Agent Skill · Harness
dora-metrics
Generate DORA metrics and engineering performance reports using Harness SEI via MCP. Track deployment frequency, lead time, change failure rate, and MTTR. Use when user says "DORA metrics", "deployment frequency", "lead time", "engineering metrics", or asks about team performance.
Skill body
DORA Metrics
Generate DORA metrics reports using Harness Software Engineering Insights (SEI) via MCP.
Instructions
All DORA metrics are served by a single resource type: sei_dora_metric. Pass the metric parameter to select the variant:
deployment_frequencydeployment_frequency_drilldownlead_timechange_failure_ratechange_failure_rate_drilldownmttr
Required inputs on every DORA call: team_ref_id, date_start, date_end, granularity (DAILY |
WEEKLY | MONTHLY). |
Step 1: Get a DORA Metric
Deployment Frequency:
Call MCP tool: harness_get
Parameters:
resource_type: "sei_dora_metric"
metric: "deployment_frequency"
team_ref_id: "<team_id>"
date_start: "2026-03-01"
date_end: "2026-04-01"
granularity: "WEEKLY"
Lead Time for Changes:
Call MCP tool: harness_get
Parameters:
resource_type: "sei_dora_metric"
metric: "lead_time"
team_ref_id: "<team_id>"
date_start: "2026-03-01"
date_end: "2026-04-01"
granularity: "WEEKLY"
Change Failure Rate:
Call MCP tool: harness_get
Parameters:
resource_type: "sei_dora_metric"
metric: "change_failure_rate"
team_ref_id: "<team_id>"
date_start: "2026-03-01"
date_end: "2026-04-01"
granularity: "WEEKLY"
Mean Time to Recovery:
Call MCP tool: harness_get
Parameters:
resource_type: "sei_dora_metric"
metric: "mttr"
team_ref_id: "<team_id>"
date_start: "2026-03-01"
date_end: "2026-04-01"
granularity: "WEEKLY"
Step 2: Get Drilldown Data
Per-deployment detail for frequency:
Call MCP tool: harness_get
Parameters:
resource_type: "sei_dora_metric"
metric: "deployment_frequency_drilldown"
team_ref_id: "<team_id>"
date_start: "2026-03-01"
date_end: "2026-04-01"
granularity: "DAILY"
Per-failure detail for CFR:
Call MCP tool: harness_get
Parameters:
resource_type: "sei_dora_metric"
metric: "change_failure_rate_drilldown"
team_ref_id: "<team_id>"
date_start: "2026-03-01"
date_end: "2026-04-01"
granularity: "DAILY"
Step 3: Get Team Data
List teams:
Call MCP tool: harness_list
Parameters:
resource_type: "sei_team"
Get team details (integrations, developers, integration filters):
Call MCP tool: harness_list
Parameters:
resource_type: "sei_team_detail"
team_ref_id: "<team_id>"
aspect: "developers" # or "integrations" | "integration_filters"
Step 4: AI Metrics (Optional)
Call MCP tool: harness_get
Parameters:
resource_type: "sei_ai_adoption"
Related: sei_ai_impact, sei_ai_usage, sei_ai_raw_metric.
DORA Benchmarks
| Metric | Elite | High | Medium | Low |
|---|---|---|---|---|
| Deployment Frequency | Multiple/day | Weekly-Monthly | Monthly-6mo | 6mo+ |
| Lead Time | < 1 hour | 1 day-1 week | 1-6 months | 6mo+ |
| Change Failure Rate | < 5% | 5-10% | 10-15% | > 15% |
| MTTR | < 1 hour | < 1 day | 1 day-1 week | 1 week+ |
Report Format
## DORA Metrics Report
**Period:** <date range>
**Team:** <team or org>
### Performance Summary
| Metric | Value | Rating | Trend |
|--------|-------|--------|-------|
| Deployment Frequency | X/week | High | Improving |
| Lead Time | X hours | Elite | Stable |
| Change Failure Rate | X% | Medium | Needs attention |
| MTTR | X hours | High | Improving |
### Overall Rating: <Elite/High/Medium/Low>
### Recommendations
1. CFR at X% - invest in test automation and code review
2. Lead time trending up - look at PR review bottlenecks
3. Consider feature flags to decouple deploy from release
SEI Resource Types
| Resource Type | Operations | Description |
|---|---|---|
sei_dora_metric |
get (+ metric param) |
All 6 DORA variants: deployment_frequency, deployment_frequency_drilldown, lead_time, change_failure_rate, change_failure_rate_drilldown, mttr |
sei_team |
list, get | Team definitions |
sei_team_detail |
list (+ aspect param: developers / integrations / integration_filters) |
Per-team sub-resources |
sei_metric |
list, get | Generic metrics |
sei_productivity_metric |
get | Productivity metrics |
sei_org_tree |
list, get | Organization structure |
sei_org_tree_detail |
list, get | Org tree detail |
sei_business_alignment |
get | Business alignment |
sei_ai_adoption |
get | AI adoption metrics |
sei_ai_impact |
get | AI impact metrics |
sei_ai_usage |
get | AI usage metrics |
sei_ai_raw_metric |
get | Raw AI metrics |
Examples
- “How are we doing on DORA metrics?” - Call
sei_dora_metricfour times with each primarymetric - “Compare DORA across teams” - List
sei_team, then callsei_dora_metricperteam_ref_id - “What’s our deployment frequency trend?” - Get
sei_dora_metricwithmetric: deployment_frequency, then drilldown - “Show AI adoption metrics” - Get
sei_ai_adoptionand related AI resources
Performance Notes
- Always pass
team_ref_id,date_start,date_end,granularity— these are required. - Gather metrics across the full requested time range before generating the report. Partial data skews results.
- Compare metrics across multiple time periods to identify trends, not just snapshots.
Troubleshooting
No Metric Data
- Verify SEI integrations are configured (Git, CI/CD, issue tracking)
- Confirm
team_ref_idbelongs to an active SEI team (harness_list resource_type: sei_team) - Check the date range covers data the integrations have ingested
- Allow time for data collection and calculation after new integrations are added
Metrics Seem Incorrect
- Verify deployment detection rules in SEI settings
- Check failure classification criteria
- Review team member mappings via
sei_team_detail aspect: developers
Skill frontmatter
metadata: {"author" => "Harness", "version" => "2.1.0", "mcp-server" => "harness-mcp-v2"}
license: Apache-2.0
compatibility: Requires Harness MCP v2 server (harness-mcp-v2). All six DORA metric variants are served by a single consolidated `sei_dora_metric` resource — pick the variant via the `metric` parameter.
Work with this as data
Every skill here is available over the APIs.io API and to AI agents over MCP.