> For the complete documentation index, see [llms.txt](https://docs.ixhello.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ixhello.com/ix-hello-reporting/premium-reporting/total-conversations-with-contained-and-transferred-dedicated-sub-view/conversations-by-assistant-disposition-dedicated-sub-view.md). # Conversations by Assistant Disposition — Dedicated Sub-View This sub-view provides the full-page, filter-enabled version of the Conversations by Assistant Disposition horizontal bar chart from Section 22. It adds Assistant Disposition as an explicit filter, enabling analysts to isolate specific outcome types.

*Figure 1: Conversations by Assistant Disposition — Full Sub-View with Filter Panel*

### 1. Filter Panel


Filter	Description
Date Selection Type	Custom Dates or relative options. Period shown: 03/08/2026 – 04/09/2026.
Channel	(All) — can be narrowed to isolate disposition patterns per channel.
Stage	STG — should be set to PROD for production analysis.
Business Day	(All) — filter to business days only to exclude weekend behavior.
Assistant	(All) — critical filter: selecting a specific assistant reveals its individual Success/Failure profile.
Assistant Disposition	(All) — selecting a specific value (e.g., Failure only) highlights which assistants and days generated failures.

The color-coded legend in the filter panel confirms the disposition color scheme: Success (gold), Failure (light green), Null (medium green), AbandonSuccess (blue/gray). These colors are consistent across all Service-Disposition workbook sub-views. ### 23.2 Business Value The Assistant Disposition filter is particularly powerful for quality investigations. Filtering to Failure only and then filtering by Assistant reveals which specific assistant generates the most failures. Filtering to Null reveals which assistants are missing disposition configuration. This sub-view is the recommended starting point for any AI assistant quality audit or post-incident review. --- # 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 by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.ixhello.com/ix-hello-reporting/premium-reporting/total-conversations-with-contained-and-transferred-dedicated-sub-view/conversations-by-assistant-disposition-dedicated-sub-view.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. 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.