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AI Diff Review Card — Free Code Change Accept/Reject Snippet

AI Diff Review Card · Cards · Plain HTML, CSS & JS · Live preview

CategoryCards
TagsAI UI

Copy & paste

Source Code

<div class="drc-card">
  <div class="drc-head">
    <div class="drc-head-left">
      <span class="drc-icon">&#10022;</span>
      <div>
        <h3>AI-suggested change</h3>
        <p id="drcFile">utils/formatCurrency.js</p>
      </div>
    </div>
    <span class="drc-confidence" id="drcConfidence">92% confident</span>
  </div>

  <div class="drc-diff" id="drcDiff"></div>

  <div class="drc-reason">
    <strong>Why:</strong> <span id="drcReason">Rounds to the nearest cent before formatting to avoid floating-point display errors like $9.999999.</span>
  </div>

  <div class="drc-actions">
    <button type="button" class="drc-reject" id="drcReject">Reject</button>
    <button type="button" class="drc-accept" id="drcAccept">Accept change</button>
  </div>

  <div class="drc-result" id="drcResult" hidden></div>
</div>

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What's included

Features

Red/green line diff
Data-driven del/add/context lines render with familiar diff coloring and gutter markers.
Confidence badge
Sets reviewer expectations about how carefully to check the suggestion.
Plain-language reason
Explains why the change was suggested, not just what changed.
Accept / Reject actions
Clear binary decision with a visible result state afterward.
HTML-escaped code rendering
Diff lines are safely escaped so arbitrary code text can't break the layout.
Monospace diff styling
Matches familiar code-review tool conventions for instant legibility.
Decided-state UI
Actions disappear once a decision is made, replaced by a clear outcome.
No dependencies
Pure HTML, CSS, and vanilla JavaScript — no diff library required.

About this UI Snippet

AI Diff Review Card — Red/Green Diff with Confidence and Accept/Reject

Screenshot of the AI Diff Review Card snippet rendered live

AI coding assistants and autonomous agents increasingly propose code changes rather than making them silently — and the review moment is where trust is won or lost. This snippet builds a self-contained diff review card in plain HTML, CSS, and vanilla JavaScript: a red/green line-by-line diff, a confidence badge, a plain-language explanation of *why* the change was made, and clear Accept/Reject actions.

A line-typed diff, not a diff library

Each line in the DIFF array is tagged del, add, or ctx (context). renderDiff() maps that into a gutter marker (−, +, or blank) and a colored background — red with strikethrough for removed lines, green for added lines, muted for unchanged context — the same visual language as GitHub and every major code review tool, without pulling in a diffing library. Because it's just data, generating this from a real diff (e.g. from Git or an LLM's structured output) is a straightforward mapping step.

A confidence badge that sets expectations

The 92% badge in the header signals the AI's own certainty about the suggestion, letting a reviewer calibrate how carefully to check it — a low-confidence change deserves more scrutiny than a high-confidence one. This is the same trust-calibration idea behind this library's AI confidence badge, applied specifically to code suggestions.

Explaining the "why," not just the "what"

Below the diff, a reason panel states in plain language why the change was suggested — here, a floating-point rounding bug — rather than leaving the reviewer to reverse-engineer intent from the code alone. This single addition is often what separates an AI suggestion a developer trusts enough to accept quickly from one they ignore.

Decisive actions with a visible outcome

Accepting or rejecting hides the action row and shows a clear result message, so the card visibly reflects the reviewer's decision rather than staying in an ambiguous "still pending" state. Pair it with an AI action approval card for non-code AI actions, or an AI review summary card to summarize a batch of decisions like this one.

Customizing it

Swap the hard-coded DIFF array for a real diff parsed from your AI backend's output, add a "view full file" expand action, or add a third "request changes" option that opens a comment field instead of a binary accept/reject.

Step by step

How to Use

  1. 1
    Paste HTML, CSS, and JSA diff review card renders with a red/green line diff and a confidence badge.
  2. 2
    Read the reason panelA plain-language explanation states why the AI suggested the change.
  3. 3
    Click Accept or RejectThe action buttons hide and a result message confirms the decision.
  4. 4
    Edit the DIFF arrayChange the del/add/ctx lines to show a different suggested change.
  5. 5
    Change the confidence valueUpdate the badge text and color to reflect the AI's certainty.
  6. 6
    Wire up real actionsReplace decide() with calls to apply or discard the change via your API.

Real-world uses

Common Use Cases

AI coding assistants
Let developers review a suggested change as a red and green diff before it is applied, with a confidence badge setting expectations.
Autonomous coding agents
Gate agent-proposed commits behind an explicit decision, pairing with an AI action approval card for non-code actions.
Pull request review bots
Surface a bot's suggested fix inline, using a code diff viewer for the full file view when more context is needed.
Refactor suggestion tools
Show a batch of proposed refactors one at a time, each with a plain-language reason explaining why the change was suggested.
Lint fixes and learning
Let users accept or reject an automatic fix, or teach diff reading with a styled example, comparing with code comparison.
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Got questions?

Frequently Asked Questions

The DIFF array already encodes each line's type (removed, added, or unchanged context) rather than computing a diff at render time. renderDiff() simply maps each type to a gutter marker and a CSS class. If you need to diff two arbitrary strings client-side, you would still want a small diffing algorithm — this snippet assumes the diff is already known, which is typically true when an AI backend returns a structured suggestion.

Confidence helps a reviewer calibrate scrutiny — a change the AI is 98% confident about (a straightforward bug fix) usually needs a quick glance, while a 60% confidence change (a larger refactor) deserves a closer read. Surfacing that number turns a binary "trust it or don't" into a more honest, gradated signal.

Replace the accept button's decide("accepted") call with a request to your backend or version control API that applies the underlying patch, then call decide("accepted") once that request succeeds (or decide with an error state if it fails).

Yes — extend DIFF to include a hunk header type (showing something like @@ -12,3 +12,4 @@) between groups of lines, and add a small amount of spacing or a divider between hunks in renderDiff(). The accept/reject actions can stay scoped to the whole suggestion or be split per hunk depending on your workflow.

Pass the diff lines and confidence as props, render them with a map/v-for/*ngFor, and lift the accept/reject decision to a callback prop so the parent can apply or discard the underlying patch. The escapeHtml step becomes unnecessary since JSX/templates escape text content by default.