AI Change Proof
After the change, the agent verifies it in layers: structural inspection, syntax/type/build checks, targeted behaviour testing, regression checks, and final diff/scope inspection.
$9
Works with the AI Agents you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+21 moreClaude CodeCursorCodex CLIMuseDots
Manus
Grok
Grok Bot+18 agentsAI Change Proof
Example session with this skill installed
Fix a feature without disturbing the existing application
The settings page has a Save button that currently does nothing.
Fix the Save button.
Important constraints
- Do not redesign the settings page.
- Do not change the existing API routes.
- Do not change the database schema.
- Do not modify unrelated settings behavior.
- Preserve any existing uncommitted work.
- Before editing, establish the current state and identify the files that actually need to change.
- After the fix, prove that the Save action works and show exactly what changed.
- Read your context and instructions
- Compiled the ai change proof
Summary
I fixed the settings Save action without redesigning the page, changing API routes, changing the database schema, or overwriting pre-existing work.
The change was kept within the existing settings form flow.
Change contract
| Requirement | Result |
|---|---|
| Make Save perform the existing save operation | Implemented |
| Preserve existing settings UI | Preserved |
| Do not change API routes | Preserved |
| Do not change database schema | Preserved |
| Preserve pre-existing user changes | Preserved |
| Verify the Save behavior | Verified |
| Inspect final change scope | Verified |
Checkpoint
Before editing, I inspected the repository state and identified existing changes.
The pre-existing changes were treated as protected and were not reset, stashed, cleaned, or overwritten.
Implementation
The Save button was connected to the existing form submission/save path rather than introducing a new API or replacing the settings architecture.
No unrelated refactor was performed.
Verification
Structural check
Confirmed that the intended settings component contains the Save handler and that no unrelated application areas were modified.
Build/type check
The project's existing build/type validation was run after the change.
Result: PASS
Targeted behavior
The settings Save flow was exercised directly.
Result: PASS
The button now triggers the intended save operation and reaches the existing persistence path.
Scope check
The final change set was inspected after verification.
Only the files required for the requested settings fix were changed.
No API route or database schema changes were introduced.
Final status
Requested behavior: implemented.
Protected behavior: preserved.
Verification: completed.
Unrelated changes: none identified.
Evidence
The strongest evidence is the combination of:
- the targeted Save-flow verification;
- the successful project validation;
- the final change-scope inspection.
The change is therefore considered complete within the requested boundaries.
Recovery
The pre-change state was recorded before implementation, so the change can be isolated or reverted through the project's existing version-control workflow if required.
Connects securely to your tools. The creator never sees your data.
About this skill
AI Change Proof gives coding agents a disciplined way to modify existing software without turning every request into an uncontrolled rewrite.
It establishes a baseline before editing, identifies existing user changes, defines exactly what must and must not change, creates a practical recovery checkpoint, and keeps implementation deliberately scoped.
After the change, the agent verifies it in layers: structural inspection, syntax/type/build checks, targeted behaviour testing, regression checks, and final diff/scope inspection.
The key principle is simple: a change is not complete because the code looks right. It is complete when the requested behaviour is implemented, protected work remains protected, appropriate checks pass, and the agent can show evidence for its conclusion.
AI Change Proof is especially useful when working on existing React, Node.js, TypeScript, Python, API, backend, compiler, or other software projects where preserving working behaviour matters as much as adding the new functionality.
It does not replace Git, testing, CI/CD, or human review. It provides the engineering discipline that helps an AI coding agent use those mechanisms correctly.
Requires existing test/build tools to provide proof. Cannot verify behavior without runnable checks. Does not replace human review or CI/CD pipelines.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
Reviews
No reviews yet
Be one of the first to try it. Every listed skill goes through the trust checks below.
Security scanned
Checked by our 8-point scan before listing
Fresh listing
Recently published to Agensi
Money-back guarantee
Doesn't do what its page promises? You get your money back.
Trust & safety
Security scan
Security scan passed today
Permissions
File Scopes
This skill needs file read/write and terminal access because its purpose is to establish a project baseline, make bounded code changes, run the project's existing verification commands, and inspect the final change scope. It does not require external network access, credentials, or third-party accounts.