Performance Metrics
Astrakion operates under a Kanban workflow where success is defined by stable flow, predictable delivery, small batch sizes, minimal waiting, and consistent cycle times.
Kanban Principles
- Flow > Speed — Predictability over raw execution speed
- Small Work Items — Issues fit into Kade's 5-15 minute window
- Limit WIP — One issue moves through the pipeline at a time
- Make Delays Visible — Blocked time identifies systemic delays
- Metrics Guide Refinement Only — Metrics never cause rework
Core Metrics
The following metrics are recorded for every code-impacting issue. Analysis-only issues do not generate metrics.
Lead Time
Time from human approval → Astra submitting a PR into <HOD_BRANCH>.
Represents end-to-end delivery from the human's perspective.
Cycle Time
Time from Astra assigning to Kade → Orion merging into astrakion/develop.
Shows internal AI execution efficiency.
Implementation Time
Time from Kade beginning → Kade opening the PR.
Ensures tasks stay within 5-15 minute batch size.
Estimate Accuracy
Difference between Kade's estimated time and actual implementation time:
- Accurate: ±2 minutes
- Moderate variance: ±3-5 minutes
- High variance: 6+ minutes
Helps detect unclear requirements or hidden complexity.
Flow Efficiency
Ratio of active work time to total cycle time:
Flow Efficiency = Active Work Time / Total Cycle Time Shows how much time is spent working vs. waiting.
Blocked Time
Time an issue cannot progress due to:
- Waiting for human clarification
- Human-origin PR blocking the AI lane
- LLM provider errors
- Exhausted Astrakion Tokens
- GitHub outages
Analysis-only issues never contribute to Blocked Time.
Throughput
Number of code-impacting issues completed per day or week.
Measures long-term delivery stability.
Work Type Distribution
Percentage breakdown by category: bug fix, feature, enhancement, clarification, QA-raised improvement, human-directed update.
Cost Per Issue
Effective cost to complete one code-impacting issue based on tier, included capacity, and tokens consumed.
Analysis-only issues have no cost.
What Astra Learns
Metrics inform future refinement:
- Oversized Issues — Long cycle time → future issues should be split
- Unclear Requirements — High variance → improve refinement
- Risky Modules — Repeatedly slow areas tracked for caution
- Human Bottlenecks — High blocked time from clarifications
- Predictability Trends — Stable throughput indicates healthy flow
Metrics never affect current work — only future tasks.
Safety Guarantees
Performance metrics never trigger:
- Rework or retries
- Issue reopening
- PR modification
- Additional test passes
- Scope expansion
- Automatic corrections to rejected PRs
Ownership Summary
| Metric | Owner |
|---|---|
| Lead Time | Astra |
| Cycle Time | Astra |
| Implementation Time | Kade → Astra |
| Estimate Accuracy | Astra |
| Flow Efficiency | Astra |
| Blocked Time | Astra |
| Throughput | Astra |
| Work Type Distribution | Astra |
| QA / Risk Insights | Orion |
| Cost Per Issue | Astra |