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<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width,initial-scale=1">
<meta name="description" content="Explore agent observability across planning, tools, memory, verification, recovery and long-horizon execution.">
<title>Agent Observability</title>
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<body>
<header class="hero">
<div class="wrap">
  <span class="kicker">Agent Tracing · Memory · Tools · Recovery</span>
  <h1>Agent <span class="grad">Observability</span></h1>
  <p>Trace how advanced AI agents plan, act, use tools, update memory, recover and reach final outcomes.</p>
</div>
</header>

<main class="wrap">
<section class="controls" id="controls"></section>

<section class="layout">
  <div class="panel">
    <div class="ey" id="category"></div>
    <h2 id="name"></h2>
    <div class="desc" id="desc"></div>

    <div class="flow" id="flow"></div>
    <div class="cards" id="cards"></div>

    <div class="ey" style="margin-top:16px">Recommended fields</div>
    <div class="tags" id="fields"></div>
  </div>

  <aside class="panel">
    <div class="ey">Operational profile</div>
    <h2 style="font-size:21px">Observability value</h2>
    <div class="desc">Conceptual importance for production agent systems.</div>
    <div id="metrics"></div>

    <div class="failure">
      <b>Typical blind spot</b>
      <span id="failure"></span>
    </div>

    <div class="note">Conceptual values only; not benchmark scores.</div>
  </aside>
</section>
</main>

<footer>
<div class="wrap">
  <strong>Agent Observability</strong> — an independent Hugging Face Space.<br>
  Collaboration and partnerships: <strong>agenten@magenta.de</strong>
</div>
</footer>

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 d:"Preserves the original objective, constraints and success criteria across the full agent execution.",
 flow:["Goal","Constraints","Plan","Action","Outcome"],
 cards:[
  ["Why it matters","Makes goal drift detectable."],
  ["Best for","Long-horizon and autonomous agents."],
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  ["Related","Planning, verification, human oversight."]
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  ["Best for","Planner-executor and hierarchical agents."],
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  ["Best for","Agent loops and multi-step workflows."],
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{
 n:"Tool Tracing",cat:"Action",
 d:"Tracks tool selection, arguments, execution results, permissions and retries.",
 flow:["Select Tool","Authorize","Call","Result","Validate"],
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  ["Why it matters","External actions must be reconstructable."],
  ["Best for","Browser, API, code and enterprise tools."],
  ["Key question","What did the agent actually do outside the model?"],
  ["Related","Permissions, tool registry, retries."]
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},
{
 n:"Memory Tracing",cat:"State",
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  ["Best for","Persistent and long-horizon agents."],
  ["Key question","Did stale or wrong memory cause the decision?"],
  ["Related","State management, provenance, freshness."]
 ],
 fields:["memory_id","operation","source","freshness","confidence","conflict"],
 m:{DebugValue:99,LongHorizonValue:100,AuditValue:94,ImplementationComplexity:80},
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},
{
 n:"Verification Tracing",cat:"Quality",
 d:"Records which checks were run, what evidence was used and whether the result passed.",
 flow:["Output","Verifier","Evidence","Decision","Continue"],
 cards:[
  ["Why it matters","Makes correctness gates visible."],
  ["Best for","High-reliability and high-impact workflows."],
  ["Key question","Was this action independently checked?"],
  ["Related","Validation, evaluation, human approval."]
 ],
 fields:["verifier","evidence","result","failure_reason","next_action"],
 m:{DebugValue:95,LongHorizonValue:98,AuditValue:100,ImplementationComplexity:74},
 fail:"A wrong intermediate result is accepted, and there is no evidence showing whether verification ran."
},
{
 n:"Recovery Tracing",cat:"Resilience",
 d:"Tracks retries, fallback paths, checkpoint restores, replanning and escalation.",
 flow:["Failure","Diagnose","Recover","Verify","Resume"],
 cards:[
  ["Why it matters","Shows whether the agent can recover intelligently."],
  ["Best for","Long-running production agents."],
  ["Key question","How did the system respond after failure?"],
  ["Related","Checkpoints, fallbacks, retries, replanning."]
 ],
 fields:["failure_type","recovery_action","retry_count","fallback","checkpoint","outcome"],
 m:{DebugValue:100,LongHorizonValue:100,AuditValue:92,ImplementationComplexity:78},
 fail:"The system retries repeatedly, but recovery behavior is not distinguishable from normal execution."
},
{
 n:"Human Approval Tracing",cat:"Oversight",
 d:"Records approval requests, decisions, approvers and the high-impact action being controlled.",
 flow:["Propose","Risk Check","Human Review","Approve / Reject"],
 cards:[
  ["Why it matters","Creates an auditable boundary around autonomy."],
  ["Best for","Financial, publishing, deployment and privileged actions."],
  ["Key question","Who approved this action and why?"],
  ["Related","Permissions, policy, governance."]
 ],
 fields:["approval_id","action","risk_level","approver","decision","timestamp"],
 m:{DebugValue:84,LongHorizonValue:90,AuditValue:100,ImplementationComplexity:62},
 fail:"A consequential action executes, but the approval event cannot be reconstructed."
},
{
 n:"Cost Tracing",cat:"Operations",
 d:"Attributes cost to specific agent steps, tools, models, retries and verification calls.",
 flow:["Step","Model / Tool","Meter","Attribute","Aggregate"],
 cards:[
  ["Why it matters","Long-horizon agents can accumulate hidden cost."],
  ["Best for","Multi-model agent systems."],
  ["Key question","Which step or retry drives task cost?"],
  ["Related","Budgets, routing, optimization."]
 ],
 fields:["step_cost","model_cost","tool_cost","retry_cost","total_cost","budget"],
 m:{DebugValue:76,LongHorizonValue:96,AuditValue:88,ImplementationComplexity:60},
 fail:"Total spend rises, but costs cannot be linked to individual steps or retries."
},
{
 n:"Drift Detection",cat:"Long-Horizon",
 d:"Uses execution telemetry to detect repeated actions, plan drift, goal drift and runaway loops.",
 flow:["Trace","Compare","Detect Drift","Alert","Correct"],
 cards:[
  ["Why it matters","Long tasks amplify small deviations."],
  ["Best for","Persistent autonomous agents."],
  ["Key question","Is the agent still making meaningful progress?"],
  ["Related","Goal tracing, plan tracing, memory tracing."]
 ],
 fields:["repeat_rate","goal_alignment","plan_changes","step_count","progress_score"],
 m:{DebugValue:98,LongHorizonValue:100,AuditValue:90,ImplementationComplexity:88},
 fail:"The agent keeps working but makes little progress because drift is not detected."
}
];

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