Create Honeycomb Board

作者 honeycombiob169d7d1c76a無授權條款27 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫2 週前更新

Design and then create a board (dashboard) in Honeycomb with queries and SLOs. Trigger phrases: "create a board", "make a board", "build a dashboard", "create a Honeycomb board", "make a dashboard in Honeycomb", "set up a board", "dashboard for my service", "visualize service health", "golden signals dashboard", "set up monitoring board", or any request to design and create or build a Honeycomb board or dashboard.

AI 產生的概覽

透過 MCP 工具設計並建立包含查詢、SLO 與文字面板的 Honeycomb 看板(儀表板)。

功能
引導代理設計 Honeycomb 看板:蒐集 SLO、瀏覽工作區資料集與欄位、草擬候選查詢、執行查詢並規劃 12 欄版面。接著向使用者展示完整的看板方案以供確認,並使用 create_board MCP 工具建立看板,最後回傳看板連結。產出物是帶有查詢、SLO 與文字面板的 Honeycomb 儀表板,以及標籤與選用的預設篩選器。
適用情境
當使用者要求建立或建構 Honeycomb 看板或儀表板時使用,例如服務健康、黃金指標、功能使用情形或事件看板。適用於視覺化服務健康或在 Honeycomb 中設定監控看板的需求。
執行需求
需要 Honeycomb MCP 工具(create_board、run_query、get_query_results,以及工作區、環境、資料集、欄位、查詢、SLO、觸發條件與看板列表相關工具)和檔案讀取工具(Read、Grep、Glob)。需要存取 Honeycomb 環境及其資料集。不附帶指令碼,內含兩份參考文件。

Create a Honeycomb Board

Build a board (dashboard) in Honeycomb using the create_board MCP tool. There is no update tool — define it well before creating.

When building a board, think about the purpose and time frame involved. Some examples:

  • a board for a service. This should be timeless, looking at the service's health, performance, and business metrics. Do not do any problem diagnosis or investigation when building this board. Do not express opinions or summarize graphs in text panels. The board should be a representation of the service's health at whatever moment someone looks at it.
  • a board for a feature. This should look at the feature's usage trends, and its impact on the business. This board would have a time frame of 7 days, and would not include any infrastructure metrics or service dependencies.
  • a board for a problem. This might be created during an incident, or afterward. This one would have a time frame specific to the incident. It would include investigations, and your opinions about what is happening. Patterns of what to look for are appropriate here.

Workflow

Gather SLOs

Use get_slos to list SLOs in the environment. Relevant SLOs will go on the board as slo panels.

Gather descriptive context

Look at the code and docs (using Read/Grep/Glob) to understand the service or feature. Use this to write a text panel. Link to GitHub or documentation if you can.

This will vary greatly depending on the purpose of the board.

Description of the application and link to the code - great for a service board.

What is the feature, and what business impact does it have? - great for a feature board.

What is the problem, and what is the impact? What patterns do we see? - great for a problem board.

Build candidate queries

Get Honeycomb context: Call get_workspace_context for available environments. Use get_environment to find datasets — each dataset corresponds to an OTEL_SERVICE_NAME.

Code context: Look at the language and any custom attributes (often prefixed app.). Custom fields are prime candidates for breakdowns and business metrics.

Discover columns: Use find_columns or get_dataset_columns. Pay special attention to non-standard columns — those are specific to the application.

Find queries: Use find_queries to see what people have already queried. Check get_triggers for what they alert on — those indicate what matters.

Time range: Default to 2 hours. Use 8–24 hours for lower-volume services. Use 7 days for feature usage boards. Keep it consistent across all panels.

Aim for 6–12 graphs. Stat panels are bonus — they don't count against this limit.

List your candidate queries for the user with reasons before running them. See ${CLAUDE_PLUGIN_ROOT}/skills/create-honeycomb-board/references/board-queries.md for what to include and how to write each kind.

Run and check queries

Use run_query for each candidate query. Each result returns a query run PK (like QR-abc123) — you'll use this as the panel id when building the board.

Fix errors. Eliminate queries that return no interesting results.

Plan the layout

Think about visual flow and how to make the board expressive. The board uses a 12-column grid — stat panels can sit side-by-side, a heatmap deserves full width, breakdowns benefit from extra height. See ${CLAUDE_PLUGIN_ROOT}/skills/create-honeycomb-board/references/board-layout.md for sizing examples.

Consider preset_filters if viewers will want to slice the board interactively (by route, region, account tier, etc.).

Show the proposed board to the user — always, without exception

For each panel, display:

  • Text panels: Show the full markdown content that will appear on the board. The user needs to review the exact wording before creation since boards can't be updated.
  • SLO panels: Show the SLO name, target, and current compliance.
  • Query panels: Show the name, description, chart type, display style, and a link to the query (the query_url from the run_query result metadata). Briefly describe what the results showed.
  • Planned layout (sizing and groupings)
  • Tags: Display the tags you plan to add to the board.
  • Any preset filters

End with: "Here's the board I'd create. Shall I go ahead?"

This step is non-negotiable. If the user says "just create it", "I trust you", or "skip the preview" — show the plan anyway. The user cannot meaningfully confirm something they haven't seen. There is no way to update a board after creation; the only fix is to delete it and start over. Showing the plan first protects them even when they think they don't need it.

The one exception: if the user has already reviewed and approved a specific plan in this conversation, you may proceed.

Create the board

Call create_board with a panels array. Every panel requires a type field — "query", "slo", or "text" — that determines what other fields apply. See ${CLAUDE_PLUGIN_ROOT}/skills/create-honeycomb-board/references/board-layout.md for the full field reference.

json
{  "environment_slug": "production",  "name": "Checkout Service",  "description": "...",  "panels": [    {      "type": "text",      "content": "## Checkout Service\nOwned by Platform team. [Source](https://github.com/...)"    },    {      "type": "slo",      "id": "SLO-abc123",      "size": { "width": 4 }    },    {      "type": "query",      "id": "QR-abc123",      "name": "Request Rate",      "chart_type": "stat",      "display_style": "chart",      "size": { "width": 4 }    },    {      "type": "query",      "id": "QR-def456",      "name": "Error Rate",      "chart_type": "stat",      "display_style": "chart",      "size": { "width": 4 }    },    {      "type": "query",      "id": "QR-ghi789",      "name": "Latency Distribution",      "description": "Overall request latency as a heatmap",      "chart_type": "default",      "display_style": "chart",      "size": { "width": 12, "height": 3 }    }  ],  "preset_filters": [{ "column": "http.route", "alias": "Route" }],  "tags": ["team:platform", "tier:critical"]}

Follow up

Link the user to the board.

Cross-References

  • For query construction patterns and calculated fields: query-patterns skill
  • For SLO interpretation and burn alert design: slos-and-triggers skill

來源與署名

來源:honeycombio/agent-skill位於honeycomb/skills/create-honeycomb-board提交b169d7d

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