Live Dashboard from Coupler.io Data

A live artifact is a self-contained HTML page registered with Cowork that persists across sessions and re-fetches data from MCP connectors every time it opens. This skill covers the specific pitfalls of wiring one to a Coupler.io dataflow. Most generic widget guidance (CDN allowlist, sandboxing) lives in Cowork's create_artifact tool description — read that first. This skill captures the Coupler-specific traps that cost real time the first time someone hits them.

When to use

The user wants a re-openable view over Coupler.io data: KPIs, funnel, leaderboard, time series, comparison. They have an existing dataflow or are pointing at a data set in their Coupler workspace. The output is a .html file registered via mcp__cowork__create_artifact.

Process

Step 1 — Probe in chat first

Before writing a single line of HTML, run these chat-side calls and read the output. All Coupler operations go through the single dispatcher tool coupler: coupler({verb: "call", name: "<operation>", args: {...}}). Args are snake_case.

1. search-datasets({query: "<dataflow name>"}) to find the dataflow_id, last_dataset_snapshot_id, and the dataset id.
2. get-schema({dataset_snapshot_id}) and read ai_context carefully. It documents column meanings, the funnel order, the SQL conventions, and known caveats. Most pitfalls are flagged here.
3. get-data({dataset_snapshot_id, query: "SELECT * FROM data LIMIT 3"}) to see the actual row shape. Confirm what the schema claims.
4. get-data({dataset_snapshot_id, query: "SELECT DISTINCT col_X FROM data ORDER BY col_X"}) for any column you intend to expose as a filter dropdown — pre-compute the full enum.
5. Verify the stated grain. The schema's ai_context often claims one row per (entity × time), but real data sometimes has finer grain. Run:

   SELECT col_<id>, col_<time>, COUNT(*) cnt FROM data GROUP BY col_<id>, col_<time> HAVING cnt > 1 LIMIT 5
   

   If this returns rows, the grain is finer than advertised — the leaderboard query must GROUP BY <id> and SUM(...) everything, otherwise duplicates show up.

Read references/coupler-conventions.md once before writing SQL. It encodes Coupler's column/value conventions you will hit immediately.

Step 2 — Decide the refresh strategy

Two modes, pick by how stale the user can tolerate:

Mode	Behavior	Latency	When to use
Live snapshot (default)	Each artifact open calls list-datasets({dataflow_id}), takes last_dataset_snapshot_id, queries with get-data.	Fast (~1 RTT).	Daily checks, dashboards, any case where the user is fine with the last scheduled run.
Forced refresh (button)	Manual button calls run-dataflow({dataflow_id}), polls list-datasets every 5 s for up to 5 min until snapshot ID changes, then re-queries.	30 s – several min.	"I want fresh data right now" buttons. Never on every page load — too slow and wasteful.

Default to live-snapshot for load. Add a "Refresh data" button for forced refresh. Show last_success_run_at ("Last run: 5h ago") in the header so the user knows how stale things are.

Step 3 — Pick widget MCP tools

Only list MCP tools you actually call from the widget in the mcp_tools parameter of create_artifact. There is a single Coupler tool — the dispatcher — but its exact name is specific to this Cowork installation and must never be hardcoded. Find it yourself: look through your own available tools for the one matching mcp__<connector-id>__coupler, where <connector-id> is a UUID tied to this installation's registered Coupler MCP connector. Every installation has a different UUID — a skill that ships a literal one will silently call a tool name that doesn't exist anywhere else.

• Whatever you find, list it once in mcp_tools; it covers all operations.

Widget-side calls take the form:

window.cowork.callMcpTool("<your discovered mcp__<connector-id>__coupler tool name>",
  { verb: "call", name: "list-datasets", args: { dataflow_id: DATAFLOW_ID } })

Operations the widget uses: list-datasets (snapshot lookup — accepts dataflow_id alone), get-data (runs SQL), run-dataflow (only if a refresh button exists).

Do not use:

• search-datasets with only dataflow_id — its validator rejects this and returns "At least one of query, source, or name must be provided".
• get-dataflow for snapshot lookup — it returns config (sources/destinations) only, no snapshot ID.

Step 4 — Write the artifact HTML

Start from references/widget-template.html — it's a minimal working scaffold with the right boilerplate (Chart.js CDN tag, snapshot lookup, localStorage filter persistence, light-mode styling).

Required helpers (in references/snippets.js, copy-paste into the artifact):

1. Tolerant MCP response parser. Widget-side callMcpTool wraps results inconsistently — sometimes direct JSON, sometimes {content:[{type:"text",text:"..."}]}, sometimes prose-prefixed text like "Total datasets: 1\n\n[...]". Use the snippet's parseToolResult + tryJsonFromText — they handle all variants.
2. Timezone-safe month strings. Never use new Date(y, m, 1).toISOString().slice(0, 10) — for users east of UTC it returns the previous day, silently producing zero-row queries. Use the snippet's monthFirst / prevMonthFirst.
3. Quote stripping. Coupler stores string columns with embedded double quotes (e.g. col_1 = '"Looker Studio"'). SQL WHERE matches must include the quotes; display layer must strip them. Use the snippet's stripQuotes for display, and quote values in SQL like col_1 = '"${value}"'.
4. Run-and-poll. If the widget has a refresh button, copy the snippet's refreshData flow.
5. Chart.js canvas wrapping. With responsive: true, maintainAspectRatio: false, every <canvas> must sit inside a parent with explicit height (e.g. <div style="position:relative;height:260px;width:100%"><canvas/></div>). Without it, Chart.js silently collapses the canvas and renders a broken-image icon.
6. Allowed CDN libs only. Chart.js, Grid.js, Mermaid — exact tags from Cowork's create_artifact description (with integrity and crossorigin). Anything else must be inlined.
7. localStorage for filter/sort state. Persist the user's dropdown selections and sort order between opens — that's what makes a daily-check view feel right.

Step 5 — Verify in the widget runtime

Probing in chat verifies data shape but not widget-runtime behavior. The two failure modes that are invisible to chat-side testing:

• MCP-wrapper shape differences — same tool returns one shape in chat, another shape (often prose-prefixed text) in widgets.
• Timezone bugs — new Date(...).toISOString() behaves differently per user, and the symptom is silent zeros, not an error.

After registering the artifact, verify the rendered widget shows non-zero values for a known-populated month. If KPIs all read 0, suspect the timezone bug or the quote convention before suspecting the data.

Step 6 — Register the artifact

mcp__cowork__create_artifact({
  id: "<kebab-slug>",
  html_path: "<absolute path to the .html in outputs>",
  description: "<one-line summary of what it shows>",
  mcp_tools: ["<your discovered mcp__<connector-id>__coupler tool name, from Step 3>"]
})

For updates: mcp__cowork__update_artifact({id, html_path, update_summary}). Include a real update_summary — it's shown to the user in the approval prompt.

Rules & Edge Cases

• Always read ai_context from get-schema before writing SQL. It documents column quote conventions, the funnel order, and known caveats. Skipping this step is the most common time-waster.
• Verify dataset grain with a GROUP BY ... HAVING COUNT(*) > 1 probe. Don't trust the schema's stated grain. If the real grain is finer than advertised, your leaderboard will show duplicates.
• Never hardcode dataset_snapshot_id. It rotates on every dataflow run. Always resolve via list-datasets({dataflow_id}) (through the dispatcher) at load time.
• Default to live-snapshot loads, gate run-dataflow behind an explicit button. Triggering a fresh run on every artifact open turns a 1-second load into a 1-minute load. Users will hate it.
• Coupler's string-quoting convention is not stable. Some dataflows/snapshots store strings with embedded double quotes (col_X = '"Looker Studio"'), others do not (col_X = 'Looker Studio'). The convention can flip between snapshots of the same dataflow. Always probe SELECT * FROM data LIMIT 1 and look at the actual values before writing SQL filters. Defense in depth: write filters that match both conventions, e.g. col_X IN ('value', '"value"'). Keep stripQuotes on the display layer as a no-op safety net.
• Build YYYY-MM-01 strings manually. Never via toISOString(). Use ${y}-${String(m+1).padStart(2,"0")}-01. The timezone bug is silent — it produces zero-row queries, not errors.
• Chart.js canvases need a fixed-height parent. Wrap every <canvas> in <div style="position:relative;height:Npx;width:100%">. Otherwise canvases collapse to 0 and you get a broken-image fallback.
• Only the CDN libs listed in the create_artifact tool description load. Chart.js, Grid.js, Mermaid. Use the exact <script> tags including integrity and crossorigin. Other CDNs are blocked.
• The widget runs in light mode. Set :root { color-scheme: light } and use a light background with dark text.
• All Coupler operations go through the coupler dispatcher. mcp_tools lists only the dispatcher tool; widget calls pass {verb: "call", name, args} with snake_case args. The operation set can change — discover via {verb: "tools"} rather than trusting memory. The dispatcher's widget-runtime response wrapping has not been end-to-end verified; the tolerant parser in references/snippets.js is designed to absorb extra wrapping, but the first artifact built against the dispatcher must complete the Step 5 verification.
• mcp_tools array must list every tool the widget actually calls (for Coupler, that is just the dispatcher). Tools not listed will fail at runtime.
• Filter dropdown values: pre-compute, don't query in the widget. Pulling distinct values is slow and pointless when you already know the enum at build time.
• End-to-end widget verification is not optional. Probe-in-chat catches data-shape bugs but misses widget-wrapper and timezone bugs. Always reload the rendered widget once and confirm non-zero values for a known-populated period.
• table-layout: fixed collapses auto-width columns when other columns sum near the table width. If a column needs to be flexible but visible, give it an explicit width (e.g. 280px), not auto. Wrap the table in overflow-x:auto as a fallback.

Reference files

• references/coupler-conventions.md — Coupler quote convention, grain caveats, ai_context tips, MCP tool quirks. Read before writing SQL.
• references/snippets.js — Drop-in helpers: parseToolResult, tryJsonFromText, monthFirst, prevMonthFirst, stripQuotes, runQuery, fetchSnapshotInfo, refreshData. Copy what you need into the artifact.
• references/widget-template.html — Minimal working scaffold (snapshot lookup, KPI cards, Chart.js, localStorage state, refresh button). Start here for new artifacts.

Self-improvement

When the user flags a new Coupler quirk or widget-runtime gotcha, append it to Rules & Edge Cases. When the user approves a finished artifact that demonstrates a useful pattern (e.g. a clean way to render a stacked-bar funnel with destination breakdown), copy it to references/examples/<descriptive-name>.html for future runs to anchor on.