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Add remove_redundant_context_v1 A/B experiment to pr-sous-chef workflow - #56257
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Co-authored-by: pelikhan <4175913+pelikhan@users.noreply.github.com>
Co-authored-by: pelikhan <4175913+pelikhan@users.noreply.github.com>
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[WIP] Remove redundant context in pr-sous-chef workflow
Add remove_redundant_context_v1 A/B experiment to pr-sous-chef workflow
Aug 27, 2026
pelikhan
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August 27, 2026 06:39
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@copilot resolve the merge conflicts in this pull request |
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Pull request overview
Adds an A/B experiment to measure whether removing redundant skip-rule context improves PR Sous Chef execution duration without reducing evaluation pass rates.
Changes:
- Adds balanced control/candidate experiment configuration and grader instrumentation.
- Gates the redundant skip-rules table to the control variant.
- Regenerates the compiled workflow with experiment persistence and grader artifacts.
Show a summary per file
| File | Description |
|---|---|
.github/workflows/pr-sous-chef.md |
Defines the experiment, graders, and prompt gating. |
.github/workflows/pr-sous-chef.lock.yml |
Compiles experiment assignment, grading, and state persistence. |
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Co-authored-by: pelikhan <4175913+pelikhan@users.noreply.github.com>
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pr-sous-chefis the highest-traffic tracked workflow, making it the best candidate to test whether removing a redundant "Required skip rules per PR" backup table from the main-agent prompt reduces execution duration without regressing eval pass rates — the same three skip conditions are already enforced deterministically by the prefilter step and re-verified by thepr-processorsub-agent.Changes
remove_redundant_context_v1(control vs. candidate) topr-sous-chef.mdfrontmatter, targetinggrader:execution-durationas the primary metric witheval:comment-added/eval:pr-evaluatedguardrails (≥0.90 pass rate),mann_whitneyanalysis, and a 15,000ms minimum effect threshold.graders: execution-duration: {}— since any explicitly listed built-in grader causes the rest of the built-in registry to populate with defaults, this reliably surfacesexecution-durationeven after merging with imported custom graders.shared/graders.mdtoimports:, pulling in the custom trajectory graders (recurrence-determinism, recurrence-laminarity, state-revisit-probability-rep).controlvariant, keeping candidate behavior otherwise identical:pr-sous-chef.lock.ymlto reflect the frontmatter changes.