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CSS Box-Shadow Code Generator VS QA Batch Scorer

Compare CSS Box-Shadow Code Generator VS QA Batch Scorer and see what are their differences

CSS Box-Shadow Code Generator

Easy and simple way to generate box-shadow and border-radius using this web app

Rating
0 reviews
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Alternatives Is it good?
QA Batch Scorer

Most contact centers review 2 to 5% of calls. This scores all of them against your own rubric, locally, for a one-time $99.

Rating
0 reviews
Pricing
Paid $99 / One-off (Unlimited agents, perpetual license)
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Alternatives Is it good?
Tacit AI
FMEAs that stay current. Tacit AI builds DFMEAs, PFMEAs and FMECAs from your design specs, process documents, manuals and failure reports, and updates them as they change. sponsored

Base details

Website, pricing, platforms and company facts side by side.

CSS Box-Shadow Code Generator
QA Batch Scorer
Website stevewalson.github.io everycallqa.com
Pricing —
Paid $99 / One-off (Unlimited agents, perpetual license) Official pricing
Platforms —
Web
Company — Startup from the United States · 2026
Listed in —
Call Center Management Quality Management Conversational Intelligence

About CSS Box-Shadow Code Generator and QA Batch Scorer

In their own words, as submitted to SaaSHub.

CSS Box-Shadow Code Generator
QA Batch Scorer

No description of CSS Box-Shadow Code Generator yet.

QA Batch Scorer reads contact center call transcripts in bulk and scores each one against a rubric you define. Every criterion is scored 0 to 5 with a verbatim quote from the transcript as evidence, so scores can be checked rather than trusted. Criteria can be marked critical, which fails a call...

Read more about QA Batch Scorer

Features and specs

What each product offers, as listed by its team.

CSS Box-Shadow Code Generator 5 features
QA Batch Scorer 3 features
  • Visual real-time preview
    The generator provides an instant visual preview of the box-shadow effect as you adjust the parameters, allowing users to see exactly how their shadow will look before copying the code.
  • Simple and intuitive interface
    The tool has a clean, straightforward interface with sliders and input fields that make it easy for beginners and experienced developers alike to create box-shadow effects without memorizing CSS syntax.
  • Free and browser-based
    The tool is completely free to use and runs entirely in the browser with no installation, sign-up, or downloads required, making it instantly accessible to anyone.
  • Quick code output
    The generator produces ready-to-use CSS box-shadow code that can be copied and pasted directly into a stylesheet, saving development time and reducing syntax errors.
  • Adjustable parameters
    Users can easily tweak key shadow properties such as horizontal offset, vertical offset, blur radius, spread radius, and color to fine-tune the exact shadow effect they need.

Possible disadvantages

  • Limited to single shadow
    The tool appears to only support generating a single box-shadow value at a time, whereas CSS allows multiple comma-separated shadows for more complex effects.
  • Minimal styling options
    The generator focuses solely on box-shadow and doesn't include related CSS properties like border-radius or background color adjustments that could help users visualize the shadow in a more realistic context.
  • No preset examples
    The tool lacks a library of pre-built shadow presets or templates that users could use as starting points, which would speed up the design process for common shadow styles.
  • Basic UI design
    The interface is quite minimal and could benefit from a more polished, modern design with better visual hierarchy and additional guidance or tooltips for less experienced users.
  • No export or save functionality
    There is no built-in way to save, bookmark, or export multiple shadow configurations for later comparison or use, so users must manually copy and store their generated values elsewhere.
  • Coverage
    Scores 100% of transcripts, not a 2-5% sample
  • Evidence
    Verbatim transcript quote behind every criterion score
  • Data handling
    Runs locally with your own API key, no vendor server

Analysis

An editorial look at what each product does well and who it suits.

CSS Box-Shadow Code Generator
QA Batch Scorer

Overall verdict

  • CSS Box-Shadow Code Generator by stevewalson.github.io is a solid, lightweight utility for developers and designers who need to quickly create box-shadow CSS without manually writing syntax. It's a good, practical tool though not a groundbreaking product—ideal for speeding up simple styling tasks.

Why this product is good

  • Provides a visual interface to adjust shadow properties like blur, spread, offset, and color in real time
  • Automatically generates accurate, ready-to-use CSS code, reducing syntax errors
  • Free and accessible directly in the browser without installation
  • Simple, minimal UI makes it easy to use even for beginners
  • Useful for quick prototyping and experimenting with different shadow effects

Recommended for

  • Front-end developers wanting to save time writing CSS manually
  • Designers experimenting with UI shadow effects
  • Students learning CSS box-shadow properties
  • Hobbyists building personal or small projects
  • Anyone needing quick CSS snippets without deep CSS expertise

No analysis of QA Batch Scorer yet.

Questions & Answers

As answered by people managing CSS Box-Shadow Code Generator and QA Batch Scorer.

What makes your product unique?

QA Batch Scorer's answer:

Three things, and the third is the one nobody else does.

It scores 100% of your transcripts rather than the 2 to 5% sample a supervisor can physically get through. Every criterion comes back with a verbatim quote from the transcript as evidence, so a score can be checked rather than trusted, and no agent has to accept a number they cannot see the basis for. And it runs entirely on your own machine using your own AI provider key, so transcripts never reach a server we control.

That last point is the structural difference. There is no account, no upload, and no vendor in the data path. It is a single HTML file you open in a browser.

Why should a person choose your product over its competitors?

QA Batch Scorer's answer:

Mostly you should not, and it is worth being clear about that.

If you need real-time agent assist, a coaching workflow, dialler integration, or audio transcription, buy a platform. Observe.AI, Scorebuddy, MaestroQA, Convin and Enthu.ai all do things this does not. This is one job done properly, not a suite.

Choose this if you are a floor under about fifty seats and the platform economics do not work. Entry pricing in this category starts around 35 to 59 dollars per agent per month, usually billed six or twelve months up front, which puts a 25-seat team somewhere between ten and seventeen thousand dollars a year on a contract. This is 99 dollars once, unlimited agents, no renewal.

Also choose it if your transcripts contain things you would rather not upload. Nothing here touches a server we run.

And choose it if you want to know what is actually on your calls before committing budget to a platform. Score a month of calls for a few dollars in API credit and you will know whether the problem justifies the spend.

How would you describe the primary audience of your product?

QA Batch Scorer's answer:

Owner-operators and ops leads at contact centers roughly 5 to 60 seats, in businesses where nobody has budget for a QA platform but the calls still carry risk.

In practice that means small BPOs, collections and receivables desks, healthcare intake teams, inbound sales floors, and in-house support teams inside small and mid-sized businesses.

The common shape is a supervisor who reviews a handful of calls a week, knows that is not coverage, and has no realistic path to changing it. The buyer is usually the owner or the person accountable for compliance exposure rather than a dedicated QA analyst, because at this size that role often does not exist.

It is not built for enterprise contact centers. Above roughly a hundred seats you want workflow, calibration tooling and integrations that this deliberately does not have.

What's the story behind your product?

QA Batch Scorer's answer:

It started from a number that most people in this industry have stopped questioning: the share of calls that actually get reviewed. On a floor under fifty seats it is usually somewhere between two and five percent, because that is what one supervisor can physically listen to in a week. Everyone treats that as a capacity fact rather than a quality problem.

Every tool built to fix it is priced for enterprise. Entry pricing in this category starts around 35 to 59 dollars per agent per month and is usually billed six or twelve months up front, which means the smallest operators, the ones with the least QA slack, are the ones priced out entirely.

The other thing that kept coming up was data. Call recordings and transcripts contain account details, payment information and disclosed hardship. Asking a small operator to upload all of that to a vendor they have never met, to solve a problem they are not sure they have yet, is a real barrier.

So this was built the other way round. One file, no account, no upload, and the buyer's own AI key so the transcripts stay in their control. One price, paid once, so trying it does not require a contract. It does one job and deliberately stops there.

It is new, and honest about that. Version 1 shipped in August 2026.

Which are the primary technologies used for building your product?

QA Batch Scorer's answer:

Deliberately almost none, and that is the point.

The whole product is a single HTML file: vanilla JavaScript, no framework, no build step, no dependencies, no package manager. It opens directly in Chrome, Edge, Firefox or Safari from your file system. There is no backend, no database and no hosting, because there is nothing to host.

Scoring is done by whichever large language model you point it at. It supports OpenRouter, Anthropic and OpenAI, calling their APIs directly from your browser with your own key. The model list is fetched live from the provider at runtime rather than hardcoded, so it does not break when a model is retired.

CSV, TSV and JSON parsing is written from scratch inside the file, so nothing has to be installed and no data passes through a third-party library.

The constraint is a feature rather than minimalism for its own sake. No server means no place for your transcripts to sit. No install means it runs on a locked-down machine without an IT ticket. No dependencies means it will still open in five years.

User comments

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