profile-dart-code

Name: profile-dart-code
Author: kevmoo

11installs16forks

How to install profile-dart-code?

kevmoo/dash_skills/profile-dart-code

$npx -y skills add kevmoo/dash_skills --skill profile-dart-code

Installs into the current project.

Summary

Profile Dart command-line applications using the VM Service protocol to capture CPU samples and identify performance bottlenecks. Helps agents automate CPU profiling, generate function call breakdown summaries, and export JSON profiles without a browser or DevTools.

Files · 1

View on GitHub

SKILL.md

1	# Dart CPU Profiling
2
3	Guidelines and automated tools for capturing CPU profiles and identifying
4	bottlenecks in Dart command-line applications.
5
6	## When to use this skill
7	- When asked to profile, optimize, or benchmark CPU execution of a Dart script
8	or CLI tool.
9	- When investigating hot loops, heavy function calls, or unexpected execution
10	overhead.
11
12	## Workflow
13	1. Ensure clean compilation: Make sure the target Dart script runs cleanly
14	(`dart run <script.dart>`).
15	2. Run Profiler Script: Use the automated profiling helper script inside
16	this skill directory to launch the target app with VM Service observability
17	enabled, capture CPU samples, and output top-consuming functions.
18	3. Analyze & Optimize: Review the self and total sample percentages
19	reported by the tool to pinpoint bottlenecks (e.g., excessive object
20	allocation, costly hashing, virtual dispatch overhead).
21
22	## Running the Profiler Helper Script
23
24	This repository includes a zero-dependency (using only official `vm_service`)
25	profiling script that launches any Dart file, connects to the VM Service, waits
26	for execution to complete (`--pause-isolates-on-exit`), retrieves CPU samples,
27	and prints a clean summary while exporting the full JSON profile.
28
29	Run it from any working directory:
30	```bash
31	dart run <dash_skills_repo>/skills/profile-dart-code/scripts/bin/profile.dart --out=cpu_profile.json -- <path_to_target.dart> [target_arguments...]
32	```
33
34	### Script Arguments
35	- `-o, --out=<file>`: Output file path to save the raw JSON CPU profile
36	(default: `cpu_profile.json`).
37	- `-p, --period=<micros>`: Sampling interval in microseconds (default: `1000`µs
38	= 1ms). Minimum `50`µs.
39	- `-- <target.dart> [args...]`: The Dart script to profile, followed by any
40	arguments passed to `main()`.
41
42	> [!WARNING]
43	> Potential Hangs: When profiling or debugging Dart targets using VM services,
44	> target exceptions or connection issues can cause the process to hang
45	> indefinitely. Ensure your target script handles timeouts, and monitor the
46	> process output.
47
48	### Example Output
49	```
50	Connecting to VM service at ws://127.0.0.1:8181/ws...
51	Target execution paused at exit. Retrieving CPU profile samples...
52
53	=== Top CPU Functions (Self Samples) ===
54	1. _PuzzleSmart._shiftSlice (self: 34.2%, total: 41.0%)
55	2. _countInversions (self: 18.5%, total: 18.5%)
56	3. shortestPaths (self: 12.1%, total: 98.4%)
57
58	Saved complete JSON profile to: cpu_profile.json
59	```
60
61	## Best Practices for Interpreting Profiles
62	1. Focus on Self % vs. Total %: High `self %` indicates where CPU time is
63	spent directly inside a function's own body (math, loop branching, array
64	indexing). High `total %` with low `self %` indicates a dispatcher or outer
65	orchestration loop.
66	2. Look for Hidden Overhead: Watch out for implicit object allocations
67	(`_copyData`, iterator wrappers, closure creation) inside tight loops.
68	3. Verify Optimizations Empirically: Always record baseline sample counts
69	and execution duration (`time -v`) before and after applying optimizations.

People who liked this also viewed

6 picks

Type

profile-dart-code

11installs16forks

View on GitHub

How to install profile-dart-code?

kevmoo/dash_skills/profile-dart-code

$npx -y skills add kevmoo/dash_skills --skill profile-dart-code

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Dart CPU Profiling
2
3	Guidelines and automated tools for capturing CPU profiles and identifying
4	bottlenecks in Dart command-line applications.
5
6	## When to use this skill
7	- When asked to profile, optimize, or benchmark CPU execution of a Dart script
8	or CLI tool.
9	- When investigating hot loops, heavy function calls, or unexpected execution
10	overhead.
11
12	## Workflow
13	1. Ensure clean compilation: Make sure the target Dart script runs cleanly
14	(`dart run <script.dart>`).
15	2. Run Profiler Script: Use the automated profiling helper script inside
16	this skill directory to launch the target app with VM Service observability
17	enabled, capture CPU samples, and output top-consuming functions.
18	3. Analyze & Optimize: Review the self and total sample percentages
19	reported by the tool to pinpoint bottlenecks (e.g., excessive object
20	allocation, costly hashing, virtual dispatch overhead).
21
22	## Running the Profiler Helper Script
23
24	This repository includes a zero-dependency (using only official `vm_service`)
25	profiling script that launches any Dart file, connects to the VM Service, waits
26	for execution to complete (`--pause-isolates-on-exit`), retrieves CPU samples,
27	and prints a clean summary while exporting the full JSON profile.
28
29	Run it from any working directory:
30	```bash
31	dart run <dash_skills_repo>/skills/profile-dart-code/scripts/bin/profile.dart --out=cpu_profile.json -- <path_to_target.dart> [target_arguments...]
32	```
33
34	### Script Arguments
35	- `-o, --out=<file>`: Output file path to save the raw JSON CPU profile
36	(default: `cpu_profile.json`).
37	- `-p, --period=<micros>`: Sampling interval in microseconds (default: `1000`µs
38	= 1ms). Minimum `50`µs.
39	- `-- <target.dart> [args...]`: The Dart script to profile, followed by any
40	arguments passed to `main()`.
41
42	> [!WARNING]
43	> Potential Hangs: When profiling or debugging Dart targets using VM services,
44	> target exceptions or connection issues can cause the process to hang
45	> indefinitely. Ensure your target script handles timeouts, and monitor the
46	> process output.
47
48	### Example Output
49	```
50	Connecting to VM service at ws://127.0.0.1:8181/ws...
51	Target execution paused at exit. Retrieving CPU profile samples...
52
53	=== Top CPU Functions (Self Samples) ===
54	1. _PuzzleSmart._shiftSlice (self: 34.2%, total: 41.0%)
55	2. _countInversions (self: 18.5%, total: 18.5%)
56	3. shortestPaths (self: 12.1%, total: 98.4%)
57
58	Saved complete JSON profile to: cpu_profile.json
59	```
60
61	## Best Practices for Interpreting Profiles
62	1. Focus on Self % vs. Total %: High `self %` indicates where CPU time is
63	spent directly inside a function's own body (math, loop branching, array
64	indexing). High `total %` with low `self %` indicates a dispatcher or outer
65	orchestration loop.
66	2. Look for Hidden Overhead: Watch out for implicit object allocations
67	(`_copyData`, iterator wrappers, closure creation) inside tight loops.
68	3. Verify Optimizations Empirically: Always record baseline sample counts
69	and execution duration (`time -v`) before and after applying optimizations.

People who liked this also viewed

6 picks

Type