diff --git a/CONSTRAINTS.md b/CONSTRAINTS.md
index eb7c58f..3b96db1 100644
--- a/CONSTRAINTS.md
+++ b/CONSTRAINTS.md
@@ -1,6 +1,8 @@
 ## LLM Constraints and Guidelines
+- Not everything is an anamoly. Err on the side of caution when selecting severity. Its ok not to report anything. You don't have to say anything if you don't want to, or don't need to.
 - Please do not report on anything that is older then 24 hours.
 - The server uses a custom DNS server at 192.168.2.112.
+- Please think carefully on if the measured values exceed the averages by any significant margin. A few seconds, or a few degrees in difference do not mean a significant margin. Only report anomolies with delta values greater then 10.
 
 ### Important Things to Focus On:
 - Security-related events such as failed login attempts, unauthorized access, or unusual network connections.
diff --git a/PROGRESS.md b/PROGRESS.md
index 7949ff7..1170256 100644
--- a/PROGRESS.md
+++ b/PROGRESS.md
@@ -60,10 +60,18 @@
 36. [x] Create helper function in `data_storage.py` for calculating average metrics.
 37. [x] Update `README.md` with current project status and improvements.
 38. [x] Create `AGENTS.md` to document human and autonomous agents.
+
+## Keeping track of Current Objectives
+
 [x] Improve "high" priority detection by explicitly instructing LLM to output severity in structured JSON format.
 [x] Implement dynamic contextual information (Known/Resolved Issues Feed) for LLM to improve severity detection.
 
 ## TODO
 
-
-
+- [ ] Change baseline calculations to only use integers instead of floats.
+- [ ] Add a log file that only keeps records for the past 24 hours.
+- [ ] Log all LLM responses to the console.
+- [ ] Reduce alerts to only happen between 9am and 12am.
+- [ ] Get hostnames of devices in Nmap scan.
+- [ ] Filter out RTT fluctuations below 10 seconds.
+- [ ] Filter out temperature fluctuations with differences less than 5 degrees.
\ No newline at end of file
diff --git a/data_storage.py b/data_storage.py
index 5d63bc6..dd74178 100644
--- a/data_storage.py
+++ b/data_storage.py
@@ -19,7 +19,7 @@ def store_data(new_data):
 def _calculate_average(data, key1, key2):
     """Helper function to calculate the average of a nested key in a list of dicts."""
     values = [d[key1][key2] for d in data if key1 in d and key2 in d[key1] and d[key1][key2] != "N/A"]
-    return sum(values) / len(values) if values else 0
+    return int(sum(values) / len(values)) if values else 0
 
 def calculate_baselines():
     data = load_data()
diff --git a/known_issues.json b/known_issues.json
index 2036b7c..dd8db9d 100644
--- a/known_issues.json
+++ b/known_issues.json
@@ -13,7 +13,7 @@
     },
     {
         "issue": "Port 62078 is open",
-        "resolution": "Port 62078 is used in apple devices for syncing communcation between each other. This is not an amomaly, this is expected and normal behavior used by Apple Devices to communicate."
+        "resolution": "This is normal behavior for Apple devices. Do not report."
     },
     {
         "issue": "RTT averages are higher then average",
diff --git a/monitor_agent.py b/monitor_agent.py
index 55c859d..a4b662b 100644
--- a/monitor_agent.py
+++ b/monitor_agent.py
@@ -195,7 +195,8 @@ def build_llm_prompt(data, baselines, nmap_changes, constraints, known_issues):
     **Constraints and Guidelines:**
     {constraints}
 
-    **Output Request:** If you find an anomaly, provide a report as a single JSON object with two keys: "severity" and "reason". The "severity" must be one of "high", "medium", "low", or "none". The "reason" must be a natural language explanation of the anomaly. Please include specific values if the anomoly has them. If no anomaly is found, return a single JSON object with "severity" set to "none" and "reason" as an empty string. Do not wrap the JSON in markdown or any other formatting.
+    **Output Request:** If you find an anomaly, provide a report as a single JSON object with two keys: "severity" and "reason". The "severity" must be one of "high", "medium", "low", or "none". The "reason" must be a natural language explanation of the anomaly. Please include specific values if the anomoly has them. If no anomaly is found, return a single JSON object with "severity" set to "none" and "reason" as an empty string. Do not wrap the JSON in markdown or any other formatting. Only return the JSON, and nothing else.
+
 
     **Reasoning Hint:** Think step by step to come to your conclusion. This is very important.
     """