Systemonomic
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| SYSTEMONOMIC_API_KEY | Yes | Your API key from Systemonomic (starts with 'sk_sys_') | |
| SYSTEMONOMIC_API_URL | No | Optional API endpoint URL (defaults to production) | https://systemonomic.com |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_tasksC | List all tasks in a project. Each task has an id, name, description, mode (manual/semi-auto/auto), and links to WDA nodes. |
| create_taskB | 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) |
| generate_tasks_from_wdaB | 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. |
| derive_task_suggestionsA | 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_suggestionsB | List all pending task suggestions for a project. Suggestions are AI-generated task proposals that haven't been accepted yet. |
| accept_suggestionsC | 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_batchA | 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_atss_resultsB | Get stored ATSS results for a project. Returns previously persisted assessment results, including scores, classifications, and reasoning for each task. |
| persist_atss_resultsC | 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_atss_runsB | List all ATSS assessment runs for a project, with timestamps and summaries. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 10 tools
Most tools have distinct purposes, but there is some potential confusion between 'derive_task_suggestions' and 'generate_tasks_from_wda' as both generate tasks from WDA objects, with the former being described as 'more sophisticated.' The other tools are clearly differentiated, covering suggestion management, task creation, ATSS assessment, and listing operations.
All tool names follow a consistent snake_case pattern with clear verb_noun structures (e.g., 'accept_suggestions', 'create_task', 'list_tasks'). This uniformity makes the tool set predictable and easy to navigate, with no deviations in naming conventions.
With 10 tools, the server is well-scoped for managing tasks, suggestions, and ATSS assessments in a project automation system. Each tool serves a specific role in the workflow, from creation and listing to analysis and persistence, without feeling bloated or sparse.
The tool set covers core workflows for task and suggestion management, including creation, listing, and assessment, but lacks update and delete operations for tasks or suggestions. This minor gap might require workarounds, but the overall surface supports the domain of project automation and AI-driven task analysis effectively.