Consola de operaciones para agentes de IA

Plantilla de prompt para copiar

La plantilla técnica se mantiene en inglés para usarla directamente con los agentes compatibles. La explicación, selección y comprobaciones están localizadas.

Create an AI agent operations console for [TEAM] running [AGENT WORKFLOW]. The main user needs to answer three questions quickly: what is running, where is it stuck, and what needs human approval?

Information architecture:
- Overview with active, waiting, failed, completed, and over-budget runs plus a trustworthy time and cost summary.
- Run queue with owner, goal, current agent, elapsed time, token/cost budget, risk level, and last event.
- Run detail with a chronological trace of model turns, tool calls, handoffs, guardrail checks, approvals, retries, and final output.
- Agent map showing each specialist’s responsibility, available tools, handoff rules, and current state.
- Evaluation view for success criteria, grader results, recurring failure clusters, and version comparisons.

Critical interactions:
- Filter and search runs; pause, resume, cancel, retry from a safe checkpoint, and duplicate into a sandbox.
- Open any trace event to inspect inputs, outputs, latency, cost, model, and redacted metadata.
- Present approval requests with the proposed action, affected resource, exact arguments, risk explanation, and approve/reject/edit controls.
- Require confirmation for cancellation or actions that can change external systems.
- Add a replay mode that uses recorded tool results so debugging does not repeat real-world side effects.

States and integrity:
- Use realistic sample runs for [AGENT WORKFLOW], including a successful handoff, a guardrail block, a timed-out tool, a rejected approval, and a budget stop.
- Distinguish queued, running, waiting, paused, failed, cancelled, and completed states by text and icon—not color alone.
- Never expose secrets or raw sensitive payloads; show redaction and retention controls.
- Keep totals, trace durations, token counts, and cost rollups internally consistent.

Visual direction: [VISUAL DIRECTION]. Favor scanability and causal sequence over a grid of generic KPI cards. The mobile view should support monitoring and approvals; move deep trace analysis to wider screens.

Finish by testing keyboard navigation, live updates, stale data, reconnection, approval expiry, destructive confirmations, and an interrupted run that resumes from a checkpoint.