Systemonomic

List all tasks in a project.

Each task has an id, name, description, mode (manual/semi-auto/auto), and links to WDA nodes.

Create a new task in a project.

Args: project_id: The project to add the task to name: Task name description: Optional task description mode: One of: manual, semi-auto, auto (default: manual)

Auto-generate tasks from the WDA Objects level.

Analyzes the Objects (lowest level) of the WDA and creates corresponding control tasks. This is the standard first step before running ATSS.

Use AI to derive detailed task suggestions from WDA objects.

More sophisticated than generate_tasks_from_wda — uses an LLM to analyze each WDA object and suggest tasks with descriptions.

Args: project_id: The project to analyze provider: LLM provider — gemini, claude, or openai (default: gemini)

List all pending task suggestions for a project.

Suggestions are AI-generated task proposals that haven't been accepted yet.

Accept task suggestions, promoting them to actual project tasks.

Args: project_id: The project containing the suggestions suggestion_ids: List of suggestion IDs to accept

Run ATSS (Automated Task Suitability Scoring) on all tasks in a project.

Each task is assessed across multiple gates (data availability, rule-base, exception handling, etc.) and scored 0-100 for automation suitability.

Args: project_id: The project whose tasks to assess provider: LLM provider — gemini, claude, or openai (default: gemini) model: Specific model name (optional, uses provider default)

Returns scored results for each task with classification (Automate / Augment / Manual) and reasoning.

Get stored ATSS results for a project.

Returns previously persisted assessment results, including scores, classifications, and reasoning for each task.

Persist ATSS assessment results to the project.

Args: project_id: The project to save results to rows: List of ATSS result objects (from run_atss_batch output)

List all ATSS assessment runs for a project, with timestamps and summaries.