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execution-transparency-dashboard

Design dashboards for migrations and runtimes. Use for authority drift, verifier status, burn-down, runtime health, or pain panels. NOT for vanity analytics, ad hoc charts, or duplicate reporting.

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含まれるファイル(7)

  • SKILL.md5.3 KB
  • affordance-scorecard.json797 B
  • CHANGELOG.md825 B
  • diagrams/01_flowchart_decision-points.md483 B
  • diagrams/INDEX.md150 B
  • references/dashboard-panels.md522 B
  • references/INDEX.md474 B

SKILL.md(原文)

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Execution Transparency Dashboard

Build dashboards that answer operator questions, reveal drift between intended and actual execution, and shorten the time from anomaly to corrective action.

When to Use

  • Building internal dashboards for workflow runtimes, migrations, multi-agent systems, or refactors.
  • Exposing authority drift, verifier status, backlog burn-down, runtime health, or user-visible failure patterns.
  • Replacing ad hoc status spreadsheets with a source-of-truth operator surface.
  • Designing a panel set where every chart must map to a specific operator decision.

NOT for

  • Marketing, growth, or executive KPI dashboards whose value is narrative rather than intervention.
  • One-off exploratory charts with no owner, threshold, or follow-up action.
  • Duplicate reporting for product analytics that already has a stable home.
  • Full UI implementation details for internal tooling chrome. Use admin-dashboard when the shell and controls are the hard part.

Decision Points

  • Start with operator questions, not available metrics. If nobody can act on the panel, cut it.
  • Separate live runtime truth from planned work. Mixing them produces false confidence.
  • Prefer status panels that expose blocked edges, drift, or unverified states over vanity totals.
  • Add drill-down only when operators need to localize a failure boundary, not just admire the aggregate.
  • Make freshness explicit whenever a panel can lag behind the underlying runtime.
flowchart TD
  A[Need transparency dashboard] --> B{What operator question matters most?}
  B -->|Authority mismatch| C[Authority Drift panel]
  B -->|Migration progress| D[Legacy Burn-Down panel]
  B -->|Execution trust| E[Verification Matrix]
  B -->|User-visible failure| F[User Pain Register]
  C --> G[Map each metric to a concrete source of truth]
  D --> G
  E --> G
  F --> G
  G --> H[Ship only if the panel changes operator behavior]

Failure Modes

  • Dashboard theater. Symptom: attractive panels with no linked operator action. Recovery: attach an owner and decision threshold to each panel or delete it.
  • Drifted truth. Symptom: the dashboard summarizes a shadow data source instead of the runtime contract. Recovery: trace every metric to one authoritative source.
  • Mixed horizons. Symptom: planned work and live state appear identical. Recovery: visually distinguish forecast, backlog, and verified runtime facts.
  • Hidden staleness. Symptom: operators act on outdated data because freshness is invisible. Recovery: display timestamps and refresh mechanics directly in the panel.
  • Metric sprawl. Symptom: dozens of weak charts dilute attention. Recovery: keep only the panels tied to intervention, escalation, or rollout confidence.

Worked Example

Need: build a migration dashboard for moving a workflow engine from frontend-simulated execution to backend authority.

  1. Create an Authority Drift panel showing how many flows still depend on frontend-only transitions.
  2. Add a Legacy Burn-Down panel for compatibility shims, dual-path adapters, and remaining migration blockers.
  3. Add a Verification Matrix panel that distinguishes tested, untested, and failing subsystems.
  4. Track a User Pain Register for incidents the migration is meant to eliminate, not just internal technical milestones.
  5. Expose freshness timestamps and drill-down links so operators can move from red panel to exact failing boundary.

The expert move is treating the dashboard as an operational contract, not a decorative readout.

Quality Gates

  • Every panel is framed as an operator question.
  • Every metric resolves to an authoritative source of truth.
  • Planned, inferred, and verified states are visually distinct.
  • Freshness and sampling cadence are visible.
  • A red state implies a concrete next action or escalation path.
  • Drill-down paths localize the failure boundary without requiring raw-log spelunking for common cases.

Anti-Patterns and Shibboleths

  • "If the data exists, it deserves a chart." Wrong. Operators need intervention surfaces, not metric hoarding.
  • "A migration dashboard should mostly show percent complete." Weak. Experts track drift, blocked edges, and unverified seams because those predict rollout risk.

Reference Map

  • references/INDEX.md
  • references/dashboard-panels.md

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