一键导入
ground
Full end-to-end pipeline — collect all mirror data (8 steps), run all analysis agents, produce grounding documents.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Full end-to-end pipeline — collect all mirror data (8 steps), run all analysis agents, produce grounding documents.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Capture mirror bundles from OpenObserve — health, schemas, alerts, functions, traces, supplementary data, config chains, screenshots, and DOM.
Run multi-agent analysis pipeline on collected mirror data — baseline, 3 per-dashboard analysts (structure, data, UX), and synthesizer.
| name | ground |
| description | Full end-to-end pipeline — collect all mirror data (8 steps), run all analysis agents, produce grounding documents. |
| license | MIT |
| metadata | {"author":"musicofhel","version":"0.2.0","category":"pipeline"} |
Use this skill for a complete end-to-end run: collection through grounding document production. This combines the collect and analyze skills into a single orchestrated pipeline.
Phase 1: Collection (automated — 8 steps)
├── dm-health → output/_baseline/oo-health.json, oo-config.json, oo-cluster.json
├── dm-schema → output/_baseline/stream-schema.json, cross-dashboard-map.json
├── dm-alerts → output/_baseline/alerts.json, alert-drift.json, alert-schema-coverage.json, ...
├── dm-functions → output/_baseline/functions.json, pipelines.json, pipeline-streams.json, ...
├── dm-traces → output/_baseline/trace-services.json, trace-operations.json, trace-structure.json, ...
├── dm-supplementary → output/_baseline/saved-views.json, reports.json, annotations.json, folders.json
├── dm-chain → output/*/config/{source,transformed,sent,stored,chain-diff}
└── dm-collect → output/*/screenshots, dom, api, timing, meta
Phase 2: Baseline Analysis (1 agent)
└── baseline agent → output/_baseline/baseline-report.md
Phase 3: Per-Dashboard Analysis (3 agents × N dashboards)
├── Analyst A (Structure) → output/*/analyst-structure.md
├── Analyst B (Data) → output/*/analyst-data.md
└── Analyst C (UX) → output/*/analyst-ux.md
Phase 4: Synthesis (1 agent × N dashboards)
└── Synthesizer → output/*/grounding.md
For N dashboards: 1 baseline + 3N analysts + N synthesizers = 4N + 1 agents
Example: 6 dashboards = 25 agents total
OPENOBSERVE_URLcd ~/dashboard-mirror && uv sync && uv run playwright install chromium completedDM_CONFIG_DIRcd ~/dashboard-mirror
# Recommended: single command runs all 8 steps
uv run dm-collect-all # Full pipeline (~4-6 min)
uv run dm-collect-all --skip-playwright # API-only (~30-40s)
# Or run individual collectors:
uv run dm-health
uv run dm-schema
uv run dm-alerts
uv run dm-functions
uv run dm-traces
uv run dm-supplementary
uv run dm-chain --config-dir ~/dev-loop/config/dashboards
uv run dm-collect
Baseline first, then per-dashboard analysis, then synthesis. See the analyze skill for details.
The final deliverable per dashboard is output/<slug>/grounding.md — a comprehensive, fact-based, screenshot-referenced document describing exactly what the dashboard looks like and what state it's in.
To refresh a single dashboard:
uv run dm-collect --dashboard <slug>
Then re-run the 3 analysts + synthesizer for that slug only.
To refresh API-only data (alerts, functions, traces, etc.) without re-running Playwright:
uv run dm-collect-all --skip-playwright