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Add Job Queue reliability and scheduling guidance (#148)
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* knowledge(performance): add job queue reliability guidance

* Address Job Queue review feedback

* Address Job Queue routing review feedback

* Encode job queue conflict in fixtures
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Stefano Demiliani 2026-09-14 12:44:30 +02:00 • committed by GitHub
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evaluation/README.md
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@ -2,7 +2,7 @@
The evaluation is convention-driven. The harness discovers every `<layer>/skills/review/al-<domain>-review.md` leaf across the enabled `microsoft`, `community`, and `custom` layers. Duplicate domains resolve with `custom > community > microsoft` precedence. For each selected leaf, the harness finds paired knowledge across the same layers, applies the same precedence to duplicate article slugs, selects the first article (by filename) with both `.bad.al` and `.good.al` companions, and derives the expected positive and clean control automatically. Adding a conforming leaf requires no scoring-contract edit.
`review-fixtures.json` contains only global thresholds and optional exceptional overrides. An override may select a different article or add context when the generic convention cannot express a scenario. It should remain empty in the normal case.
`review-fixtures.json` contains only global thresholds and optional exceptional overrides. An override may select a different `article`, add context when the generic convention cannot express a scenario, or use an `articles` array when one domain needs explicit regression coverage for several paired articles. Specify either `article` or `articles`, not both. The first selected article retains the stable `<domain>-bad` and `<domain>-good` manifest IDs; additional articles use slug-qualified IDs. Overrides should remain empty in the normal case.
Model-facing preparation hashes case IDs, neutralizes `Good`/`Bad` object-name tokens, and removes full-line sample comments so neither the article slug, domain, nor expected outcome reveals the answer.
@ -26,7 +26,7 @@ This credential-free check proves every selected leaf maps to a same-named knowl
2. For a fast/small model, use one fresh invocation per `request-case-*.json`. Each request embeds the exact leaf instructions, that domain's candidate index rows with authoritative paths, and one opaque case. The model opens only matching articles and copies finding IDs from `candidateArticles[].path`. Save each response with the matching `result-case-*.json` name in the same directory.
`request-<domain>.json` files provide optional two-case leaf batches and identify the selected layer-owned skill path; save those as `result-<domain>.json`. Directory scoring prefers `result-case-*.json` when present and otherwise falls back to `result-*.json`. `review-request.json` is an optional all-domains stress test for larger models. Neither batch form is the preferred fast-model profile.
`request-<domain>.json` files provide optional leaf batches containing every selected case for that domain and identify the selected layer-owned skill path; save those as `result-<domain>.json`. A normal convention-selected domain has one bad/good pair, while an `articles` override contributes one pair per listed article. Directory scoring prefers `result-case-*.json` when present and otherwise falls back to `result-*.json`. `review-request.json` is an optional all-domains stress test for larger models. Neither batch form is the preferred fast-model profile.
3. Save only this result shape: