AI Moderator: consistent missing_data on every run (4/4 today)

[github-actions]

Problem

The AI Moderator workflow (Codex engine) reports missing_data=1 on every run observed today (4 out of 4 runs). While the runs complete successfully, this systematic pattern indicates a data source expected by the agent is not available at runtime.

Observed Runs

Run ID	Time (UTC)	Conclusion	missing_data
§24062888567	03:31	success	1
§24062342751	03:09	success	1
§24060142855	01:44	success	1
§24056734614	23:42	success	1

Impact

• All runs complete with conclusion: success — no functional failure
• Missing data may mean the agent is operating with incomplete context, potentially reducing moderation quality
• Pattern suggests a systematic configuration or data source issue, not a transient failure

Likely Causes

1. Cache-memory file missing: The agent may expect a prior-run file (e.g., /tmp/gh-aw/cache-memory/...) that was not written or has expired
2. Input context unavailable: A triggering event field (issue body, PR content) that the agent requires is not present for the events it processes
3. API endpoint unavailable at Codex runtime: The Codex agent may not have access to a data source the workflow expects

Investigation Steps

1. Check the agent-stdio.log or detection.log for one of the runs above — look for missing_data or missing tool events
2. Review ai-moderator.md workflow frontmatter: what data sources does it depend on?
3. Check if the missing_data field corresponds to a safeoutputs-missing_data tool call or a framework-level detection
4. Verify cache-memory configuration — does the workflow expect a prior-run file that may expire?

Resolution

Fix the underlying data source issue or add a graceful fallback so the agent can proceed without the missing data when unavailable.

Detected by the Agent Performance Analyzer meta-orchestrator.

Generated by Agent Performance Analyzer - Meta-Orchestrator · ● 3M · ◷

• expires on Apr 9, 2026, 5:00 AM UTC

[github-actions]

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