[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DCFJSEKHK1CSRHJKBFYCMS":3,"skill-same:01M6DCFJSEKHK1CSRHJKBFYCMS":73},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":41,"linkOnly":42,"markdownContent":43,"markdownBody":44,"frontMatter":45,"refName":51,"commitSha":52,"skillDirectory":53,"forksCount":54,"repositoryHtmlUrl":55,"repositoryHomepageUrl":6,"ownerHtmlUrl":56,"ownerBlogUrl":6,"ownerDescription":57,"updatedAt":58,"install":59,"resources":72},"01M6DCFJSEKHK1CSRHJKBFYCMS","dora-metrics",null,"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.","zapabob\u002FSkills","zapabob","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130830376?v=4","01M6DBMYZAGRTFQDSQYW3W764P","峯岸 亮","01M6DBMZ3GKDSJ01NZ9XTZD7JD",2,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Farchive\u002Fskill-md-reviewed\u002Fsha256\u002F14\u002F140978c4171c2667f509d55cdfd7f0836558f25b65a163b7ded66b4f9b1c1861\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],"dora metrics","metrics","engineering","time","reports","use","user","pick","team","mttr","MCP","server","harness","generate","deployment","change","performance","2026-11-10 10:12:30",false,"---\r\nname: dora-metrics\r\ndescription: 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.\r\nmetadata:\r\n  author: Harness\r\n  version: 2.1.0\r\n  mcp-server: harness-mcp-v2\r\nlicense: Apache-2.0\r\ncompatibility: 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.\r\n---\r\n\r\n# DORA Metrics\r\n\r\nGenerate DORA metrics reports using Harness Software Engineering Insights (SEI) via MCP.\r\n\r\n## Instructions\r\n\r\nAll DORA metrics are served by a single resource type: `sei_dora_metric`. Pass the `metric` parameter to select the variant:\r\n\r\n- `deployment_frequency`\r\n- `deployment_frequency_drilldown`\r\n- `lead_time`\r\n- `change_failure_rate`\r\n- `change_failure_rate_drilldown`\r\n- `mttr`\r\n\r\nRequired inputs on every DORA call: `team_ref_id`, `date_start`, `date_end`, `granularity` (DAILY | WEEKLY | MONTHLY).\r\n\r\n### Step 1: Get a DORA Metric\r\n\r\nDeployment Frequency:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"deployment_frequency\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"WEEKLY\"\r\n```\r\n\r\nLead Time for Changes:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"lead_time\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"WEEKLY\"\r\n```\r\n\r\nChange Failure Rate:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"change_failure_rate\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"WEEKLY\"\r\n```\r\n\r\nMean Time to Recovery:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"mttr\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"WEEKLY\"\r\n```\r\n\r\n### Step 2: Get Drilldown Data\r\n\r\nPer-deployment detail for frequency:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"deployment_frequency_drilldown\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"DAILY\"\r\n```\r\n\r\nPer-failure detail for CFR:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"change_failure_rate_drilldown\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"DAILY\"\r\n```\r\n\r\n### Step 3: Get Team Data\r\n\r\nList teams:\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"sei_team\"\r\n```\r\n\r\nGet team details (integrations, developers, integration filters):\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"sei_team_detail\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  aspect: \"developers\"   # or \"integrations\" | \"integration_filters\"\r\n```\r\n\r\n### Step 4: AI Metrics (Optional)\r\n\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_ai_adoption\"\r\n```\r\n\r\nRelated: `sei_ai_impact`, `sei_ai_usage`, `sei_ai_raw_metric`.\r\n\r\n## DORA Benchmarks\r\n\r\n| Metric | Elite | High | Medium | Low |\r\n|--------|-------|------|--------|-----|\r\n| Deployment Frequency | Multiple\u002Fday | Weekly-Monthly | Monthly-6mo | 6mo+ |\r\n| Lead Time | \u003C 1 hour | 1 day-1 week | 1-6 months | 6mo+ |\r\n| Change Failure Rate | \u003C 5% | 5-10% | 10-15% | > 15% |\r\n| MTTR | \u003C 1 hour | \u003C 1 day | 1 day-1 week | 1 week+ |\r\n\r\n## Report Format\r\n\r\n```\r\n## DORA Metrics Report\r\n\r\n**Period:** \u003Cdate range>\r\n**Team:** \u003Cteam or org>\r\n\r\n### Performance Summary\r\n\r\n| Metric | Value | Rating | Trend |\r\n|--------|-------|--------|-------|\r\n| Deployment Frequency | X\u002Fweek | High | Improving |\r\n| Lead Time | X hours | Elite | Stable |\r\n| Change Failure Rate | X% | Medium | Needs attention |\r\n| MTTR | X hours | High | Improving |\r\n\r\n### Overall Rating: \u003CElite\u002FHigh\u002FMedium\u002FLow>\r\n\r\n### Recommendations\r\n1. CFR at X% - invest in test automation and code review\r\n2. Lead time trending up - look at PR review bottlenecks\r\n3. Consider feature flags to decouple deploy from release\r\n```\r\n\r\n## SEI Resource Types\r\n\r\n| Resource Type | Operations | Description |\r\n|--------------|-----------|-------------|\r\n| `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 |\r\n| `sei_team` | list, get | Team definitions |\r\n| `sei_team_detail` | list (+ `aspect` param: developers \u002F integrations \u002F integration_filters) | Per-team sub-resources |\r\n| `sei_metric` | list, get | Generic metrics |\r\n| `sei_productivity_metric` | get | Productivity metrics |\r\n| `sei_org_tree` | list, get | Organization structure |\r\n| `sei_org_tree_detail` | list, get | Org tree detail |\r\n| `sei_business_alignment` | get | Business alignment |\r\n| `sei_ai_adoption` | get | AI adoption metrics |\r\n| `sei_ai_impact` | get | AI impact metrics |\r\n| `sei_ai_usage` | get | AI usage metrics |\r\n| `sei_ai_raw_metric` | get | Raw AI metrics |\r\n\r\n## Examples\r\n\r\n- \"How are we doing on DORA metrics?\" - Call `sei_dora_metric` four times with each primary `metric`\r\n- \"Compare DORA across teams\" - List `sei_team`, then call `sei_dora_metric` per `team_ref_id`\r\n- \"What's our deployment frequency trend?\" - Get `sei_dora_metric` with `metric: deployment_frequency`, then drilldown\r\n- \"Show AI adoption metrics\" - Get `sei_ai_adoption` and related AI resources\r\n\r\n## Performance Notes\r\n\r\n- Always pass `team_ref_id`, `date_start`, `date_end`, `granularity` — these are required.\r\n- Gather metrics across the full requested time range before generating the report. Partial data skews results.\r\n- Compare metrics across multiple time periods to identify trends, not just snapshots.\r\n\r\n## Troubleshooting\r\n\r\n### No Metric Data\r\n- Verify SEI integrations are configured (Git, CI\u002FCD, issue tracking)\r\n- Confirm `team_ref_id` belongs to an active SEI team (`harness_list resource_type: sei_team`)\r\n- Check the date range covers data the integrations have ingested\r\n- Allow time for data collection and calculation after new integrations are added\r\n\r\n### Metrics Seem Incorrect\r\n- Verify deployment detection rules in SEI settings\r\n- Check failure classification criteria\r\n- Review team member mappings via `sei_team_detail aspect: developers`\r\n","# DORA Metrics\r\n\r\nGenerate DORA metrics reports using Harness Software Engineering Insights (SEI) via MCP.\r\n\r\n## Instructions\r\n\r\nAll DORA metrics are served by a single resource type: `sei_dora_metric`. Pass the `metric` parameter to select the variant:\r\n\r\n- `deployment_frequency`\r\n- `deployment_frequency_drilldown`\r\n- `lead_time`\r\n- `change_failure_rate`\r\n- `change_failure_rate_drilldown`\r\n- `mttr`\r\n\r\nRequired inputs on every DORA call: `team_ref_id`, `date_start`, `date_end`, `granularity` (DAILY | WEEKLY | MONTHLY).\r\n\r\n### Step 1: Get a DORA Metric\r\n\r\nDeployment Frequency:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"deployment_frequency\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"WEEKLY\"\r\n```\r\n\r\nLead Time for Changes:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"lead_time\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"WEEKLY\"\r\n```\r\n\r\nChange Failure Rate:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"change_failure_rate\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"WEEKLY\"\r\n```\r\n\r\nMean Time to Recovery:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"mttr\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"WEEKLY\"\r\n```\r\n\r\n### Step 2: Get Drilldown Data\r\n\r\nPer-deployment detail for frequency:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"deployment_frequency_drilldown\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"DAILY\"\r\n```\r\n\r\nPer-failure detail for CFR:\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_dora_metric\"\r\n  metric: \"change_failure_rate_drilldown\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  date_start: \"2026-03-01\"\r\n  date_end: \"2026-04-01\"\r\n  granularity: \"DAILY\"\r\n```\r\n\r\n### Step 3: Get Team Data\r\n\r\nList teams:\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"sei_team\"\r\n```\r\n\r\nGet team details (integrations, developers, integration filters):\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"sei_team_detail\"\r\n  team_ref_id: \"\u003Cteam_id>\"\r\n  aspect: \"developers\"   # or \"integrations\" | \"integration_filters\"\r\n```\r\n\r\n### Step 4: AI Metrics (Optional)\r\n\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"sei_ai_adoption\"\r\n```\r\n\r\nRelated: `sei_ai_impact`, `sei_ai_usage`, `sei_ai_raw_metric`.\r\n\r\n## DORA Benchmarks\r\n\r\n| Metric | Elite | High | Medium | Low |\r\n|--------|-------|------|--------|-----|\r\n| Deployment Frequency | Multiple\u002Fday | Weekly-Monthly | Monthly-6mo | 6mo+ |\r\n| Lead Time | \u003C 1 hour | 1 day-1 week | 1-6 months | 6mo+ |\r\n| Change Failure Rate | \u003C 5% | 5-10% | 10-15% | > 15% |\r\n| MTTR | \u003C 1 hour | \u003C 1 day | 1 day-1 week | 1 week+ |\r\n\r\n## Report Format\r\n\r\n```\r\n## DORA Metrics Report\r\n\r\n**Period:** \u003Cdate range>\r\n**Team:** \u003Cteam or org>\r\n\r\n### Performance Summary\r\n\r\n| Metric | Value | Rating | Trend |\r\n|--------|-------|--------|-------|\r\n| Deployment Frequency | X\u002Fweek | High | Improving |\r\n| Lead Time | X hours | Elite | Stable |\r\n| Change Failure Rate | X% | Medium | Needs attention |\r\n| MTTR | X hours | High | Improving |\r\n\r\n### Overall Rating: \u003CElite\u002FHigh\u002FMedium\u002FLow>\r\n\r\n### Recommendations\r\n1. CFR at X% - invest in test automation and code review\r\n2. Lead time trending up - look at PR review bottlenecks\r\n3. Consider feature flags to decouple deploy from release\r\n```\r\n\r\n## SEI Resource Types\r\n\r\n| Resource Type | Operations | Description |\r\n|--------------|-----------|-------------|\r\n| `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 |\r\n| `sei_team` | list, get | Team definitions |\r\n| `sei_team_detail` | list (+ `aspect` param: developers \u002F integrations \u002F integration_filters) | Per-team sub-resources |\r\n| `sei_metric` | list, get | Generic metrics |\r\n| `sei_productivity_metric` | get | Productivity metrics |\r\n| `sei_org_tree` | list, get | Organization structure |\r\n| `sei_org_tree_detail` | list, get | Org tree detail |\r\n| `sei_business_alignment` | get | Business alignment |\r\n| `sei_ai_adoption` | get | AI adoption metrics |\r\n| `sei_ai_impact` | get | AI impact metrics |\r\n| `sei_ai_usage` | get | AI usage metrics |\r\n| `sei_ai_raw_metric` | get | Raw AI metrics |\r\n\r\n## Examples\r\n\r\n- \"How are we doing on DORA metrics?\" - Call `sei_dora_metric` four times with each primary `metric`\r\n- \"Compare DORA across teams\" - List `sei_team`, then call `sei_dora_metric` per `team_ref_id`\r\n- \"What's our deployment frequency trend?\" - Get `sei_dora_metric` with `metric: deployment_frequency`, then drilldown\r\n- \"Show AI adoption metrics\" - Get `sei_ai_adoption` and related AI resources\r\n\r\n## Performance Notes\r\n\r\n- Always pass `team_ref_id`, `date_start`, `date_end`, `granularity` — these are required.\r\n- Gather metrics across the full requested time range before generating the report. Partial data skews results.\r\n- Compare metrics across multiple time periods to identify trends, not just snapshots.\r\n\r\n## Troubleshooting\r\n\r\n### No Metric Data\r\n- Verify SEI integrations are configured (Git, CI\u002FCD, issue tracking)\r\n- Confirm `team_ref_id` belongs to an active SEI team (`harness_list resource_type: sei_team`)\r\n- Check the date range covers data the integrations have ingested\r\n- Allow time for data collection and calculation after new integrations are added\r\n\r\n### Metrics Seem Incorrect\r\n- Verify deployment detection rules in SEI settings\r\n- Check failure classification criteria\r\n- Review team member mappings via `sei_team_detail aspect: developers`\r\n",{"name":5,"license":15,"metadata":46,"description":7,"compatibility":50},{"author":47,"version":48,"mcp-server":49},"Harness","2.1.0","harness-mcp-v2","Requires Harness MCP v2 server (harness-mcp-v2). 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