For AI Agents
Hand your agent this brief or the ReUI MCP, not a screenshot. Installs with a ReUI Pro or Ultimate license.
When to use
- Run monitoring for a fleet of agents: a live overview, a run queue and failed run triage
- Human review of agent work: an approval inbox, one run's step trace and a nightly evaluation report
- Control pages for agent behavior: tool access, playbooks, run settings and stored memory
When not to use
- One run narrated live to the person who started it, inside a chat or task view: use the Agent Activity blocks
- Model provider routing, prompt reviews, token spend and safety policies for LLM features: use the AI Ops blocks
- An account, workspace, notification or integration page of labeled switches and selects: use the Settings blocks
Agent notes
- Every block sets a
min-h-svhwrapper with its own padding and max width in page.tsx, its root component or both; drop them inside an app shell - No block mounts the
sonnertoaster, so everytoastcall stays invisible until your layout renders one - No handler reaches a backend: actions change local
useStateand fire atoast, so wire each one to your agent API
Third-party API docs
- Sonner v2: API reference, docs, used by 10 of 10 blocks
- TanStack Table v9: API reference, docs, used by 7 of 10 blocks
- Recharts v3: API reference, docs, used by 2 of 10 blocks
- date-fns v4: docs, used by 1 of 10 blocks
- React DayPicker v9: API reference, docs, used by 1 of 10 blocks
https://web.dev.reui.io/blocks/solutions/agents.mdsearch({ query: "agents", type: "block", category: "agents" })Shadcn AI Agent Blocks for Run Monitoring, Approvals, and Evals
Agent products fail in operations, not in the model. Somebody has to see which runs are stuck, approve the dangerous action before it fires, read the trace when a run dies at step seven, and notice that last night's eval dropped four points. This category is the set of surfaces for that job.
It starts with the ops dashboard: KPI cards, a throughput chart, an incident Timeline, and a filterable run queue with row actions. From there you drop into a triage table with collapsible Running, Waiting, Failed, and Completed groups, then into one run's step trace with per-step tool calls, latency, and a row-editable settings panel.
The governance side is the part most teams have to invent from scratch. A per-agent tool access matrix sets each tool's mode, rate limit, and approver, a playbook wizard defines trigger, conditions, tool allowlist, and approval gate before publishing, and a run-configuration form pins reasoning model, concurrency, validated timeout, autonomy, sandbox, and retry policy.
All Agents Blocks
Open any block on its own page for a live preview, the components it is built from, and the install command.
- Agent Fleet Overview AI Agent Operations Dashboard with Run Queue, Throughput Chart and Incident Timeline
- Agent Run Queue Agent Run Queue with Collapsible Status Groups and Attention Filters
- Run Step Trace Agent Run Detail with Inline Step Trace and Editable Settings Panel
- Tool Access Matrix Agent Tool Access Matrix with Approval Routing and Run Policies
- Action Approval Inbox Agent Action Approval Inbox with Risk-Tiered Queue and Bulk Approve or Reject
- Playbook Builder Agent Playbook Builder Wizard with Live Summary Card and Tool Allowlist
- Failed Run Triage Failed Agent Run Triage Board with Detail Sheet and Retry Ladder
- Agent Eval Report Agent Evaluation Report with Pass Rate Trend and Release Markers
- Agent Memory Agent memory manager with scope rail and confidence-scored entries grid
- Agent Run Settings Agent run-configuration settings form with picker, validated timeout, and locked policy row
Human in the Loop, as an Actual Inbox
Approval flows get designed as a modal, then collapse the first week an agent produces forty pending actions.
The approval inbox is built as a queue instead: filter by risk tier and status, bulk approve or reject, and open a detail Sheet to inspect the payload before deciding. It uses ReUI DataGrid, Badge, and Timeline with shadcn Sheet, Select, and Checkbox.
The tool access matrix is the policy behind that inbox. Every tool gets an access mode of Auto Run, Approval, or Blocked, a rate limit, and a named approver, alongside run-policy Switch rows and an explicit save or discard. What reaches a human becomes a configuration you can review, not a rule buried in orchestration code.
Debugging and Evaluating Runs
When a run fails, the triage board puts metric cards over a failure grid, then opens a detail sheet tabbed into error, retry attempts, and payload. The single-run detail page goes further with a step trace showing each tool call and its latency, plus a row-editable settings panel so you can change the configuration that caused the failure without leaving the page.
Regression tracking gets its own report. The nightly eval block charts pass rate over time with release markers on the trend, shows per-suite Progress, and lists regressions in a table comparing two releases, with a period selector, a regressions-only toggle, and export.
The memory manager covers the newest problem, which is what an agent is allowed to remember. A scope rail with per-scope counts sits beside a confidence-scored grid of retained facts, each one pinnable, forgettable, and filterable.
Built for a Category That Did Not Exist Two Years Ago
- Run states as first-class UI Running, Waiting, Failed, and Completed are collapsible groups with an attention filter and a density toggle, not four badge colors on one flat table.
- Risk tiers on the queue Pending actions rank by risk, so a destructive tool call does not sit behind forty harmless ones waiting for someone to scroll.
- Traces without a vendor lock Step-by-step tool calls and latency render from typed local data, so the same page can front LangSmith, Langfuse, OpenTelemetry spans, or your own runs table.
- Policy before autonomy Tool allowlists, approval gates, sandbox and retry switches, validated timeouts, and a locked PII row the form will not let you toggle off.
Related Shadcn Solutions Block Categories
- AI Ops Blocks (9 blocks) The layer under the agents: model providers, prompt versions, token cost, routing, and quotas.
- Dev Ops Blocks (6 blocks) Cron jobs, deploys with a live canary, SLO error budgets and an audit log for the platform your agents run on.
- Analytics Blocks (9 blocks) Funnel, cohort, and experiment reporting for measuring whether the agent feature actually got adopted.
- Users Blocks (7 blocks) RBAC matrices and audit logs for the humans who approve agent actions and answer for them later.
- Billing Blocks (9 blocks) Metered usage ledgers and plan catalogs for products that charge per run, per task, or per token.
- Inventory Blocks (11 blocks) Stock, reorder, and movement screens, a good reference for dense operational grids outside AI.
- CRM Blocks (9 blocks) Pipeline and contact screens if your agents are acting on sales records rather than infrastructure.
All Shadcn Block Groups
Browse the full ReUI Shadcn blocks library by product surface. Each group bundles category-level blocks you can mix and match across your project.
- Shadcn Application Blocks (303) Browse 303 Shadcn Application blocks across 23 categories.
- Shadcn Data Grid Blocks (47) Browse 47 Shadcn Data Grid blocks across 9 categories.
- Shadcn Charts Blocks (52) Browse 52 Shadcn Charts blocks across 10 categories.
- Shadcn Solutions Blocks (76) Browse 76 Shadcn Solutions blocks across 11 categories.
- Shadcn AI & Agents Blocks (22) Browse 22 Shadcn AI & Agents blocks across 3 categories.
- Shadcn eCommerce Blocks (87) Browse 87 Shadcn eCommerce blocks across 13 categories.
- Shadcn Marketing Blocks (67) Browse 67 Shadcn Marketing blocks across 8 categories.
Frequently Asked Questions
Do these work with LangGraph, CrewAI, or the OpenAI Agents SDK?
What does an agent ops console actually need?
How do I install an agent block?
Can I restyle the console for a dense, dark ops look?
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