jira-sprint-dashboard

Jira Sprint Dashboard

Build a focused dashboard that helps an engineering manager, tech lead, or senior engineer see current Jira work quickly enough to decide what needs attention. The output is a dashboard, not a prose report and not a generic health score.

This skill is read-only by default. Do not create, update, transition, assign, or comment on Jira work items unless the user explicitly asks for a write action after reviewing the dashboard.

Output Mode

Use the richest dashboard renderer supported by the current environment. The dashboard content, claims, counts, and source appendix must stay consistent across renderers; only the presentation changes.

Choose the renderer in this order:

1. Cursor Canvas, if running in Cursor with Canvas support.
2. Interactive artifact, if the current agent supports HTML, React, or similar artifact output.
3. Static HTML file, if file creation is available and useful.
4. Markdown dashboard, if no richer visual renderer is available.
5. Structured JSON plus concise summary, only if visual rendering is impossible.

Do not mention that Cursor Canvas is unavailable unless the user specifically asked for Cursor Canvas. If the user asked for a dashboard generally, use the best available renderer without apologizing for the environment.

Cursor Canvas Renderer

Use this section only when running in Cursor with Canvas support.

Read ~/.cursor/skills-cursor/canvas/SKILL.md before writing canvas code. If you need exact exports or prop shapes, read the files in ~/.cursor/skills-cursor/canvas/sdk/.

Canvas constraints:

• Create one .canvas.tsx file in the Cursor canvases directory.
• Import only from cursor/canvas. Do not import react, CSSProperties, JSX, Atlaskit, or other packages.
• Embed Jira data inline in the canvas; do not fetch from the canvas.
• Prefer Canvas primitives such as Stack, Grid, Card, Stat, Table, Pill, Callout, UsageBar, BarChart, LineChart, PieChart, and Code over raw HTML.
• Use useHostTheme() for custom styles. Do not hardcode hex colors, gradients, box shadows, ADS variables, unsupported CSS frameworks, or @atlaskit/*.
• Do not publish or share the canvas unless the user asks.

Portable Renderers

Use this section when Cursor Canvas is unavailable.

For an interactive artifact renderer:

• Render the same dashboard model as an interactive artifact.
• Prefer tables, compact charts, stat rows, and collapsible source details.
• Keep interactions lightweight: filtering, expanding details, or switching chart/table views is fine; do not require live Jira fetching from the artifact.

For static HTML:

• Create a self-contained dashboard file with embedded data.
• Use responsive layout, accessible tables, and simple chart-like visuals when chart libraries are unavailable.
• Do not fetch Jira data from the HTML file.

For Markdown:

• Preserve the dashboard order.
• Use compact tables for stats, owner load, risks, highest-priority work, and source appendix.
• Use textual chart substitutes only when they remain honest, such as counts, percentages, and simple bars.
• Avoid turning the output into a long prose report.

For JSON fallback:

• Return the normalized dashboard model.
• Include a short human-readable summary with the highest-signal risks and the source scope.

Get The Scope

Do not guess the Jira scope. If the user does not provide a project key, space key, board, sprint, filter, JQL, work item keys, or Jira URL, stop and ask for one. A dashboard from a random visible project or guessed team context is worse than no dashboard.

If the user gives a project or space key but no sprint, board, or filter, start with the Jira JQL project field and the user's key:

project = "SPACE_KEY" AND sprint in openSprints() ORDER BY Rank ASC

If the open sprint result is empty, stale, or misleading, switch to snapshot mode and say so in a compact caveat below the top bar:

project = "SPACE_KEY" AND statusCategory != Done ORDER BY priority DESC, updated ASC
project = "SPACE_KEY" AND updated >= -60d ORDER BY updated DESC

Use a 60-day recent movement window by default unless the user asks for another period.

Query Jira

Use read-only Jira search. Request only fields needed for the dashboard and tolerate missing fields.

Useful fields: key, summary, status, statusCategory, assignee, priority, issuetype, created, updated, resolutiondate, duedate, parent, issuelinks, labels, components, fixVersions, sprint, and any available estimate/story point field.

Start with maxResults: 100. For complete sprint, board, or filter dashboards, paginate until the scope is complete or too large for useful work-item-level rendering.

Default to one complete paginated scope query. Derive ordinary dashboard signals locally from the returned work item set instead of issuing separate JQL calls for each signal.

Derive these locally when the scope query returned the required fields:

• Recently completed from statusCategory = Done and resolutiondate.
• Aging unfinished from statusCategory != Done and updated.
• Unowned unfinished from statusCategory != Done and empty assignee.
• High-priority unfinished from statusCategory != Done and priority.
• Status or label blockers from status, statusCategory, and labels.
• Owner load, stale work, due date risk, and planning gaps from the normalized scope dataset.

Use targeted follow-up queries only when they are needed to support a visible claim that cannot be derived safely from the scope data, when the scope is too large for useful local processing, or when the user asks for an audit-style dashboard with exact evidence per signal.

Rule of thumb:

• Small or medium sprint dashboard: prefer one full paginated scope query, with at most one targeted blocker-text or dependency-status follow-up when needed.
• Large scope dashboard: use narrower follow-up queries when pulling and processing the full work-item set would be slow or low-value.
• Evidence-heavy review: multiple focused queries are acceptable when the exact JQL evidence matters more than minimizing calls.

Examples of targeted follow-up queries, only when justified:

• Recently completed: <scope> AND statusCategory = Done ORDER BY resolutiondate DESC
• Aging unfinished: <scope> AND statusCategory != Done AND updated <= -3d ORDER BY updated ASC
• Unowned unfinished: <scope> AND statusCategory != Done AND assignee is EMPTY ORDER BY priority DESC, updated ASC
• High-priority unfinished: <scope> AND statusCategory != Done AND priority in (Highest, High) ORDER BY priority DESC, updated ASC
• Blocked signal: <scope> AND statusCategory != Done AND (status = Blocked OR text ~ "blocked" OR labels in (blocked, blocker)) ORDER BY priority DESC, updated ASC

Do not make negative claims such as "no blockers" or "no dependencies" unless the source appendix shows the query or returned field coverage that supports the claim. If only status and labels were checked for blockers, say that no status/label blockers were found rather than claiming there are no blockers. If a signal was not checked, say so.

For derived signals, cite the base scope JQL and field coverage in the source appendix instead of inventing separate support queries. Include additional JQL only for targeted follow-up queries that were actually run.

For work item links (issuelinks), fetch linked work item status/category when possible. If linked details are unavailable, show dependency status as unknown rather than resolved.

Normalize

Before designing the output, create a compact renderer-independent work item model with:

• Key, URL, summary, type, status, status category, priority
• Assignee display name or Unassigned
• Owner status as active, inactive, unknown, or unassigned
• Created age, updated age, resolution age when done, due date distance
• Parent/epic/workstream, sprint, estimate, components, versions, labels
• Linked work item keys, direction, link type, and linked status when available

Derived signals should stay explainable from Jira facts: done, active, not started, stale, very stale, blocked, unowned, inactive owner, time-sensitive, support-impacting, cross-space dependency, and missing planning data. Mark weak text-only signals as inferred.

Dashboard Model

Create a dashboard model before rendering. Every renderer should use this same model.

Include:

• Context metadata: title, project or space, sprint, board, filter, JQL, window, query timestamp, and mode.
• Four top stats: committed or total scope, done or completed, active or in progress, and needs attention.
• Scope caveat, only when sprint data is missing, mixed, stale, or blended with recent project movement.
• Optional capacity or commitment segments, only when real data exists.
• Optional chart data, only when categories, values, units, and time ranges are available.
• Owner load and gaps.
• Risk and attention items.
• Highest-priority work item table.
• Recently completed work.
• Source appendix with exact JQL, field coverage, assumptions, and the composition of Needs attention.

Do not invent data to fill the model. Empty or unsupported sections should be omitted.

Dashboard Shape

Keep the visible dashboard simple and deterministic. When the data exists, broadly follow this order:

1. Compact context header

   • Show title plus project, space, board, sprint, or window metadata.
   • Keep it short. Do not put queries, field coverage, or executive-summary prose at the top.

2. Four-stat top bar

   • Show exactly four stat values.
   • Default to committed/total scope, done/completed, active/in progress, and needs attention.
   • Use work item counts when story points are unavailable.
   • Needs attention should combine the highest-signal risks: blocked, stale, unassigned, time-sensitive, or unresolved linked work.
   • Put secondary counts below the fold only when they change the readout.

3. Scope caveat, only when needed

   • Use one compact caveat below the top bar when sprint data is missing, mixed, stale, or blended with recent project movement.
   • Keep it to 1 to 2 short sentences.

4. Capacity or commitment bar

   • Render a capacity or commitment visual only when capacity, commitment, or allocation segment data is available.
   • Skip it rather than inventing capacity, segment, or buffer values.

5. Sprint charts

   • If available, render remaining work over time as a line chart.
   • Beside it, render status distribution as a pie chart or compact status visual.
   • Below those, render resolved/completed per working day as a bar chart.
   • Skip any chart whose categories, values, units, or time range are missing. Never render placeholder, sample, empty, or guessed charts.

6. Owner load and gaps

   • Show active, stale, blocked, support-impacting, and done counts by assignee.
   • Include unassigned, inactive-owner, and unknown-owner-status buckets.
   • Keep it compact; prefer a small table or bar chart over per-owner cards.

7. Risk and attention

   • Place this below owner load.
   • Include only the work items most likely to need manager or lead attention.
   • For each item, show key, reason, evidence, owner, age, and next question.
   • Use a callout or highlighted row for the single highest delivery risk when one stands out.

8. Highest-priority work item table

   • Include a compact table of top sprint work items or top attention items.
   • Do not render every low-signal work item by default.

9. Recently completed and optional detail

   • If recently completed work exists, put it in a collapsed section or compact table below the main readout.
   • Workstream grouping and dependencies should appear only when they change what the viewer should inspect next.
   • Keep dependencies to unresolved or unknown-status linked work by default.

10. Source appendix

    • Put exact JQL, query timestamps, field coverage, assumptions, and the composition of Needs attention at the bottom.

If the full data set is unavailable, preserve the same broad order and omit the sections or charts that cannot be rendered honestly.

Content And Style

• Use charts and tables where they beat paragraphs.
• Follow the reference layout order when the data supports it; skip unsupported charts instead of changing the whole page shape.
• Keep work item summaries short; avoid full descriptions unless a short excerpt is needed to explain impact.
• Tie every recommendation or next question to work item keys or aggregate counts.
• Separate Jira facts from derived or inferred signals.
• Use semantic tones where the renderer supports them: success for done, warning for stale/deadline risk, danger for blocked/overdue/severe risk, info for caveats/linked work, and neutral for low-signal facts.
• Pair color with labels. Prefer work item key links over large buttons.
• Keep the first screen focused on status and attention, not process notes.

Renderer-Specific Style

For Cursor Canvas:

• Use Canvas components and host theme styles.
• Keep the top area compact: context header followed by exactly four stats.
• Prefer Canvas tables and charts over custom layout code.

For interactive artifacts or static HTML:

• Use a restrained dashboard layout with compact cards, tables, and simple charts.
• Keep text readable on mobile and desktop.
• Use accessible labels for chart substitutes and status colors.
• Keep source details below the main dashboard.

For Markdown:

• Use short section headings.
• Prefer tables over paragraphs.
• Keep caveats and recommendations concise.
• Put source queries at the bottom.

Self-Check

Before returning:

• Scope came from the user or a provided URL; missing or ambiguous scope was clarified before querying.
• The selected renderer matches the current environment's capabilities.
• Cursor Canvas instructions were used only when Cursor Canvas is available.
• If Cursor Canvas was used, the canvas imports only from cursor/canvas.
• The top area is a compact context header followed by exactly four stats.
• There is no query list, field coverage, or executive summary above the top bar.
• Ordinary signals were derived from the paginated scope query when possible; targeted follow-up queries were used only when they supported a visible claim that the scope data could not safely support.
• Counts reconcile with the queried work item set.
• Empty sections are omitted.
• Charts are rendered only when their categories, values, units, and time ranges are available.
• Risk labels are explainable from visible Jira data.
• Source appendix includes exact JQL and field coverage for visible claims.
• No Jira write tools were used.