```dot
digraph process {
    rankdir=TB;

    "Create research directory in scratchpad" -> "Dispatch Query Analyzer agent";
    "Dispatch Query Analyzer agent" -> "Analyzer writes research-plan.md";
    "Analyzer writes research-plan.md" -> "Read plan, dispatch N Research agents IN PARALLEL";
    "Read plan, dispatch N Research agents IN PARALLEL" -> "Each agent writes findings-{thread}.md";
    "Each agent writes findings-{thread}.md" -> "Wait for all agents";
    "Wait for all agents" -> "Dispatch Synthesizer agent";
    "Dispatch Synthesizer agent" -> "Synthesizer reads all findings, writes final-output.md";
    "Synthesizer reads all findings, writes final-output.md" -> "Read final output, present summary to user";
}
```text

## Quick Reference

### Phase 1: Planning (Query Analyzer Agent)

Uses `./query-analyzer-prompt.md`. Writes `research-plan.md` containing:

- Query type: technical | domain | hybrid
- Complexity: simple (2-3 agents) | moderate (3-4) | complex (5-6)
- Research threads with source recommendations
- Output format recommendation: brief | report

### Phase 2: Parallel Research

Uses `./research-agent-prompt.md`. Each agent:

1. Invokes `exa-search` skill for source strategy
2. Executes searches (Exa-primary, see Source Selection below)
3. Writes `findings-{thread-name}.md`

**Source Selection:**

| Query Signal                 | Primary Source                   |
| ---------------------------- | -------------------------------- |
| Code, APIs, libraries        | `mcp__exa__get_code_context_exa` |
| Concepts, analysis, opinions | `mcp__exa__web_search_exa`       |
| Video explanations needed    | `yt-transcribe` skill            |
| Very recent news (< 1 week)  | `WebSearch` fallback             |

### Phase 3: Synthesis

Uses `./synthesizer-prompt.md`. Reads all findings files, writes `final-output.md`:

- **Actionable Brief** (~300 words): Simple query + clear consensus
- **Structured Report** (~1500 words): Complex query or conflicting findings

## Agent Dispatch Methods

**For complex queries (4+ threads):** Use Task tool with `subagent_type: "general-purpose"` for true sub-agent
isolation. Dispatch all research agents in a single message (parallel Task calls).

**For simpler queries (2-3 threads):** Parallel tool calls within same context is acceptable - make all searches
simultaneously, then write findings files.

Either way: research threads must execute in parallel, not sequentially.

## File Structure

```text
{scratchpad}/deep-research-{timestamp}/
├── research-plan.md
├── findings-*.md
└── final-output.md
```text

## Common Mistakes

| Mistake                                               | Fix                                                 |
| ----------------------------------------------------- | --------------------------------------------------- |
| Doing research yourself instead of dispatching agents | Always use the three-phase architecture             |
| Keeping findings in context instead of files          | Each agent MUST write to files                      |
| Sequential research agents                            | Dispatch all research agents in PARALLEL            |
| Skipping planning phase                               | Always run Query Analyzer first                     |
| Using WebSearch as default                            | Exa is primary; WebSearch only for very recent news |

## Red Flags - STOP

- "I'll just do a quick search myself" → Use the full process
- "I don't need to write files for this" → Files are mandatory
- "I'll research these topics one at a time" → Parallel dispatch
- "This is simple, I'll skip planning" → Always plan first

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Patterns and techniques for evaluating and improving AI agent outputs.

The English summary is being prepared. Showing the original description.

rudironsoni/Synaxis2Updated Mar 17, 2026

Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations.

The English summary is being prepared. Showing the original description.

rudironsoni/Synaxis2Updated Mar 17, 2026

AI-powered wiki generation for code repositories with commands, agents, and skills

The English summary is being prepared. Showing the original description.

rudironsoni/Synaxis2Updated Mar 17, 2026

Use when building .NET 10 or C# 14 applications; when using minimal APIs, modular monolith patterns, or feature folders; when implementing HTTP resilience, Options pattern, Channels, or validation; when seeing outdated patterns like old extension method syntax

The English summary is being prepared. Showing the original description.

rudironsoni/Synaxis2Updated Mar 17, 2026

Implements accessible .NET UI. SemanticProperties, ARIA, AutomationPeer, testing per platform.

The English summary is being prepared. Showing the original description.

rudironsoni/Synaxis2Updated Mar 17, 2026

Adds analyzer packages to a project. Nullable, trimming, AOT compat analyzers, severity config.

The English summary is being prepared. Showing the original description.

rudironsoni/Synaxis2Updated Mar 17, 2026

See all skills by rudironsoni

Report a problem with this skill