diff --git a/misc/block-time-analyzer/BlockTimeTrap.sol b/misc/block-time-analyzer/BlockTimeTrap.sol
new file mode 100644
index 0000000..acb9ac1
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+++ b/misc/block-time-analyzer/BlockTimeTrap.sol
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+// SPDX-License-Identifier: MIT
+pragma solidity ^0.8.20;
+
+import "contracts/interfaces/ITrap.sol";
+
+contract BlockTimeTrap is ITrap {
+    struct CollectOutput {
+        uint256 blockTimestamp;
+    }
+
+    function collect() external view returns (bytes memory) {
+        return abi.encode(CollectOutput({blockTimestamp: block.timestamp}));
+    }
+
+    function shouldRespond(bytes[] calldata data) external pure returns (bool, bytes memory) {
+        if (data.length < 2) {
+            return (false, bytes(""));
+        }
+
+        CollectOutput memory recent = abi.decode(data[0], (CollectOutput));
+        CollectOutput memory older = abi.decode(data[1], (CollectOutput));
+
+        uint256 timeDifference = recent.blockTimestamp - older.blockTimestamp;
+
+        // Trigger if the time between blocks is unusually long (e.g., > 30 seconds)
+        if (timeDifference > 30) {
+            return (true, abi.encode("High latency detected between blocks!"));
+        }
+
+        return (false, bytes(""));
+    }
+}
diff --git a/misc/block-time-analyzer/EventLogger.sol b/misc/block-time-analyzer/EventLogger.sol
new file mode 100644
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+++ b/misc/block-time-analyzer/EventLogger.sol
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+// SPDX-License-Identifier: MIT
+pragma solidity ^0.8.20;
+
+contract EventLogger {
+    address public owner;
+    uint256 public eventCount;
+
+    event Sighting(uint256 indexed eventId, string message, uint256 timestamp);
+
+    constructor() {
+        owner = msg.sender;
+    }
+
+    function recordSighting(string memory message) external {
+        eventCount++;
+        emit Sighting(eventCount, message, block.timestamp);
+    }
+}
diff --git a/misc/block-time-analyzer/README.md b/misc/block-time-analyzer/README.md
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+++ b/misc/block-time-analyzer/README.md
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+# Block Time Analyzer Trap
+
+This trap provides a real-time monitoring solution for blockchain network health by analyzing the time between consecutive blocks. It serves as a practical and effective example of **Rate of Change Analysis** using Drosera.
+
+## What It Does
+
+The primary function of this trap is to detect potential network-level issues, such as heavy congestion, validator problems, or early signs of a chain liveness failure. It acts as a decentralized watchdog for the blockchain's pulse.
+
+## How It Works
+
+The trap's logic is straightforward and reliable, utilizing the most fundamental data on the blockchain:
+
+-   **`BlockTimeTrap.sol`**: The main trap contract.
+    -   **Collects:** The `block.timestamp` of every new block as it is produced.
+    -   **Analyzes:** It calculates the time difference (delta) between the timestamp of the most recent block and the one immediately preceding it.
+    -   **Responds:** If the time difference exceeds a predefined threshold (e.g., 30 seconds), the trap's `shouldRespond` function returns `true`, signaling that an incident has occurred.
+
+-   **`EventLogger.sol`**: A simple responder contract. When the trap is triggered, the Drosera network calls the `recordSighting` function on this contract, creating a permanent, on-chain log of the high-latency event.
+
+## Real-World Use Case
+
+This trap is highly useful for any protocol, staking provider, or infrastructure service that depends on the consistent and timely production of blocks.
+
+-   **Infrastructure Monitoring:** A DevOps team for a large exchange or dApp could use this trap to get immediate, decentralized alerts about network instability, allowing them to react before their users are impacted.
+-   **Staking Services:** A liquid staking protocol could use this trap to monitor for validator downtime or network partitions that could affect staking rewards or network security.
+-   **Automated Alerting:** The on-chain event from the `EventLogger` can be easily indexed by services like The Graph or integrated with off-chain tools like Zapier to trigger alerts in Slack, Telegram, or PagerDuty, creating a fully automated monitoring and alerting pipeline.