Agent skill

Simulink Profile Initialization

by hashgraph-online in hashgraph-online/awesome-codex-plugins

Profile and analyze the initialization (compile) phase of a Simulink model.

Apache-2.0Auto-check passedDevelopment

Install Simulink Profile Initialization

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill simulink-profile-initialization -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins simulink-profile-initialization --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/summer521521/MATLAB_Simulink_plugin/skills/simulink-profile-initialization .claude/skills/simulink-profile-initialization && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
simulink-profile-initialization
GitHub stars
1.2k
Token cost
~1.5k tokens
SKILL.md length
647 words
Files
15 (incl. scripts)
Skills in repo
736
Repo updated
First seen
Licence
Apache-2.0

At a glance

Profile and analyze the initialization (compile) phase of a Simulink model.

  • Works in 8 steps: Determine whether to collect or analyze → Collect profiling data → Analyze timing overview (out_after.mat) → …
  • The user asks to profile model initialization
  • SKILL.md covers Your Capabilities, Setup and Workflow
  • Diagnose slow model loading/compiling

What it does

Simulink Profile Initialization is an agent skill from hashgraph-online/awesome-codex-plugins. Profile and analyze the initialization (compile) phase of a Simulink model. Use when the user asks to profile model initialization, diagnose slow model loading/compiling, or analyze existing init profiling data files (outafter.mat, perfTracer.mat, profilerResults.mat, modelCompileDiary.txt).

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including scripts.

It sits in Development, covering Performance optimization. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.

When your agent uses it

  • The user asks to profile model initialization
  • Diagnose slow model loading/compiling
  • Analyze existing init profiling data files (outafter.mat
  • ProfilerResults.mat

Example prompts

  • “/simulink-profile-initialization”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Determine whether to collect or analyze
  2. Collect profiling data
  3. Analyze timing overview (out_after.mat)
  4. Analyze Performance Tracer phases (perfTracer.mat)
  5. Analyze MATLAB Profiler results (profilerResults.mat)
  6. Check ModelRefRebuild setting (modelCompileDiary.txt)
  7. Generate interactive HTML report
  8. Summarize findings

What it can do on your machine

Read from SKILL.md and the folder at commit 16b4156. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 12 files in scripts/, which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Simulink Profile Initialization loads about 1.5k tokens when it runs. Until then it costs about 81 tokens; SKILL.md has 647 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~81
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 16b4156, republished under its Apache-2.0 licence (© hashgraph-online). 647 words, ~1,540 tokens.

Download SKILL.mdSave it as .claude/skills/simulink-profile-initialization/SKILL.md (or your agent's skills folder). This skill also uses 14 other files; get the full folder from GitHub.
name
simulink-profile-initialization
description
Profile and analyze the initialization (compile) phase of a Simulink model. Use when the user asks to profile model initialization, diagnose slow model loading/compiling, or analyze existing init profiling data files (out_after.mat, perfTracer.mat, profilerResults.mat, modelCompileDiary.txt).

You are an expert in profiling and analyzing the initialization (compile) phase of Simulink models. You help users either collect profiling data or analyze existing profiling results to identify bottlenecks.

Your Capabilities

  • Run the initialization profiling harness on a loaded Simulink model
  • Analyze four output files: out_after.mat, perfTracer.mat, profilerResults.mat, modelCompileDiary.txt
  • Distinguish MATLAB shipping code from user code in profiler results
  • Identify actionable bottlenecks the user can address
  • Check model configuration for inefficient settings

Setup

Before running any analysis scripts, run the setup function located in the skill's scripts/ folder. This self-locating script adds its own folder to the MATLAB path regardless of where the skill is installed or which AI agent is used.

matlab
run('SCRIPTS_FOLDER/setup.m')

Replace SCRIPTS_FOLDER with the absolute path to this skill's scripts/ directory (derived from the <skill_files> entries below — use the parent folder of any listed .m file).

This makes the following functions available:

  • collectInitProfiling — run the profiling harness on a loaded model
  • analyzeTimingOverview — display timing breakdown from SimulationOutput
  • analyzePerfTracer — display Performance Tracer phase durations
  • analyzeProfilerResults — display user vs shipping code profiler results
  • checkModelRefRebuild — check ModelRefRebuild setting from diary
  • generateFlamegraph — generate a standalone interactive HTML flamegraph
  • generateInitProfilingReport — generate a combined HTML report with flamegraphs

Workflow

Step 0 — Determine whether to collect or analyze
  • If the user has existing profiling files (any of the four .mat/.txt files), skip to Step 2.
  • If the user wants to profile a model, proceed to Step 1.
Step 1 — Collect profiling data

The model must be loaded in Simulink. Run the collectInitProfiling script:

matlab
collectInitProfiling('ModelName')

If no model name is provided, it uses bdroot. This produces four files in the current directory:

  • out_after.mat: SimulationOutput with timing metadata
  • profilerResults.mat: MATLAB Profiler results (variable p)
  • perfTracer.mat: Simulink Performance Tracer raw data
  • modelCompileDiary.txt: Command window diary capturing displayed info

It also creates a timestamped .zip archive of all four files.

Step 2 — Analyze timing overview (out_after.mat)
matlab
analyzeTimingOverview('out_after.mat')

Report the total wall time and how it breaks down between initialization, execution, and termination. For a StopTime=0 run, nearly all time should be in initialization.

Step 3 — Analyze Performance Tracer phases (perfTracer.mat)

Run the analyzePerfTracer script:

matlab
analyzePerfTracer('perfTracer.mat')

This parses PerformanceTracingRawDataVector using a stack-based approach to match nested start/end phase pairs, and displays a table of all phases with duration and percentage of total wall time.

Show full SKILL.md (271 more words)Show less
Step 4 — Analyze MATLAB Profiler results (profilerResults.mat)

Run the analyzeProfilerResults script:

matlab
analyzeProfilerResults('profilerResults.mat')

This computes self time (TotalTime minus children time) for each function, separates shipping code (under matlabroot) from user code, and displays two ranked tables:

  1. User files — Top 20 by self time: Actionable by the user.
  2. Shipping files — Top 20 by self time: For awareness only.
Step 5 — Check ModelRefRebuild setting (modelCompileDiary.txt)

Run the checkModelRefRebuild script:

matlab
checkModelRefRebuild('modelCompileDiary.txt')

This checks the ModelRefRebuild parameter value recorded in the diary:

  • 'IfOutOfDate': Good — recommended value ("If changes in known dependencies detected").
  • 'AssumeUpToDate': Informational — skips all rebuild checks. Fast, but risks stale targets.
  • 'IfOutOfDateOrStructuralChange' or 'Force': Inefficient — flag to user and recommend changing.
Step 6 — Generate interactive HTML report

Generate a combined HTML report with interactive flamegraphs:

matlab
generateInitProfilingReport()                        % uses files in current directory
generateInitProfilingReport('path/to/data')          % specify data directory
generateInitProfilingReport('path/to/data', 'report.html')  % specify output path

This produces a self-contained HTML file with:

  • Summary dashboard (init time, execution time, user vs shipping code split)
  • Interactive compile-phase flamegraph (click to zoom, breadcrumb navigation)
  • Interactive user-code call tree flamegraph (MathWorks shipping code collapsed)
  • Phase table sorted by duration
  • User code and shipping code profiler tables
  • ModelRefRebuild setting status

To generate only a standalone flamegraph from Performance Tracer data:

matlab
generateFlamegraph('perfTracer.mat')                 % saves flamegraph_perfTracer.html
generateFlamegraph('perfTracer.mat', 'output.html')  % specify output path
Step 7 — Summarize findings

Present a structured summary with:

  1. Total initialization time from timing metadata
  2. Phase breakdown from Performance Tracer (top phases by duration)
  3. Shipping vs user code split (percentage of self-time in each category)
  4. User-actionable bottlenecks (top user-code functions by self time, with call counts)
  5. ModelRefRebuild setting check (flag if not 'IfOutOfDate')
  6. Recommendations prioritized by potential time savings

Focus recommendations on what the user can actually change. For shipping-code bottlenecks, mention them for awareness but note they are internal to MATLAB.

© hashgraph-online, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 14 other files (scripts) in plugins/summer521521/MATLAB_Simulink_plugin/skills/simulink-profile-initialization of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • reference/flamegraph_template.html
  • reference/init_profiling_template.html
  • scripts/analyzePerfTracer.m
  • scripts/analyzeProfilerResults.m
  • scripts/analyzeTimingOverview.m
  • scripts/checkModelRefRebuild.m
  • scripts/collectInitProfiling.m
  • scripts/generateFlamegraph.m
  • scripts/generateInitProfilingReport.m
  • scripts/jsonEscape.m
  • scripts/node2json.m
  • scripts/parsePerfTracerData.m
  • scripts/parseProfilerData.m
  • scripts/setup.m

Open the folder on GitHubat commit 16b4156

Compare with similar skills

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LLM Torch Profiler Analysissgl-project/sglang37k2 repos~6.4kAutomated safety check: PassApache-2.0
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Electron Heap Snapshot Analysiskeybase/client9.3k—~875Automated safety check: PassBSD-3-Clause

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Categories

Questions about Simulink Profile Initialization

What does Simulink Profile Initialization do?

Profile and analyze the initialization (compile) phase of a Simulink model. Simulink Profile Initialization is an agent skill from hashgraph-online/awesome-codex-plugins. Profile and analyze the initialization (compile) phase of a Simulink model.

When should I use Simulink Profile Initialization?

Simulink Profile Initialization fits situations like: the user asks to profile model initialization; diagnose slow model loading/compiling; analyze existing init profiling data files (outafter.mat; profilerResults.mat.

How do I install Simulink Profile Initialization in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill simulink-profile-initialization -a claude-code`. Or copy the skill folder (plugins/summer521521/MATLAB_Simulink_plugin/skills/simulink-profile-initialization in hashgraph-online/awesome-codex-plugins) into .claude/skills/simulink-profile-initialization in your project. Claude Code loads it when a task matches its description.

How do I install Simulink Profile Initialization in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill simulink-profile-initialization -a codex`. Or copy the skill folder (plugins/summer521521/MATLAB_Simulink_plugin/skills/simulink-profile-initialization in hashgraph-online/awesome-codex-plugins) into .agents/skills/simulink-profile-initialization in your project. Codex loads it when a task matches its description.

Can I use Simulink Profile Initialization in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill simulink-profile-initialization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/simulink-profile-initialization, .gemini/skills/simulink-profile-initialization, .github/skills/simulink-profile-initialization and .opencode/skills/simulink-profile-initialization in your project.

What does Simulink Profile Initialization need to run?

SKILL.md names no scripts, command-line tools or credentials: Simulink Profile Initialization is instructions for the agent only.

Does Simulink Profile Initialization access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Simulink Profile Initialization safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Simulink Profile Initialization use?

Simulink Profile Initialization is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Simulink Profile Initialization use?

About 1.5k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Simulink Profile Initialization?

Skills that share tags, products or a category with Simulink Profile Initialization: Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), LLM Torch Profiler Analysis (sgl-project/sglang, 37k stars), Py (crazyguitar/pysheeet, 8.2k stars) and Cmux Debugging Guide (manaflow-ai/cmux, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Simulink Profile Initialization?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,232 GitHub stars. The repository holds 736 skills in this directory. The repository was last updated on October 6, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.