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tsz-performance-engineering

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Actualizado2 de junio de 2026 a las 05:23

Use when planning, implementing, reviewing, or interpreting TSZ performance work, including benchmark regressions, cache/residency changes, timing claims, perf counters, hotspot investigations, OOM/timeout/stack-overflow blockers, or optimization PR evidence.

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mohsen1

mohsen1/tsz

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Ocupaciones relacionadasSOC

Basado en la clasificación ocupacional SOC

Desarrolladores de softwareOcupaciones informáticas y matemáticas·SOC 15-1252

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Audit TSZ repo iteration speed and quality. Use when asked to deep-dive repo health, identify avoidable delays, improve agent workflows, reduce CI/PR churn, add guardrails, choose skills to install or create, or turn recurring TSZ process failures into focused tooling/docs PRs.

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Create, refresh, and publish TSZ pull requests with correct coordination state. Use when opening a draft PR, updating a PR body, applying canonical agent labels, changing WIP/draft/ready state, acknowledging review, handing off readiness to a manager agent, or making sure a TSZ PR satisfies AgentName, Project Corpus Impact, verification, and overlap rules.

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name	tsz-performance-engineering
description	Use when planning, implementing, reviewing, or interpreting TSZ performance work, including benchmark regressions, cache/residency changes, timing claims, perf counters, hotspot investigations, OOM/timeout/stack-overflow blockers, or optimization PR evidence.

TSZ Performance Engineering

Use for performance, cache/residency, OOM/timeout/stack-overflow, counters, benchmark regressions, and timing claims.

Rules

Read AGENTS.md, docs/plan/ROADMAP.md, and relevant PR/issues.
Correctness first. Timing claims matter only for green rows or explicit runtime/residency blockers.
Optimize the repeated operation, not a fixture spelling.
State invariant: cache key, invalidation/reset, request scope, fuel/cycle behavior, residency bound, or complexity change.
No checker-local semantic algorithms, display-string heuristics, source-text shortcuts, name allowlists, or cross-interner TypeId comparisons.
Read references/perf-mistakes.md before adding/widening caches, changing residency, or claiming speedups.

Evidence

Use narrow, reproducible commands; wrap heavy runs.

python3 scripts/perf/cache-visibility-report.py --json
python3 scripts/perf/visited-clone-report.py --json
python3 scripts/perf/debug-print-report.py --json
python3 scripts/perf/migration_callsite_counts.py --json
python3 scripts/perf/query-perf-counters.py --json <artifact> --baseline <baseline>
scripts/safe-run.sh ./scripts/bench/perf-hotspots.sh --quick --json-file /tmp/hotspots.json
scripts/safe-run.sh ./scripts/bench/bench-vs-tsgo.sh --filter '<row>' --json-file /tmp/bench.json

Use focused compile guard or cargo nextest run -E 'test(...)' when shortest. Do not run full conformance, emit, fourslash, or broad project suites locally.

Cache Checklist

What semantic question is cached?
What stable identity is the key? Avoid cross-file NodeIndex and cross-interner TypeId.
Does the key include all behavior modes: relation, variance, freshness, contextual typing, inference source, any, target/module/options, request scope, cycle/fuel, file/session generation?
Where is reset/invalidation?
What happens cold/disabled/order-randomized?
Is size/residency bounded or observable?

PR/comment packet: Project Corpus Impact, invariant, exact commands/CI, green row timing only, RSS/failure-class evidence for runtime blockers, counter deltas, noise/caveats, AgentName.