Doc: minor (#10627)

### What problem does this PR solve?


### Type of change


- [x] Documentation Update

docs/guides/agent/agent_component_reference/parser.md

@@ -0,0 +1,17 @@
+---
+sidebar_position: 30
+slug: /parser_component
+---
+
+# Message component
+
+A component that sets the parsing rules for your dataset.
+
+---
+
+A **Parser** component sets the parsing rules for various file types, including parsing methods for PDFs , fields to parse for Emails, and OCR methods for images.
+
+
+## Scenario
+
+An **parser** component is auto-populated on the ingestion pipeline canvase and always required in an ingestion pipeline workflow.

docs/release_notes.md

@@ -30,7 +30,7 @@ Released on October 15, 2025.
 
 - Orchestratable ingestion pipeline: Supports customized data ingestion and cleansing workflows, enabling users to flexibly design their data flows or directly apply the official data flow templates on the canvas.
 - GraphRAG & RAPTOR write process optimized: Replaces the automatic incremental build process with manual batch building, significantly reducing construction overhead.
-- Long-context RAG: Automatically generates document-level table of contents (TOC) structures to mitigate context loss caused by inaccurate or excessive chunking, substantially improving retrieval quality. This feature is now available via a TOC extraction template.
+- Long-context RAG: Automatically generates document-level table of contents (TOC) structures to mitigate context loss caused by inaccurate or excessive chunking, substantially improving retrieval quality. This feature is now available via a TOC extraction template. See [here](./guides/dataset/extract_table_of_contents.md).
 - Video file parsing: Expands the system's multimodal data processing capabilities by supporting video file parsing.
 - Admin CLI: Introduces a new command-line tool for system administration, allowing users to manage and monitor RAGFlow's service status via command line.