[fireairforce]

Summary

Plain string externals such as "window.ge.multimediaPlugin" currently look up a single dotted key, so the Galacean multimedia plugin resolves to undefined. Normalize dots to the existing internal global-property path format so this mapping reads globalThis["window"]["ge"]["multimediaPlugin"]; framework-normalized "ge.multimediaPlugin" also resolves correctly.

Limit the change to basic global strings. Advanced global objects keep their literal-key behavior, and explicit external types use their existing paths. Add one snapshot fixture with runtime assertions for the reported case.

Test Plan

• Externals snapshot suite, including the new dotted-global fixture
• cargo fmt
• cargo clippy --all-targets -- -D warnings --no-deps
• Repository pre-push checks: Rust formatting, Tombi, Biome, and typos

[chatgpt-codex-connector]

Codex Review Summary

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Review	Status	Commit	Review trigger
📝 Code Review	⚠️ Failed 2026-10-22T04:12:21.255059Z We couldn’t complete this review. Comment @codex review to try again.	fdf95c4	PR opened

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[PeachScript]

+1

[github-actions]

📊 Performance Benchmark Report (with-antd)

Utoopack Performance Report

Report ID: utoopack_performance_report_20261022_061636
Generated: 2026-10-22 06:16:36
Trace File: trace_antd.json (0.3GB, 0.84M spans)
Test Project: examples/with-antd

---

Executive Summary

Metric	Value	Assessment
Total Wall Time	6,864.4 ms	Baseline
Total Thread Work (de-duped)	20,401.4 ms	Non-overlapping busy time
Effective Parallelism	3.0x	thread_work / wall_time
Working Threads	10	Threads with actual spans
Thread Utilization	29.7%	⚠️ Suboptimal
Total Spans	844,640	All B/E + X events
Meaningful Spans (>= 10us)	215,532	(25.5% of total)
Tracing Noise (< 10us)	629,108	(74.5% of total)

---

Build Phase Timeline

Shows when each build phase is active and how much CPU it consumes.
Self-Time is the time spent exclusively in that phase (excluding children).

Phase	Spans	Inclusive (ms)	Self-Time (ms)	Wall Range (ms)
Resolve	47,370	6,459.7	1,751.7	3,180.2
Parse	8,163	1,453.8	1,092.3	6,113.7
Analyze	141,629	43,284.6	9,118.1	6,022.2
Chunk	5,084	5,362.3	799.1	2,541.5
Codegen	10,472	2,411.8	1,516.2	2,191.2
Emit	33	48.2	24.1	11.6
Other	2,781	7,972.3	4,494.6	6,864.3

---

Workload Distribution by Diagnostic Tier

Category	Spans	Inclusive (ms)	% Work	Self-Time (ms)	% Self
P0: Scheduling & Resolution	189,253	50,396.1	247.0%	11,125.6	54.5%
P1: I/O & Heavy Tasks	2,893	130.5	0.6%	106.5	0.5%
P2: Architecture (Locks/Memory)	0	0.0	0.0%	0.0	0.0%
P3: Asset Pipeline	22,289	9,257.9	45.4%	3,425.1	16.8%
P4: Bridge/Interop	0	0.0	0.0%	0.0	0.0%
Other	1,097	7,208.2	35.3%	4,139.0	20.3%

---

Top 20 Tasks by Self-Time

Self-time is the exclusive duration: time spent in the task itself, not in sub-tasks.
This is the most accurate indicator of where CPU cycles are actually spent.

Self (ms)	Inclusive (ms)	Count	Avg Self (us)	P95 Self (ms)	Max Self (ms)	% Work	Task Name	Top Caller
4,341.4	25,513.5	95,393	45.5	0.1	15.6	21.3%	module	module (61%)
2,652.0	3,034.4	19	139581.5	355.6	480.9	13.0%	save snapshot	persist (5%)
2,353.0	2,478.7	2,464	955.0	3.0	292.5	11.5%	analyze ecmascript module	module (70%)
1,512.9	14,109.6	34,129	44.3	0.1	9.0	7.4%	process module	process module (82%)
1,143.3	3,154.4	25,014	45.7	0.1	6.1	5.6%	internal resolving	internal resolving (75%)
1,018.8	1,380.3	5,991	170.1	0.6	91.2	5.0%	parse ecmascript	parse ecmascript (66%)
837.3	914.3	8,239	101.6	0.4	6.1	4.1%	precompute code generation	generate merged code (52%)
767.0	931.4	7,024	109.2	0.4	140.0	3.8%	compute async module info	compute async module info (58%)
681.4	5,111.2	3,980	171.2	0.3	45.2	3.3%	chunking	chunking (44%)
678.1	2,213.2	827	819.9	1.8	237.2	3.3%	generate merged code	chunking (54%)
599.6	3,296.4	21,668	27.7	0.0	4.0	2.9%	resolving	module (58%)
464.1	464.1	329	1410.6	1.2	284.7	2.3%	generate source map	code generation (83%)
396.0	833.2	130	3046.1	4.7	246.5	1.9%	emit code	generate merged code (42%)
383.6	383.6	8	47956.2	188.5	208.0	1.9%	blocking	save snapshot (62%)
334.1	595.1	1,323	252.6	0.1	189.2	1.6%	write all entrypoints to disk	write all entrypoints to disk (14%)
214.8	1,033.4	1,904	112.8	0.3	54.3	1.1%	code generation	code generation (83%)
114.4	247.1	1,062	107.7	0.2	11.1	0.6%	compute async chunks	compute async chunks (53%)
91.0	103.5	742	122.6	0.0	33.1	0.4%	compute binding usage info	compute binding usage info (47%)
73.5	73.5	2,169	33.9	0.0	3.0	0.4%	read file	parse ecmascript (91%)
37.7	68.7	1,861	20.3	0.0	12.2	0.2%	collect mergeable modules	collect mergeable modules (100%)

---

Critical Path Analysis

The longest sequential dependency chains that determine wall-clock time.
Focus on reducing the depth of these chains to improve parallelism.

Rank	Self-Time (ms)	Depth	Path
1	688.9	3	persist → save snapshot → blocking
2	487.4	6	chunking → generate merged code → emit code → emit code → emit code → read file
3	335.8	4	chunking → generate merged code → emit code → generate source map
4	331.4	2	save snapshot → blocking
5	293.6	3	process module → analyze ecmascript module → analyze ecmascript module

---

Batching Candidates

High-volume tasks dominated by a single parent. If the parent can batch them,
it drastically reduces scheduler overhead.

Task Name	Count	Top Caller (Attribution)	Avg Self	P95 Self	Total Self
process module	34,129	process module (82%)	44.3 us	0.07 ms	1,512.9 ms
internal resolving	25,014	internal resolving (75%)	45.7 us	0.09 ms	1,143.3 ms

---

Duration Distribution

Range	Count	Percentage
<10us	629,108	74.5%
10us-100us	139,178	16.5%
100us-1ms	64,941	7.7%
1ms-10ms	11,176	1.3%
10ms-100ms	199	0.0%
>100ms	38	0.0%

---

Action Items

1. [P0] Focus on tasks with the highest Self-Time — these are where CPU cycles are actually spent.
2. [P0] Use Batching Candidates to identify callers that should use try_join or reduce #[turbo_tasks::function] granularity.
3. [P1] Check Build Phase Timeline for phases with disproportionate wall range vs. self-time (= serialization).
4. [P1] Inspect P95 Self (ms) for heavy monolith tasks. Focus on long-tail outliers, not averages.
5. [P1] Review Critical Paths — reducing the longest chain depth directly improves wall-clock time.
6. [P2] If Thread Utilization < 60%, investigate scheduling gaps (lock contention or deep dependency chains).

Report generated by Utoopack Performance Analysis Agent