Diagnosing and Remediating the JADA Agent Daemon: OAuth Token Expiration and Session Management

```html

During a routine health check of the JADA orchestrator daemon running on Lightsail instance 34.239.233.28, we discovered a critical OAuth token failure in the port sheet sync pipeline and identified patterns in agent session termination. This post covers the diagnosis methodology, infrastructure findings, and remediation steps taken.

What Was Done

We performed a comprehensive health audit of the JADA daemon infrastructure, including:

SSH access via AWS Lightsail temporary credentials (avoiding local key storage)
Service status inspection and uptime verification
Log analysis for errors and performance anomalies
CloudWatch metrics collection for CPU, memory, and network behavior
Agent session accounting and task completion tracking
Root cause analysis of the port_sheet_sync.py OAuth failure

Infrastructure State and Findings

Lightsail Instance Health:

Uptime: 11 days continuous; service running since May 10 (3 days in current session)
Resource utilization: CPU 0.65% average, memory 144MB / 914MB, disk 6.2GB / 39GB
Load average: 0.00 between task executions (expected for a polling daemon)
Status checks: Zero failures in last 2 hours — infrastructure stable

Agent Session Accounting (May 13):

Session 1 (00:00 UTC): Max turns reached (30/30) — exit code 1
Session 2 (00:02 UTC): Completed successfully — processed e-signature blockers, created needs-you task
Session 3 (00:05 UTC): Max turns reached (30/30) — exit code 1
Sessions used: 3 of 5 daily allocation
Pending tasks after 00:05: 0 (daemon idling normally)

This pattern indicates that two complex tasks exhausted the 30-turn Claude API limit per session, while the intermediate session completed meaningful work. The daemon correctly logged these as non-fatal errors and continued operation.

Critical Issue: OAuth Token Failure in Port Sheet Sync

Symptom: Every 30-minute execution of port_sheet_sync.py since at least afternoon on May 13 has failed with:

[port-sheet] token error: HTTP Error 400: Bad Request

Root Cause: The Google OAuth token stored for the port sheet sync process has expired or been revoked. This token is used to authenticate against the Google Sheets API for the port booking sheet synchronization workflow.

Impact:

Port sheet data is not being synchronized with live booking state
No data corruption (failures are caught before write operations)
Daemon continues operation; sync simply skips until remediated

Why This Happened: Google OAuth tokens obtained via the 3-legged flow (user-initiated authentication) have a limited lifetime, typically 3600 seconds. Refresh tokens can extend this, but if the refresh token is missing or revoked (due to user credential changes or explicit revocation), the token becomes invalid. The auth_ga.py tool in /Users/cb/Documents/repos/tools/ handles token management but must be re-run when tokens expire.

Technical Details: Access Methodology

Traditional SSH with stored private keys presents security risks in development workflows. Instead, we used AWS Lightsail's temporary credential API:

aws lightsail get-instance-access-details \
  --instance-name jada-agent \
  --region us-east-1 \
  --query 'accessDetails.{cert:cert,privateKey:privateKey}' \
  --output json

This returns a temporary certificate and private key valid for 60 minutes, eliminating the need to store long-lived SSH keys locally. After connection, the temporary credentials were immediately purged to minimize exposure window.

Why this approach:

Zero persistent key storage: No ~/.ssh/jada-key file to leak or compromise
Audit trail: AWS API calls are logged in CloudTrail; SSH access is traceable to caller
Short-lived credentials: 60-minute expiry limits blast radius if credentials are exposed
IAM-gated access: Requires proper AWS permissions; credentials cannot be bypassed

Session Termination Pattern: Max Turns (30) Limit

Two of three agent sessions today hit the 30-turn limit in the Claude API call loop. This is not a bug but a safety mechanism:

By design: Each agent session is bounded to 30 turns to prevent infinite loops and uncontrolled API costs
Observed behavior: Sessions 1 and 3 were complex multi-step tasks (e-signature page generation, crew page analysis) that required more turns than available
Session 2 completed: Intermediate session successfully completed its work and created a needs-you task (indicating human review required)
Not a failure: The daemon logs exit code 1 but continues polling; this is expected behavior when tasks are truncated

Implication: If high-complexity tasks are regularly hitting the 30-turn limit, consider splitting them into smaller subtasks or increasing the limit if the cost/benefit justifies it. Session 2's success on the same day shows the daemon is functioning correctly.

Key Infrastructure Decisions

1. Temporary Credential Model Over Persistent Keys

We prioritized AWS Lightsail's native temporary credential API over managing long-lived SSH keys. This reduces operational security risk and aligns with AWS best practices for ephemeral access.

2. CloudWatch Metrics for Non-Invasive Monitoring

Rather than relying solely on daemon logs, we pulled CPU, memory, and network metrics via the Lightsail API to verify infrastructure health without requiring detailed log parsing. This allowed rapid triage without SSH session overhead.

3. Session Accounting as a Health Indicator

Tracking daily session count (3 of 5 used) and exit codes provides insight into workload characteristics. Two max-turn exits followed by normal idling suggests tasks are being queued correctly but some are inherently complex.

What's Next

Immediate (Priority: High)

Re-authenticate the Google OAuth token for port_sheet_sync.py using the auth_ga.py` tool with the appropriate service account or user credentials


  Verify the refresh token is present and valid in the credentials file
  Monitor the next 30-minute sync cycle to confirm HTTP 200 OK responses



Medium-term (Priority: Medium)


  Evaluate the 30-turn limit for complex