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Agent skill

Network Request Auditing

by spencerpauly in spencerpauly/awesome-cursor-skills

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.

CC0-1.0Auto-check passedProductivity & Automation

Install Network Request Auditing

skills CLI
$ npx skills add spencerpauly/awesome-cursor-skills --skill network-request-auditing -a claude-code

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

GitHub CLI
$ gh skill install spencerpauly/awesome-cursor-skills network-request-auditing --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/spencerpauly/awesome-cursor-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/resources/network-request-auditing .claude/skills/network-request-auditing && 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
network-request-auditing
GitHub stars
842
Token cost
~778 tokens
SKILL.md length
375 words
Files
1
Skills in repo
57
Repo updated
First seen
Licence
CC0-1.0

At a glance

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.

  • Works in 3 steps: Drive the app in the browser (navigate,… → Call browser_network_requests after… → Classify and report findings using the…
  • API-heavy pages and after backend
  • SKILL.md covers How it works, Audit checklist, Steps and Notes
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Network Request Auditing is an agent skill from spencerpauly/awesome-cursor-skills. 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.

Its SKILL.md is about 780 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Productivity & Automation, covering Browser automation. The repository describes itself as: A curated list of awesome skills for Cursor. The licence is CC0-1.0.

When your agent uses it

  • API-heavy pages and after backend
  • Client networking changes

Example prompts

  • “/network-request-auditing”

Workflow steps

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

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

What it can do on your machine

Read from SKILL.md and the folder at commit 99cd265. 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

    No scripts in the folder and no shell commands in SKILL.md.

    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

Network Request Auditing loads about 778 tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 375 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~778

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from spencerpauly/awesome-cursor-skills at commit 99cd265, republished under its CC0-1.0 licence (© spencerpauly). 375 words, ~778 tokens.

Download SKILL.mdSave it as .claude/skills/network-request-auditing/SKILL.md (or your agent's skills folder).
name
network-request-auditing
description
After navigating and interacting in Cursor's built-in browser, use browser_network_requests 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.
user-invocable
true

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

  1. Drive the app in the browser (navigate, click, submit forms) so real requests fire.
  2. Call browser_network_requests after meaningful interactions (and after navigation settles).
  3. 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.
Show full SKILL.md (139 more words)Show less

Steps

  1. Start from a clean navigation — browser_navigate to the target URL (or use an existing tab via browser_tabs).

  2. Exercise the feature — interactions that trigger API usage (filters, infinite scroll, form save, modal open).

  3. Fetch network log — browser_network_requests after each logical step if the page does multiple round-trips.

  4. 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).

© spencerpauly, CC0-1.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in resources/network-request-auditing of spencerpauly/awesome-cursor-skills.

Open the folder on GitHubat commit 99cd265

Compare with similar skills

Network Request Auditing 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.

Network Request Auditing compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Network Request Auditing this skillspencerpauly/awesome-cursor-skills842—~778Automated safety check: PassCC0-1.0
Agent Browserquran/quran.com-frontend-next1.9k42 repos~3.3kAutomated safety check: PassNone
Dev-Browser CLI AutomationSawyerHood/dev-browser6.7k1 repos~455Automated safety check: PassMIT
Agent Browsersuperagent-ai/grok-cli3.5k1 repos~633Automated safety check: PassMIT
Browser Automationopenclaw/openclaw392k—~2.9kAutomated safety check: PassMIT
Camoufox CLIBin-Huang/camoufox-cli3501 repos~4.5kAutomated safety check: PassMIT

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Categories

Questions about Network Request Auditing

What does Network Request Auditing do?

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. Network Request Auditing is an agent skill from spencerpauly/awesome-cursor-skills. 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.

When should I use Network Request Auditing?

Network Request Auditing fits situations like: API-heavy pages and after backend; client networking changes.

How do I install Network Request Auditing in Claude Code?

Run `npx skills add spencerpauly/awesome-cursor-skills --skill network-request-auditing -a claude-code`. Or copy the skill folder (resources/network-request-auditing in spencerpauly/awesome-cursor-skills) into .claude/skills/network-request-auditing in your project. Claude Code loads it when a task matches its description.

How do I install Network Request Auditing in Codex?

Run `npx skills add spencerpauly/awesome-cursor-skills --skill network-request-auditing -a codex`. Or copy the skill folder (resources/network-request-auditing in spencerpauly/awesome-cursor-skills) into .agents/skills/network-request-auditing in your project. Codex loads it when a task matches its description.

Can I use Network Request Auditing 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 spencerpauly/awesome-cursor-skills --skill network-request-auditing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/network-request-auditing, .gemini/skills/network-request-auditing, .github/skills/network-request-auditing and .opencode/skills/network-request-auditing in your project.

What does Network Request Auditing need to run?

SKILL.md names no scripts, command-line tools or credentials: Network Request Auditing is instructions for the agent only.

Does Network Request Auditing 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 Network Request Auditing 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. Review the folder before installing.

What licence does Network Request Auditing use?

Network Request Auditing is published under the CC0-1.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Network Request Auditing use?

About 778 tokens (SKILL.md is roughly 3.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Network Request Auditing?

Skills that share tags, products or a category with Network Request Auditing: Agent Browser (quran/quran.com-frontend-next, 1.9k stars), Dev-Browser CLI Automation (SawyerHood/dev-browser, 6.7k stars), Agent Browser (superagent-ai/grok-cli, 3.5k stars) and Browser Automation (openclaw/openclaw, 392k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Network Request Auditing?

spencerpauly (a GitHub user) maintains it in spencerpauly/awesome-cursor-skills, which has 842 GitHub stars. The repository holds 57 skills in this directory. The repository was last updated on August 2, 2026.

Source: spencerpauly/awesome-cursor-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.