> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dialog.tools/llms.txt
> Use this file to discover all available pages before exploring further.

# Working Effectively with Your Agent

> Patterns and tips for getting the most out of Dialog

Your agent responds to natural language -- research questions, commands, follow-ups, and instructions all work. Here are the patterns that get the best results.

## Research queries

### Be specific about the topic and angle

<Tabs>
  <Tab title="Good">
    "What are indie hackers saying about building in public? What strategies are working and what are the common mistakes?"
  </Tab>

  <Tab title="Too broad">
    "Tell me about building in public"
  </Tab>
</Tabs>

### Ask for comparisons

<Tabs>
  <Tab title="Good">
    "How do developers compare Supabase vs Firebase for new projects? What are the trade-offs people mention most?"
  </Tab>

  <Tab title="Too broad">
    "What's the best backend service?"
  </Tab>
</Tabs>

### Request specific formats

<Tabs>
  <Tab title="Good">
    "Summarize the top 5 complaints about Slack from Reddit, with links to the original posts"
  </Tab>

  <Tab title="Too broad">
    "What do people think about Slack?"
  </Tab>
</Tabs>

### Target specific communities

<Tabs>
  <Tab title="Good">
    "What are the most discussed topics in r/SaaS and r/startups this week?"
  </Tab>

  <Tab title="Too broad">
    "What's trending in startups?"
  </Tab>
</Tabs>

## Command patterns

Beyond research, your agent handles many types of instructions:

| Pattern                | Example                                                                         |
| ---------------------- | ------------------------------------------------------------------------------- |
| **Save a link**        | "Save this for me: \[URL]"                                                      |
| **Add to tasks**       | "Add to my task list: review competitor pricing"                                |
| **Draft content**      | "Draft a LinkedIn post about AI agent tools"                                    |
| **File to workspace**  | "Save all of this to the workspace -- create a research file and add bookmarks" |
| **Update files**       | "Add this to our competitive research"                                          |
| **Scrape and analyze** | "Scrape their website and see how they position themselves"                     |
| **Create a skill**     | "Create a skill so you know how to convert markdown to Google Docs"             |

You don't need specific syntax. Natural language like "remind me to..." or "I need to track..." works just as well as explicit commands.

## Multi-session patterns

Your agent remembers everything in its workspace. Use that continuity:

```
Add this to our OpenClaw research
```

```
Can you find the competitors we saved last week?
```

```
What links do we have related to AI agent frameworks?
```

```
Can you track down Dialog related research files?
```

Referencing past work naturally ("our research", "the competitors we saved") tells your agent to search its workspace and build on previous findings.

## Iteration patterns

Dialog is built for back-and-forth. Iterate on results:

```
I like this one but it needs to skew more towards the original angle
```

```
Give me 5 more options, each with a different approach
```

```
OK let's move forward with option F
```

```
No em dashes please
```

Your agent maintains full context within a session, so each message builds on the last. Don't re-explain -- just give direction.

## Follow-up strategies

1. **Start broad, then narrow** -- Begin with an overview question, then drill into specifics
2. **Shift angles** -- Ask about sentiment, then pricing, then features
3. **Compare and contrast** -- After researching one topic, ask how it compares to alternatives
4. **Request different formats** -- Ask for a summary table, bullet points, or a different structure
5. **Save what matters** -- When you find something useful, tell your agent to save it to the workspace

## Common research tasks

| Task                   | Example query                                                                      |
| ---------------------- | ---------------------------------------------------------------------------------- |
| Competitive intel      | "What are users saying about \[competitor]'s latest update?"                       |
| Idea validation        | "Are people looking for a tool that does \[your idea]?"                            |
| Pricing research       | "How do \[category] tools price their products? What do users think is fair?"      |
| Feature prioritization | "What features do people wish \[product category] tools had?"                      |
| Market sizing          | "How active are the communities around \[topic]? What's the engagement like?"      |
| Customer pain points   | "What are the biggest frustrations with \[existing solution]?"                     |
| Comprehensive report   | "Build a comprehensive competitive report on \[company]. Use all available tools." |
| Tool discovery         | "Can you track down the best tools for \[task]? Use Reddit and web search."        |