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Agent skill

App Callback Workflows

by VectorSpaceLab in VectorSpaceLab/AREX-Skill

A skill your agent uses for Plotly Dash app layouts, callbacks, pages, assets, configuration, clientside callbacks, Jupyter display, CSP, and app-level debugging.

MITAuto-check passedData & Analytics

Install App Callback Workflows

skills CLI
$ npx skills add VectorSpaceLab/AREX-Skill --skill app-callback-workflows -a claude-code

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

GitHub CLI
$ gh skill install VectorSpaceLab/AREX-Skill app-callback-workflows --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/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repositories/repo-skills/dash/sub-skills/app-callback-workflows .claude/skills/app-callback-workflows && 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
app-callback-workflows
GitHub stars
328
Token cost
~1.4k tokens
SKILL.md length
460 words
Files
7 (incl. scripts, references)
Skills in repo
159
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses for Plotly Dash app layouts, callbacks, pages, assets, configuration, clientside callbacks, Jupyter display, CSP, and app-level debugging.

  • Works in 5 steps: For layout and callback API details, read → For pages, URL prefixes, assets, dev… → For browser-side callback functions, read → …
  • Plotly Dash app layouts
  • SKILL.md covers Start here, Main routes, Route elsewhere and Validation checklist
  • Runs Python scripts from its folder

What it does

App Callback Workflows is an agent skill from VectorSpaceLab/AREX-Skill. Use for Plotly Dash app layouts, callbacks, pages, assets, configuration, clientside callbacks, Jupyter display, CSP, and app-level debugging.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/callbacks-and-layouts.md`, `references/clientside-callbacks.md` and `references/pages-assets-and-config.md`).

It sits in Data & Analytics, covering Jupyter notebooks. It works with Jupyter and Plotly. The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is MIT.

When your agent uses it

  • Plotly Dash app layouts
  • Clientside callbacks
  • Jupyter display
  • App-level debugging

Example prompts

  • “/app-callback-workflows”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. For layout and callback API details, read
  2. For pages, URL prefixes, assets, dev tools, Jupyter, and CSP, read
  3. For browser-side callback functions, read
  4. For common failures, read
  5. Run scripts/smoke_dash_app.py for a no-browser

What it can do on your machine

Read from SKILL.md and the folder at commit ac3fe1a. 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 2 files in scripts/ (Python), 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

App Callback Workflows loads about 1.4k tokens when it runs, and up to ~6.9k if it reads all its reference files. Until then it costs about 41 tokens; SKILL.md has 460 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~41
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.9k

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 VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its MIT licence (© VectorSpaceLab). 460 words, ~1,350 tokens.

Download SKILL.mdSave it as .claude/skills/app-callback-workflows/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
app-callback-workflows
description
Use for Plotly Dash app layouts, callbacks, pages, assets, configuration, clientside callbacks, Jupyter display, CSP, and app-level debugging.
disable-model-invocation
true
metadata.disco-role
operating
license
MIT

Dash App and Callback Workflows

Use this sub-skill when a task is about using Dash as an application framework: creating layouts, registering callbacks, debugging ID/dependency validation, configuring pages/assets, or moving work into clientside callbacks.

Start here

  1. For layout and callback API details, read references/callbacks-and-layouts.md.
  2. For pages, URL prefixes, assets, dev tools, Jupyter, and CSP, read references/pages-assets-and-config.md.
  3. For browser-side callback functions, read references/clientside-callbacks.md.
  4. For common failures, read references/troubleshooting.md.
  5. Run scripts/smoke_dash_app.py for a no-browser import/layout/callback smoke check and scripts/smoke_pages_app.py for a page-registry smoke check.

Main routes

Build a basic app

Use Dash, component modules, and a component tree:

python
from dash import Dash, html, dcc

app = Dash(__name__)
app.layout = html.Div([
    dcc.Input(id="input", value="initial"),
    html.Div(id="output"),
])

Important rules:

  • Layout children must be Dash components, strings, numbers, None, or lists of those values. Raw arbitrary dicts are not valid component children.
  • Component IDs can be strings or dictionaries. Use dictionary IDs for pattern-matching callbacks.
  • If a layout is generated dynamically, either ensure callback components exist in the initial validation layout or configure dynamic-layout behavior deliberately.
Register server-side callbacks

Use @app.callback when you have an app object and @dash.callback when you need module-level callback registration. Core dependency classes are Output, Input, and State.

python
from dash import Input, Output, State, callback, no_update
from dash.exceptions import PreventUpdate

@callback(Output("output", "children"), Input("input", "value"), State("store", "data"))
def update(value, stored):
    if value is None:
        raise PreventUpdate
    if value == "keep":
        return no_update
    return f"{value}: {stored}"

Use callback troubleshooting when callbacks do not fire, fire too early, reference missing components, or form circular dependencies.

Use pattern-matching IDs

Route to dictionary IDs and wildcards when components are generated from data:

python
from dash import MATCH, ALL, Input, Output

@app.callback(
    Output({"type": "row-output", "index": MATCH}, "children"),
    Input({"type": "row-input", "index": MATCH}, "value"),
)
def per_row(value):
    return value

Use MATCH for one-to-one dynamic pairs, ALL for all matching components, and ALLSMALLER when a callback needs earlier indexed values.

Inspect callback context

Use dash.ctx or dash.callback_context inside callbacks for trigger metadata:

  • ctx.triggered_id gives the component ID that triggered the callback.
  • ctx.triggered_prop_ids maps changed id.property strings to IDs.
  • ctx.args_grouping is useful with flexible callback signatures.
  • ctx.response lets a callback set response cookies/headers in supported backends.
  • ctx.websocket is only available for WebSocket callbacks; route those tasks to server backends and async.
Show full SKILL.md (161 more words)Show less
Use pages, assets, and URL prefixes

Use Dash(__name__, use_pages=True) plus dash.register_page and dash.page_container for multi-page apps. Read pages-assets-and-config.md before changing URL prefixes, asset loading, or Jupyter display behavior.

Move simple work clientside

Use clientside callbacks for simple browser-side transformations, browser storage access, or UI work that should avoid a server round trip. Read clientside-callbacks.md for namespace registration, no_update, PreventUpdate, and set_props behavior.

Route elsewhere

Validation checklist

Before declaring an app/callback fix complete:

  • The app imports Dash, html, dcc, and dependency classes from dash.
  • Every callback component ID exists in the layout, validation layout, or a deliberate dynamic-layout configuration.
  • Callback return shape matches the Output grouping.
  • Browser console is clean for browser-backed tasks.
  • If assets, pages, or URL prefixes changed, the generated URLs use app.get_asset_url, dash.get_relative_path, or the app's configured prefix-aware helpers.

© VectorSpaceLab, MIT. 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 6 other files (scripts, references) in skills/repositories/repo-skills/dash/sub-skills/app-callback-workflows of VectorSpaceLab/AREX-Skill.

  • SKILL.md
  • references/callbacks-and-layouts.md
  • references/clientside-callbacks.md
  • references/pages-assets-and-config.md
  • references/troubleshooting.md
  • scripts/smoke_dash_app.py
  • scripts/smoke_pages_app.py

Open the folder on GitHubat commit ac3fe1a

Compare with similar skills

App Callback Workflows next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

App Callback Workflows compared with similar skills
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App Callback Workflows this skillVectorSpaceLab/AREX-Skill328—~1.4kAutomated safety check: PassMIT
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Jupyter Notebookmicrosoft/ai-agents-for-beginners77k8 repos~1kAutomated safety check: PassApache-2.0
Paper FiguresEvoScientist/EvoSkills4741 repos~4.4kAutomated safety check: PassApache-2.0
Langfuse Integration Pagelangfuse/langfuse-docs246—~3.7kAutomated safety check: PassMIT
Jupyter To Marimoericmjl/llamabot1822 repos~475Automated safety check: PassNone

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Works with

Categories

Questions about App Callback Workflows

What does App Callback Workflows do?

A skill your agent uses for Plotly Dash app layouts, callbacks, pages, assets, configuration, clientside callbacks, Jupyter display, CSP, and app-level debugging. App Callback Workflows is an agent skill from VectorSpaceLab/AREX-Skill. Use for Plotly Dash app layouts, callbacks, pages, assets, configuration, clientside callbacks, Jupyter display, CSP, and app-level debugging.

When should I use App Callback Workflows?

App Callback Workflows fits situations like: plotly Dash app layouts; clientside callbacks; jupyter display; app-level debugging.

How do I install App Callback Workflows in Claude Code?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill app-callback-workflows -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/dash/sub-skills/app-callback-workflows in VectorSpaceLab/AREX-Skill) into .claude/skills/app-callback-workflows in your project. Claude Code loads it when a task matches its description.

How do I install App Callback Workflows in Codex?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill app-callback-workflows -a codex`. Or copy the skill folder (skills/repositories/repo-skills/dash/sub-skills/app-callback-workflows in VectorSpaceLab/AREX-Skill) into .agents/skills/app-callback-workflows in your project. Codex loads it when a task matches its description.

Can I use App Callback Workflows 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 VectorSpaceLab/AREX-Skill --skill app-callback-workflows -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/app-callback-workflows, .gemini/skills/app-callback-workflows, .github/skills/app-callback-workflows and .opencode/skills/app-callback-workflows in your project.

What does App Callback Workflows need to run?

Going by SKILL.md and its folder, App Callback Workflows needs Python for the scripts in its folder. Our summary lists: Python 3.

Does App Callback Workflows 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 App Callback Workflows 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 App Callback Workflows use?

App Callback Workflows is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does App Callback Workflows use?

About 1.4k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.6k tokens, read only when the agent opens those files.

What are the alternatives to App Callback Workflows?

Skills that share tags, products or a category with App Callback Workflows: Bio Reporting Quarto Reports (GPTomics/bioSkills, 1.2k stars), Jupyter Notebook (microsoft/ai-agents-for-beginners, 77k stars), Paper Figures (EvoScientist/EvoSkills, 474 stars) and Langfuse Integration Page (langfuse/langfuse-docs, 246 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains App Callback Workflows?

VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 328 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on September 3, 2026.

Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.