Agent Workflow Autonomy
Classify agent-workflow autonomy from step and intervention counts.
Description
Agent-workflow autonomy summarizes recorded autonomous and approval steps plus intervention frequency.
Agent-workflow autonomy summarizes recorded autonomous and approval steps plus intervention frequency. The bands are fixed operational heuristics.1
Classify agent-workflow autonomy from step and intervention counts.
When to use Agent Workflow Autonomy
Use this tool to classify agent-workflow autonomy from step and intervention counts.
Prepare the recorded observations, ratings, assumptions or expected/observed lists requested. Choose thresholds and definitions appropriate to the planning question.
How to use Agent Workflow Autonomy and understand its results
- Prepare the recorded observations, ratings, assumptions or expected/observed lists requested. Choose thresholds and definitions appropriate to the planning question.
- Enter totalWorkflowSteps, autonomousSteps, humanApprovalSteps, humanInterventionEvents using the field table and calculation rules, then run the tool.
- Read autonomousStepPercent, approvalStepPercent, interventionsPerStep, autonomyLevel. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| totalWorkflowSteps | Total workflow steps | integer; minimum: 1 | Required |
| autonomousSteps | Autonomous steps | integer; minimum: 0 | Required |
| humanApprovalSteps | Human approval steps | integer; minimum: 0 | Required |
| humanInterventionEvents | Human intervention events | integer; minimum: 0 | Required |
Enter positive integer total and nonnegative integer counts; autonomous/approval counts must each fit total. Return percentages, intervention ratio and high-autonomy, supervised at autonomous≥40%, or assisted.
high=autonomous%≥80 AND approval%≤20 AND interventions/step≤0.1 Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| autonomousStepPercent | Autonomous step share (%) | number; minimum: 0; maximum: 100 |
| approvalStepPercent | Approval step share (%) | number; minimum: 0; maximum: 100 |
| interventionsPerStep | Interventions per step | number; minimum: 0 |
| autonomyLevel | Autonomy level | string; one of "assisted", "supervised", "high-autonomy" |
{
"input": {
"totalWorkflowSteps": 10,
"autonomousSteps": 8,
"humanApprovalSteps": 2,
"humanInterventionEvents": 1
},
"output": {
"autonomousStepPercent": 80,
"approvalStepPercent": 20,
"interventionsPerStep": 0.1,
"autonomyLevel": "high-autonomy"
}
}Limitations and assumptions
Autonomous and approval counts may overlap; their sum is not constrained. No workflow is executed or quality assessed.
Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Tabletop Exercise Coverage: Audit futures tabletop exercise coverage. For a complementary task, use Evidence Graph Mapper: Validate a compact directed evidence graph encoded as node IDs and A->B edges.
References
-
Agent Workflow Autonomy — tool.io
Similar or alternative tools
- Tabletop Exercise Coverage
Audit futures tabletop exercise coverage.
- Evidence Graph Mapper
Validate a compact directed evidence graph encoded as node IDs and A->B edges.