annotate

To process JSONL annotations automatically, submit a batch of insert, delete, replace, or comment annotations to the task endpoint. The system triages each prompt, validates paths, sanitizes content, and writes changes directly to source files while generating an execution report.

Cross-impact analysis for code editing evaluates how insert, delete, replace, and comment annotations affect multiple files and layers within a notebook-style workspace. It ensures safe content modifications by assessing dependencies before writing changes to source files.

Yes, you can batch process these four annotation types across multiple files. The workflow triages JSONL prompts, performs path validation, applies content sanitization, and writes updates to source files while emitting structured execution reports and routing signals.

Yes, document processing reads and updates operational context files such as .target.md, .plan.md, and .index.json. These files guide the triage of JSONL annotations and ensure safe edits before generating .summary.md and .auto-signal routing outputs.

Automated JSONL annotation processing requires strict path validation and relies on structured context files to function safely. It is limited to insert, delete, replace, and comment operations within notebook-style workspaces and cannot bypass content sanitization rules.

The best way to manage workflow signals after code edits is to utilize the generated .auto-signal files. These routing signals are emitted alongside .summary.md reports to trigger progressive workflows and update the .index.json context automatically.