network-request-auditing

Q: How do I install network-request-auditing?

Run npx skills add https://github.com/spencerpauly/awesome-cursor-skills --skill network-request-auditing in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/network-request-auditing/ (personal) or .claude/skills/network-request-auditing/ (project).

by spencerpaulyBackend & APIs

After navigating and interacting in Cursor's built-in browser, use browsernetworkrequests to audit every fetch/XHR for failures, slowness, duplicate calls, and suspicious payloads. Use for API-heavy pages and after backend or client networking changes.

Installs: 439
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/spencerpauly/awesome-cursor-skills --skill network-request-auditing

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads network-request-auditing automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Network Request Auditing

Deep-dive network health using the cursor-ide-browser MCP. This skill focuses on browser_network_requests — not just “any 500s” but patterns that indicate bugs, waste, or security issues.

How it works

Drive the app in the browser (navigate, click, submit forms) so real requests fire.
Call browser_network_requests after meaningful interactions (and after navigation settles).
Classify and report findings using the criteria below.

Follow cursor-ide-browser workflow rules: use browser_snapshot before structural interactions; after actions that change the page, take a fresh snapshot before the next interaction.

Audit checklist

Failures

4xx / 5xx — list method, URL (path + query), status, and whether the UI handled the error.
CORS or network errors — often misconfigured origins or mixed content.

Performance

Slow requests — flag requests with high latency (e.g. > 500 ms server time if timings are visible; otherwise note unusually large waterfalls).
Duplicate calls — same URL + method fired multiple times in one user action (often a React effect or missing deduplication).
Oversized payloads — responses that look huge for what the UI needs (suggest pagination, field selection, or compression).

Security and privacy

Sensitive data in URLs — tokens or PII in query strings.
Missing auth — API calls that should send credentials or bearer tokens but do not (compare with adjacent authenticated calls).

Correctness

Unexpected hosts — calls to third parties not documented for the feature (trackers, accidental leaks).
Preflight storms — excessive OPTIONS requests may indicate wrong CORS caching or too many distinct origins.

Steps

Start from a clean navigation — browser_navigate to the target URL (or use an existing tab via browser_tabs).
Exercise the feature — interactions that trigger API usage (filters, infinite scroll, form save, modal open).
Fetch network log — browser_network_requests after each logical step if the page does multiple round-trips.
Report — structured output:
- Summary counts (failed, slow, duplicate groups).
- Table or bullet list of issues with URL pattern (not necessarily full secrets), status, category (failure / perf / security / correctness).
- Recommended next code changes or investigations.

Notes

Iframe traffic may not appear in the same log — note if the feature runs inside an iframe.
Compare against expected API design; a 404 might be correct for “optional resource not found” if handled in UI.
Pair with browser_console_messages for errors that do not surface as failed HTTP (e.g. parse errors after 200).

FAQ

What does the network-request-auditing skill do?

How do I install network-request-auditing?

Run npx skills add https://github.com/spencerpauly/awesome-cursor-skills --skill network-request-auditing in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/network-request-auditing/ (personal) or .claude/skills/network-request-auditing/ (project).

Which AI agents can use network-request-auditing?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is network-request-auditing safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains network-request-auditing?

It is published by spencerpauly in spencerpauly/awesome-cursor-skills. It has 439 recorded installs.