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Harden Daily Ambient Context Optimizer issue publication against placeholder and oversize payload failures #40508

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pelikhan merged 2 commits into from
Jun 20, 2026
+21 −17
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Harden Daily Ambient Context Optimizer issue publication against placeholder and oversize payload failures #40508

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Copilot Jun 20, 2026
7926cc6
fix: harden daily ambient optimizer issue creation flow
Copilot Jun 20, 2026
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30 changes: 15 additions & 15 deletions .github/workflows/daily-ambient-context-optimizer.lock.yml
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8 changes: 6 additions & 2 deletions .github/workflows/daily-ambient-context-optimizer.md
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Expand Up @@ -30,7 +30,7 @@ safe-outputs:
labels: [automation, report, workflow-optimization, analysis]
close-older-issues: true
expires: 7d
max: 1
max: 3
timeout-minutes: 45
steps:
- name: Setup Python
Expand Down Expand Up @@ -204,8 +204,10 @@ Each sub-agent invocation may return at most 3 opportunities for its run. Aggreg
- Keep the workflow bounded and avoid exploratory loops.
- Do not repeatedly re-open or re-parse the same artifacts once required metrics are extracted.
- Keep the final issue body concise and evidence-based, with short bullets and compact explanations.
- Keep the final issue body under 9500 bytes (UTF-8); if needed, shorten details before calling the tool.
- Use at most 3 run links in the final References section.
- Create the issue by calling the safe output tool directly once you have the final body.
- Never call `create_issue` with placeholders, probes, or test strings (for example `"."` or `"test"`). Call it only with the final intended title/body.
- Call `create_issue` only after validating your final body length and content.
Comment on lines +209 to +210

## Recommendation Rules

Expand Down Expand Up @@ -301,6 +303,8 @@ In that case:

Do not use `noop` merely because the sample is small or imperfect. Create exactly one issue whenever logs are available. Use `noop` only if no run logs can be downloaded at all or the repository context is unavailable.

If `create_issue` returns a body-size validation error, shorten the details and retry with a compact body that preserves Executive Summary, Highest-Leverage Changes, Key Metrics, and References.

## agent: `request-optimizer`
---
description: Ranks prompt-shrinking opportunities for one sampled run from compact deterministic metrics
Expand Down