AI Interfaces
Context Window Meter
A token allocation breakdown for system instructions, conversation history, and retrieved sources.
Installation
Copy and paste the code into your project.
Accessibility notes
Every segment has a visible label and token value, so the chart is supplementary rather than essential.
Context window
25.4k / 32k
- System
- 4.2k
- Conversation
- 12.8k
- Sources
- 8.4k
6.6k tokens available for response
Preview accent
const segments = [
{ label: "System", tokens: "4.2k", width: "w-[18%]", color: "bg-[#40E0D0]" },
{ label: "Conversation", tokens: "12.8k", width: "w-[38%]", color: "bg-[#a78bfa]" },
{ label: "Sources", tokens: "8.4k", width: "w-[27%]", color: "bg-[#fb923c]" },
];
export function ContextWindowMeter() {
return (
<section className="w-full max-w-sm rounded-xl border border-white/12 bg-[#0b0f14]/92 p-5 shadow-2xl">
<div className="flex items-end justify-between gap-4">
<div><p className="text-xs font-semibold uppercase tracking-[0.18em] text-[#40E0D0]">Context window</p><h3 className="mt-2 text-2xl font-black tabular-nums text-white">25.4k <span className="text-sm font-semibold text-slate-500">/ 32k</span></h3></div>
<span className="rounded-full bg-[#fb923c]/12 px-2.5 py-1 text-xs font-bold text-[#fdba74]">79% used</span>
</div>
<div className="mt-5 flex h-2.5 gap-1 overflow-hidden rounded-full bg-white/[0.06]" aria-hidden="true">
{segments.map((segment) => <span key={segment.label} className={`${segment.width} ${segment.color} rounded-full`} />)}
</div>
<dl className="mt-4 grid grid-cols-3 gap-2">
{segments.map((segment) => <div key={segment.label} className="rounded-lg border border-white/8 bg-white/[0.035] p-2.5"><dt className="text-[0.65rem] text-slate-500">{segment.label}</dt><dd className="mt-1 text-xs font-bold tabular-nums text-slate-200">{segment.tokens}</dd></div>)}
</dl>
<p className="mt-4 flex items-center gap-2 text-xs text-slate-400"><span className="h-1.5 w-1.5 rounded-full bg-[#40E0D0]" /> 6.6k tokens available for response</p>
</section>
);
}<ContextWindowMeter />Related components
Context compression
Compaction preview
- Keep
Decisions
1.8k
- Summarize
Discussion
8.4k → 1.2k
- Drop
Duplicates
2.1k
AI Interfaces
Context Compression Preview
A compaction preflight showing which conversation sections will be kept, summarized, or dropped.
Context window
Token allocation
23.9kof 32k
- System4.2k
- History9.8k
- Retrieval5.1k
- Response4.8k
8.1k tokens remain for tools, retries, and safety margin.
AI Interfaces
Token Budget Allocator
A context-window planner showing how instructions, history, retrieval, and response capacity consume tokens.
Agent memory
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- Uses eval scorecards
- Ships with dark themes
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A compact memory summary card for personalized agents and workspace context.