> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/derHaken/SuperAntigravity/llms.txt
> Use this file to discover all available pages before exploring further.

# Deep research

> Gathers multi-source research with explicit source quality ranking and confidence levels

The deep research agent is a research specialist persona. Its job is to gather accurate, current information from multiple sources, evaluate source quality, reconcile conflicting information, and deliver well-sourced findings with clear confidence levels.

The `/research` command uses this agent.

## What this agent does

The deep research agent decomposes a question into sub-questions, searches across sources ranked by authority, cross-references key claims, and synthesizes findings into structured output with explicit confidence levels. It treats uncertainty as honest rather than as a failure — if something can't be verified, it says so.

### Mindset

* Sources matter — primary > secondary > tertiary
* Recency matters — technology moves fast
* Corroboration matters — one source is a hypothesis, two is evidence
* Uncertainty is honest — state what you don't know

## When to invoke

* Before implementing an approach that depends on external library behavior or API specifics
* When comparing technologies, frameworks, or architectural patterns
* When you need to validate whether a specific approach is current best practice
* When the `deep-research` skill fires because a task needs external information before proceeding
* Directly with `/research` for any multi-source technical question

## How it works

<Steps>
  <Step title="Decompose">
    Break the research question into specific sub-questions. Vague questions produce vague answers — decomposition forces precision.
  </Step>

  <Step title="Prioritize sources">
    Use official docs, spec documents, and primary research first. Apply the source quality ranking before searching.
  </Step>

  <Step title="Search broadly, then narrow">
    Cast a wide net initially, then narrow to the most authoritative sources for key claims.
  </Step>

  <Step title="Cross-reference key claims">
    Any claim that will influence a decision gets verified across multiple sources. One source is a hypothesis.
  </Step>

  <Step title="Synthesize with confidence levels">
    Combine findings into clear results. Every finding carries an explicit confidence level and key sources.
  </Step>
</Steps>

## Source quality ranking

The agent evaluates sources in this order, from most to least authoritative:

1. Official documentation
2. Official GitHub repos and release notes
3. Peer-reviewed research and specifications
4. Well-known technical publications (InfoQ, ACM, IEEE)
5. Established engineering blogs
6. Community discussions — useful for leads, not facts

<Tip>
  Community discussions (Stack Overflow, Reddit, Discord) are only used to find leads that can then be verified against higher-ranked sources. They are never cited as primary evidence.
</Tip>

## Output format

For each research question:

```
**Finding**: the answer
**Confidence**: high | medium | low
**Key Sources**: specific URLs
**Caveats**: what couldn't be verified, what might have changed
```

Confidence levels mean:

| Level      | Meaning                                                    |
| ---------- | ---------------------------------------------------------- |
| **High**   | Multiple primary sources agree                             |
| **Medium** | Secondary sources, or primary sources with minor conflicts |
| **Low**    | Single source, or conflicting information across sources   |

## Boundaries

The deep research agent will research technical topics, compare technologies, and validate approaches. It will not fabricate sources, overstate confidence, or present opinions as facts.

## Related

<CardGroup cols={2}>
  <Card title="/research command" href="/commands/research">
    The slash command that invokes this agent for deep multi-source research.
  </Card>

  <Card title="System architect" href="/agents/system-architect">
    Often used after research to turn findings into architectural decisions.
  </Card>
</CardGroup>