dogfood
Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or review the quality of a web application. Produces a structured report with full reproduction evidence (screenshots, repro steps) so findings can be handed directly to responsible teams.
Best use case
dogfood is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or review the quality of a web application. Produces a structured report with full reproduction evidence (screenshots, repro steps) so findings can be handed directly to responsible teams.
Teams using dogfood should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/dogfood/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How dogfood Compares
| Feature / Agent | dogfood | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or review the quality of a web application. Produces a structured report with full reproduction evidence (screenshots, repro steps) so findings can be handed directly to responsible teams.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Dogfood
Systematically explore a web application, find issues, and produce a report with full reproduction evidence for every finding.
Uses [agent-browser](https://github.com/vercel-labs/agent-browser), a headless browser automation CLI.
## Setup
Only the **Target URL** is required. Everything else has sensible defaults.
| Parameter | Default | Example override |
|-----------|---------|-----------------|
| **Target URL** | _(required)_ | `vercel.com`, `http://localhost:3000` |
| **Session name** | Slugified domain (e.g., `vercel.com` -> `vercel-com`) | `--session my-session` |
| **Output directory** | `./dogfood-output/` | `Output directory: /tmp/qa` |
| **Scope** | Full app | `Focus on the billing page` |
| **Authentication** | None | `Sign in to user@example.com` |
If the user says something like "dogfood vercel.com", start immediately with defaults. Do not ask clarifying questions unless authentication is mentioned but credentials are missing.
Always use `agent-browser` directly (not `npx agent-browser`). The direct binary uses the fast Rust client.
Before starting, check prerequisites:
```bash
command -v agent-browser || true
command -v surge || true # only needed if user asks to publish
```
If `agent-browser` is unavailable, do not stop. Use browser tools or Playwright as a fallback and read `references/playwright-surge-fallback.md`. The goal is evidence-backed QA, not loyalty to one browser driver.
## Workflow
```
1. Initialize Set up session, output dirs, report file
2. Authenticate Sign in if needed, save state
3. Orient Navigate to starting point, take initial snapshot
4. Explore Systematically visit pages and test features
5. Document Screenshot + record each issue as found
6. Wrap up Update summary counts, close session
```
### 1. Initialize
```bash
mkdir -p {OUTPUT_DIR}/screenshots {OUTPUT_DIR}/videos
```
Copy the report template into the output directory and fill in the header fields:
```bash
cp {SKILL_DIR}/templates/dogfood-report-template.md {OUTPUT_DIR}/report.md
```
Where `{SKILL_DIR}` is the directory containing this SKILL.md file.
Start a named session:
```bash
agent-browser --session {SESSION} open {TARGET_URL}
agent-browser --session {SESSION} wait --load networkidle
```
### 2. Authenticate
If the app requires login:
```bash
agent-browser --session {SESSION} snapshot -i
# Identify login form refs, fill credentials
agent-browser --session {SESSION} fill @e1 "{EMAIL}"
agent-browser --session {SESSION} fill @e2 "{PASSWORD}"
agent-browser --session {SESSION} click @e3
agent-browser --session {SESSION} wait --load networkidle
```
For OTP/email codes: ask the user, wait for their response, then enter the code.
After successful login, save state for potential reuse:
```bash
agent-browser --session {SESSION} state save {OUTPUT_DIR}/auth-state.json
```
### 3. Orient
Take an initial annotated screenshot and snapshot to understand the app structure:
```bash
agent-browser --session {SESSION} screenshot --annotate {OUTPUT_DIR}/screenshots/initial.png
agent-browser --session {SESSION} snapshot -i
```
Identify the main navigation elements and map out the sections to visit.
### 4. Explore
Read [references/issue-taxonomy.md](references/issue-taxonomy.md) for the full list of what to look for and the exploration checklist.
**Strategy: work through the app systematically:**
- Start from the main navigation. Visit each top-level section.
- Within each section, test interactive elements: click buttons, fill forms, open dropdowns/modals.
- Check edge cases: empty states, error handling, boundary inputs.
- Try realistic end-to-end workflows (create, edit, delete flows).
- Check the browser console for errors periodically.
**At each page:**
```bash
agent-browser --session {SESSION} snapshot -i
agent-browser --session {SESSION} screenshot --annotate {OUTPUT_DIR}/screenshots/{page-name}.png
agent-browser --session {SESSION} errors
agent-browser --session {SESSION} console
```
Use your judgment on how deep to go. Spend more time on core features and less on peripheral pages. If you find a cluster of issues in one area, investigate deeper.
### 5. Document Issues (Repro-First)
Steps 4 and 5 happen together: explore and document in a single pass. When you find an issue, stop exploring and document it immediately before moving on. Do not explore the whole app first and document later.
Every issue must be reproducible. When you find something wrong, do not just note it: prove it with evidence.
**Choose the right level of evidence for the issue:**
#### Interactive / behavioral issues (functional, ux, console errors on action)
These require user interaction to reproduce. Use full repro with video and step-by-step screenshots:
1. **Start a repro video** _before_ reproducing:
```bash
agent-browser --session {SESSION} record start {OUTPUT_DIR}/videos/issue-{NNN}-repro.webm
```
2. **Walk through the steps at human pace.** Pause 1-2 seconds between actions so the video is watchable. Take a screenshot at each step:
```bash
agent-browser --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/issue-{NNN}-step-1.png
sleep 1
# Perform action (click, fill, etc.)
sleep 1
agent-browser --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/issue-{NNN}-step-2.png
sleep 1
# ...continue until the issue manifests
```
3. **Capture the broken state.** Pause so the viewer can see it, then take an annotated screenshot:
```bash
sleep 2
agent-browser --session {SESSION} screenshot --annotate {OUTPUT_DIR}/screenshots/issue-{NNN}-result.png
```
4. **Stop the video:**
```bash
agent-browser --session {SESSION} record stop
```
5. Write numbered repro steps in the report, each referencing its screenshot.
#### Static / visible-on-load issues (typos, placeholder text, clipped text, misalignment, console errors on load)
These are visible without interaction. A single annotated screenshot is sufficient. No video, no multi-step repro:
```bash
agent-browser --session {SESSION} screenshot --annotate {OUTPUT_DIR}/screenshots/issue-{NNN}.png
```
Write a brief description and reference the screenshot in the report. Set **Repro Video** to `N/A`.
---
**For all issues:**
1. **Append to the report immediately.** Do not batch issues for later. Write each one as you find it so nothing is lost if the session is interrupted.
2. **Increment the issue counter** (ISSUE-001, ISSUE-002, ...).
### 6. Wrap Up
Aim to find **5-10 well-documented issues**, then wrap up. Depth of evidence matters more than total count: 5 issues with full repro beats 20 with vague descriptions.
After exploring:
1. Re-read the report and update the summary severity counts so they match the actual issues. Every `### ISSUE-` block must be reflected in the totals.
2. If using `agent-browser`, close the session:
```bash
agent-browser --session {SESSION} close
```
3. If the user asked to publish, create a readable `index.html` in the output directory, keep `report.md` and artifacts alongside it, deploy with Surge, then verify HTTP 200 before replying. See `references/playwright-surge-fallback.md` for the exact Surge pattern.
4. Tell the user the report is ready and summarize findings: total issues, breakdown by severity, most critical items, and the public URL if published.
## Guidance
- **Repro is everything.** Every issue needs proof, but match the evidence to the issue. Interactive bugs need video and step-by-step screenshots. Static bugs (typos, placeholder text, visual glitches visible on load) only need a single annotated screenshot.
- **Don't record video for static issues.** A typo or clipped text doesn't benefit from a video. Save video for issues that involve user interaction, timing, or state changes.
- **For interactive issues, screenshot each step.** Capture the before, the action, and the after so someone can see the full sequence.
- **Write repro steps that map to screenshots.** Each numbered step in the report should reference its corresponding screenshot. A reader should be able to follow the steps visually without touching a browser.
- **Be thorough but use judgment.** You are not following a test script. You are exploring like a real user would. If something feels off, investigate.
- **Write findings incrementally.** Append each issue to the report as you discover it. If the session is interrupted, findings are preserved. Never batch all issues for the end.
- **Never delete output files.** Do not `rm` screenshots, videos, or the report mid-session. Do not close the session and restart. Work forward, not backward.
- **Never read the target app's source code.** You are testing as a user, not auditing code. Do not read HTML, JS, or config files of the app under test. All findings must come from what you observe in the browser.
- **Check the console.** Many issues are invisible in the UI but show up as JS errors or failed requests.
- **Test like a user, not a robot.** Try common workflows end-to-end. Click things a real user would click. Enter realistic data.
- **Type like a human.** When filling form fields during video recording, use `type` instead of `fill` (types character-by-character). Use `fill` only outside of video recording when speed matters.
- **Pace repro videos for humans.** Add `sleep 1` between actions and `sleep 2` before the final result screenshot. Videos should be watchable at 1x speed.
- **Be efficient with commands.** Batch multiple `agent-browser` commands in a single shell call when they are independent. Use `agent-browser --session {SESSION} scroll down 300` for scrolling.
- **Also test the backend directly — but verify your payloads.** When the app hits an API, `curl` the endpoints independently. But first, inspect what the frontend actually sends (use `eval` to read fetch call arguments, or check network requests). A 500 from a malformed test payload is YOUR bug, not the app's. If you can't determine the correct payload shape, note it as "API returned error with test payload; may be payload mismatch" rather than declaring "API is broken." Reporting false positives destroys credibility.
- **Distinguish automation artifacts from real bugs.** Some issues only appear because of how agent-browser interacts with the page (e.g., `$` signs eaten by `type`, buttons unclickable via ref but fine for real users). Before reporting, ask: "Would a human user see this?" If unsure, mark as "unconfirmed — may be automation artifact" and suggest manual verification.
## Pitfalls (agent-browser quirks)
These are real issues encountered during dogfood sessions. Read before starting.
- **`wait --load networkidle` often times out on SPAs.** Skip it if it fails and proceed with screenshots/snapshots. The page is usually ready.
- **`press` takes only a key, not a selector.** Correct: `press Enter`. Wrong: `press @e12 Enter`. To press a key while focused on an element, `click` or `focus` the element first, then `press`.
- **There is no `js`, `exec`, or `viewport` command.** Use `eval` to run JavaScript. There is no built-in viewport resize; use `eval "window.resizeTo(w, h)"` (may not work in headless) or accept the default viewport.
- **`type` may interpret `$` as special.** The `type` command sends keystrokes and `$` followed by digits can be swallowed or misinterpreted. If testing dollar amounts, verify the displayed text matches what you typed (use `eval` or `get text` to read back the field value). Use `fill` instead of `type` when exact fidelity matters more than human-like typing. Flag dollar-sign issues as "unconfirmed — may be automation artifact" unless verified in a real browser.
- **Ref-based click can fail with "matched N elements".** This happens when the page has changed since the last `snapshot`. Always re-run `snapshot -i` to get fresh refs. If a button still can't be clicked by ref, use a CSS selector or `eval "document.querySelector('...').click()"` as fallback.
- **Be efficient with commands.** Batch multiple `agent-browser` commands in a single shell call when they are independent. Use `agent-browser --session {SESSION} scroll down 300` for scrolling.
- **Also test the backend directly — but verify your payloads.** When the app hits an API, `curl` the endpoints independently. But first, inspect what the frontend actually sends (use `eval` to read fetch call arguments, or check network requests). A 500 from a malformed test payload is YOUR bug, not the app's. If you can't determine the correct payload shape, note it as "API returned error with test payload; may be payload mismatch" rather than declaring "API is broken." Reporting false positives destroys credibility.
- **Distinguish automation artifacts from real bugs.** Some issues only appear because of how agent-browser interacts with the page (e.g., `$` signs eaten by `type`, buttons unclickable via ref but fine for real users). Before reporting, ask: "Would a human user see this?" If unsure, mark as "unconfirmed — may be automation artifact" and suggest manual verification.
## Pitfalls (agent-browser quirks)
These are real issues encountered during dogfood sessions. Read before starting.
- **`wait --load networkidle` often times out on SPAs.** Skip it if it fails and proceed with screenshots/snapshots. The page is usually ready.
- **`press` takes only a key, not a selector.** Correct: `press Enter`. Wrong: `press @e12 Enter`. To press a key while focused on an element, `click` or `focus` the element first, then `press`.
- **There is no `js`, `exec`, or `viewport` command.** Use `eval` to run JavaScript. There is no built-in viewport resize; use `eval "window.resizeTo(w, h)"` (may not work in headless) or accept the default viewport.
- **`type` may interpret `$` as special.** The `type` command sends keystrokes and `$` followed by digits can be swallowed or misinterpreted. If testing dollar amounts, verify the displayed text matches what you typed (use `eval` or `get text` to read back the field value). Use `fill` instead of `type` when exact fidelity matters more than human-like typing. Flag dollar-sign issues as "unconfirmed — may be automation artifact" unless verified in a real browser.
- **Ref-based click can fail with "matched N elements".** This happens when the page has changed since the last `snapshot`. Always re-run `snapshot -i` to get fresh refs. If a button still can't be clicked by ref, use a CSS selector or `eval "document.querySelector('...').click()"` as fallback.
- **The submit/send button pattern.** Many chat UIs have submit buttons inside textareas that are hard to target. Fallback sequence: (1) try `click @ref`, (2) try `press Enter` after focusing the textarea, (3) use `eval` to find and click the button via DOM query.
## References
| Reference | When to Read |
|-----------|--------------|
| [references/issue-taxonomy.md](references/issue-taxonomy.md) | Start of session: calibrate what to look for, severity levels, exploration checklist |
| [references/design-critique.md](references/design-critique.md) | When the session scope includes UI/UX quality — run after functional exploration to score heuristics, flag visual/color/typography issues, and produce a Critical/Important/Polish triage |
| [references/playwright-surge-fallback.md](references/playwright-surge-fallback.md) | When `agent-browser` is unavailable/failing, when using Playwright/browser tools as the driver, or when publishing a public dogfood report to Surge |
## Templates
| Template | Purpose |
|----------|---------|
| [templates/dogfood-report-template.md](templates/dogfood-report-template.md) | Report structure copied to output dir at start |Related Skills
writer
Write content in Eric's voice — articles, blog posts, tweets, social media posts, marketing copy, newsletter drafts. Loads WRITING-STYLE.md and enforces kill phrases.
positioning-angles
Use when defining product positioning, choosing strategic angles, crafting value propositions, competitive positioning, product messaging, differentiation strategy, or go-to-market angles. Also use for 'how should I position my app', 'what angle should I use', 'painkiller vs vitamin', or 'market positioning'.
outline-generator
Use when generating outlines, article structures, content outlines, blog outlines, planning article sections, structuring posts, breaking down topics into sections, or organizing ideas for long-form content. Also use for 'outline this', 'structure this article', or 'plan the sections'.
last30days-open
Use only when the user explicitly asks for the open variant of last30days, including watchlists, briefings, and history queries. Sources: Reddit, X, YouTube, web.
last30days
Use when researching what happened in the last 30 days on a topic. Also triggered by 'last30'. Sources: Reddit, X, YouTube, web. Produces expert-level summary with copy-paste-ready prompts.
hooks
Use when generating hooks, headlines, titles, and scroll-stopping openers for content. Also use when analyzing viral posts, Reels, TikToks, YouTube Shorts, or successful social examples to extract reusable hook patterns and improve hook guidance.
evaluate-content
Use when judging content quality OR editing/improving existing copy: shareability, readability, voice, cuttability, angle, copy sweeps.
editor-in-chief
Use when a first draft is complete and all Phase 1 gates are done: topic selected (seo-research), title approved (hooks), outline approved (outline-generator), draft written (writer). Runs autonomous diagnosis-prescribe-rewrite loop before Substack.
copywriting
Write or improve marketing copy for any surface: pages, ads, app stores, landing pages, TikTok/Meta scripts, push notifications, UGC. Combines page copy frameworks with direct response principles.
content-strategy
Use when building content strategy: hooks, angles, and ideas from what's trending now. Covers organic and paid creative across TikTok, X, YouTube, Meta, LinkedIn.
content-pipeline
Orchestrator for the 3-article content pipeline — runs research phase, spawns parallel article sub-agents, creates Typefully drafts. Use when running the full content pipeline (usually via cron at 3am).
yt-dlp
Download audio/video from YouTube and other sites using yt-dlp. Use when the user asks to download music, songs, albums, podcasts, or video from YouTube or similar platforms. Triggers on 'download song', 'get mp3', 'yt-dlp', 'youtube download', 'rip audio'.