> For the complete documentation index, see [llms.txt](https://help.clausebuddy.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.clausebuddy.com/playbooks/why.md).

# Why?

### **Why use Playbooks?**

Analyzing a document with Playbooks helps legal teams automate contract reviews by applying explicit internal rules to documents using AI. It ensures consistency, supports knowledge sharing, and adapts reviews to deal-specific needs.

#### ✅ When you *should* use it:

* **To enforce internal rules consistently**\
  Make sure your documents comply with your organisation’s specific legal policies.
* &#x20;**To increase review efficiency**\
  Automate routine checks and speed up contract reviews while maintaining quality.
* **To support team knowledge management**\
  Capture unwritten rules and share legal expertise within your team.
* **To adapt reviews to specific deals**\
  Tailor contract reviews based on deal type, risks, and business context.

***

#### ❌ When you *shouldn’t* use it:

* **If the review delegated to non-legal experts**\
  Legal expertise is needed to interpret AI findings accurately.
* **If you prefer non-AI methods**\
  For those wary of AI, ClauseBuddy’s [Checklists](https://help.clausebuddy.com/checklists/) feature provides structured manual reviews without AI.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://help.clausebuddy.com/playbooks/why.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
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Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
