# Tips & Best Practices

### Writing Effective Prompts

The agent responds to natural language, but how you phrase your request makes a real difference.

**Be specific about the task:**

| Instead of...       | Try...                                                                                                 |
| ------------------- | ------------------------------------------------------------------------------------------------------ |
| "Process this file" | "Extract all line items from this PDF and create a CSV with columns for SKU, quantity, and unit price" |
| "Check this email"  | "Read this email and draft a reply confirming we can deliver by the requested date"                    |
| "Analyse this data" | "Compare Q1 and Q2 revenue by product category and highlight anything that changed by more than 10%"   |

**Provide context upfront:**

* Upload all relevant files with your first message
* Mention which systems or data sources are involved
* Specify the output format you want (CSV, email draft, summary, etc.)

**Iterate naturally:**

The agent remembers everything in the current session. You can:

* Ask it to revise: *"Change the date format to DD/MM/YYYY"*
* Build on previous work: *"Now do the same for the March data"*
* Redirect: *"Actually, focus on the top 10 by revenue instead"*

### Understanding the Agent's Output

#### Narration

While working, the agent shows short status messages describing each step. This is useful for:

* **Knowing it's still working** on longer tasks
* **Catching mistakes early** — if the narration shows it's headed in the wrong direction, you can interrupt
* **Understanding the approach** the agent took, which helps you refine future requests

#### Todo List

For complex tasks, the agent creates a visible todo list showing its plan. Items are checked off as they're completed, giving you a clear picture of progress.

#### Skill Cards

When the agent invokes a skill, a card appears in the chat. Skill cards show:

* The skill name
* Execution progress
* Results when complete

Cards appear immediately in a loading state and update in place — nothing shifts around or disappears.

### When to Use the Agent vs. a Workflow

**Use the agent when:**

* The task is **ad-hoc or one-off** — you won't repeat it the same way every time
* The task needs **judgement or reasoning** — interpreting documents, drafting responses, comparing data
* You want to **explore or investigate** — "What's in this file?", "How does this compare to last month?"
* The task involves **multiple steps that depend on what's found** — the agent adapts as it goes

**Use a workflow when:**

* The process is **repeatable and structured** — it runs the same way every time
* You need **scheduled or triggered execution** — process every incoming email, run every morning at 9am
* **Volume is high** — processing hundreds of orders, invoices, or documents per day
* You need **deterministic, auditable results** — every run follows the exact same logic

**Use both together:**

* Use the agent to **prototype and test** a process, then convert it to a workflow once it's proven
* Use workflows for the **high-volume automation** and the agent for **exception handling and edge cases**
* Use skills to **bridge the gap** — a skill created in the agent can encode a process that runs reliably every time

### Common Pitfalls

* **Being too vague.** The agent will try its best, but vague instructions lead to generic results. Specificity wins.
* **Not uploading files upfront.** If the agent needs data, give it the data in your first message rather than making it ask.
* **Expecting workflow-level determinism.** The agent makes decisions — it might take a different approach to the same task on a different day. If you need consistency, use a workflow.
* **Ignoring the narration.** The narration tells you what the agent is doing. If it's going wrong, catch it early and redirect.


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