Dogfood
CallstackOfficialPublished by Callstack
- Skill
- Review and audit
- Software development
- MIT
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The dogfood skill provides a structured approach for agents to perform exploratory testing on iOS and Android applications. It guides the agent through a defined workflow, including app initialization, authentication, navigation mapping, and systematic testing of core user journeys. The skill emphasizes the collection of reproducible evidence, such as screenshots and video recordings, to document visual, functional, UX, and performance issues. It includes a standardized issue taxonomy to help categorize findings by severity and type, ensuring consistent reporting.
What it does
- Automates mobile app exploration using agent-device commands.
- Captures screenshots and video recordings as reproducible evidence for identified issues.
- Generates a structured report detailing bugs, UX issues, and functional failures.
- Supports authentication flows including email and password entry.
- Maps top-level navigation and key workflows for comprehensive coverage.
- Categorizes findings based on a predefined severity and issue taxonomy.
When to use it
- When you need to perform exploratory testing on a mobile application.
- When you are asked to hunt for bugs or identify UX issues in an app.
- When you need to generate a formal report of mobile app defects with visual evidence.
- When testing core user journeys or edge states like error handling and offline behavior.
Advantages
- Ensures consistent documentation of issues with required reproduction steps.
- Reduces manual effort in capturing and organizing visual evidence.
- Provides a clear, standardized framework for severity and issue classification.
- Supports both iOS and Android platforms within a unified workflow.
Usage examples
- “Dogfood the latest build of the companion app on iOS.”
- The agent initiates a session, navigates the app, documents any discovered issues in a report, and provides a summary of findings.
- “Perform a bug hunt on the Android version of our settings module.”
- The agent explores the settings area, captures screenshots of any layout or functional defects, and compiles them into a structured report.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/callstackincubator/dogfood/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip dogfood.zip -d .agents/skills
Documentation by Callstack
Dogfood (agent-device)
Systematically explore a mobile app, find issues, and produce a report with full reproduction evidence for every finding.
Setup
Only the Target app is required. Everything else has sensible defaults.
| Parameter | Default | Example override |
|---|---|---|
| Target app | (required) | Settings, com.example.app, deep link URL |
| Platform | Infer from user context; otherwise ask (ios or android) | --platform ios |
| Session name | Slugified app/platform (for example settings-ios) | --session my-session |
| Output directory | ./dogfood-output/ | Output directory: /tmp/mobile-qa |
| Scope | Full app | Focus on onboarding and profile |
| Authentication | None | Sign in to [email protected] |
If the user gives enough context to start, begin immediately with defaults. Ask follow-up only when a required detail is missing (for example platform or credentials).
Prefer direct agent-device binary when available.
Workflow
1. Initialize Set up session, output dirs, report file
2. Launch/Auth Open app and sign in if needed
3. Orient Capture initial snapshot and map navigation
4. Explore Systematically test flows and states
5. Document Record reproducible evidence per issue
6. Wrap up Reconcile summary, close session1. Initialize
mkdir -p {OUTPUT_DIR}/screenshots {OUTPUT_DIR}/videos
cp {SKILL_DIR}/templates/dogfood-report-template.md {OUTPUT_DIR}/report.md2. Launch/Auth
Start a named session and launch target app:
agent-device --session {SESSION} open {TARGET_APP} --platform {PLATFORM}
agent-device --session {SESSION} snapshot -iIf login is required:
agent-device --session {SESSION} snapshot -i
agent-device --session {SESSION} fill @e1 "{EMAIL}"
agent-device --session {SESSION} fill @e2 "{PASSWORD}"
agent-device --session {SESSION} press @e3
agent-device --session {SESSION} wait 1000
agent-device --session {SESSION} snapshot -iFor OTP/email codes: ask the user, wait for input, then continue.
3. Orient
Capture initial evidence and navigation anchors:
agent-device --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/initial.png
agent-device --session {SESSION} snapshot -iMap top-level navigation, tabs, and key workflows before deep testing.
4. Explore
Read references/issue-taxonomy.md for severity/category calibration.
Strategy:
Move through each major app area (tabs, drawers, settings pages).
Test core journeys end-to-end (create, edit, delete, submit, recover).
Validate edge states (empty/error/loading/offline/permissions denied).
Use
diff snapshot -iafter UI transitions to avoid stale refs.Periodically capture
logs pathand inspect the app log when behavior looks suspicious.
Useful commands per screen:
agent-device --session {SESSION} snapshot -i
agent-device --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/{screen-name}.png
agent-device --session {SESSION} appstate
agent-device --session {SESSION} logs path5. Document Issues (Repro-First)
Explore and document in one pass. When you find an issue, stop and fully capture evidence before continuing.
Interactive/behavioral issues
Use video + step screenshots:
Start recording:
agent-device --session {SESSION} record start {OUTPUT_DIR}/videos/issue-{NNN}-repro.mp4Reproduce with visible pacing. Capture each step:
agent-device --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/issue-{NNN}-step-1.png
sleep 1
# perform action
sleep 1
agent-device --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/issue-{NNN}-step-2.pngCapture final broken state:
sleep 2
agent-device --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/issue-{NNN}-result.pngStop recording:
agent-device --session {SESSION} record stopAppend issue immediately to report with numbered steps and screenshot references.
Static/on-load issues
Single screenshot is sufficient; no video required:
agent-device --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/issue-{NNN}.pngSet Repro Video to N/A in the report.
6. Wrap Up
Target 5-10 well-evidenced issues, then finish:
Reconcile summary severity counts in
report.md.Close session:
agent-device --session {SESSION} closeReport total issues, severity breakdown, and highest-risk findings.
Guidance
Repro quality matters more than issue count.
Use refs (
@eN) for fast exploration, selectors for deterministic replay assertions when needed.Re-snapshot after any mutation (navigation, modal, list update, form submit).
Use
fillfor clear-then-type semantics; usetypefor incremental typing behavior checks.Keep logs optional and targeted: enable/read app logs only when useful for diagnosis.
Never read source code of the app under test; findings must come from observed runtime behavior.
Write each issue immediately to avoid losing evidence.
Never delete screenshots/videos/report artifacts during a session.
References
| Reference | When to Read |
|---|---|
| references/issue-taxonomy.md | Start of session; severity/categories/checklist |
Templates
| Template | Purpose |
|---|---|
| templates/dogfood-report-template.md | Copy into output directory as the report file |
Files
- ATTRIBUTION.mdAdded by AutoGineer910 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md6.8 KiB
- references/issue-taxonomy.md2.8 KiB
- templates/dogfood-report-template.md1.7 KiB
LICENSE
MIT License Copyright (c) 2026 Callstack Incubator Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Declares allowed tools
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Callstack
- Publisher
- Callstack (Official)
- Source
- callstackincubator/agent-skills · plugins/vendored/.agents/skills/dogfood · commit 59e9d17
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Callstack.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download dogfood.zip