Evidence Receipt. Related Resources.
Evidence Receipt. Related Resources.
Compared to this week’s papers
Verification pending
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Route this paper proof surface into REST, MCP, or developer workflows while preserving the same evidence receipt and related-resource context.
Page Freshness
Canonical route: /signal-canvas/when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agents
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agents | Route /signal-canvas/when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agents
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agentsMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agents",
"query_text": "Summarize When Tools Fail: Benchmarking Dynamic Replanning and Anomaly Recovery in LLM Agents"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "When Tools Fail: Benchmarking Dynamic Replanning and Anomaly Recovery in LLM Agents",
"normalized_query": "2606.05806",
"route": "/signal-canvas/when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agents",
"paper_ref": "when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agents",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Claims: 1
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: When Tools Fail: Benchmarking Dynamic Replanning and Anomaly Recovery in LLM Agents
PDF: https://arxiv.org/pdf/2606.05806v1
Repository: https://github.com/Zhudongsheng75/ToolMaze
Source count: 4
Coverage: 83%
Last proof check: 2026-06-06T11:26:36.377Z
Signal Canvas receipt window
/buildability/when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agents
Subject: When Tools Fail: Benchmarking Dynamic Replanning and Anomaly Recovery in LLM Agents
Verdict
Ignore
Preparing verified analysis
Dimensions overall score 0.0
{"file name": "input.pdf", "number of pages": 38, "author": "Dongsheng Zhu; Xuchen Ma; Yucheng Shen; Xiang Li; Yukun Zhao; Shuaiqiang Wang; Lingyong Yan; Dawei Yin"
Implication not extracted yet.
partial
Related resources will appear here when this paper maps cleanly to topic, benchmark, or dataset surfaces.
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Verdict is Ignore because current viability and proof state do not clear the buildability gate.
Time to first demo
Insufficient data
No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.
Structured compute envelope
Insufficient data
No data, compute, hardware, memory, latency, dependency, or serving requirement receipt is attached.
Receipt path
/buildability/when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agents
Paper ref
when-tools-fail-benchmarking-dynamic-replanning-and-anomaly-recovery-in-llm-agents
arXiv id
2606.05806
Generated at
2026-06-06T11:26:36.377Z
Evidence freshness
fresh
Last verification
2026-06-06T11:26:36.377Z
Sources
4
References
0
Coverage
83%
Lineage hash
80dcac87af4698ebc721665cd4c90b37c9aa3509d045d5604809d864bc2025fc
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
Verification is blocked until an external signature is provided.
Pending verification refs / 4 sources / Verification pending
references