dogfood
Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", or "test this app" on mobile. Produces a structured report with reproducible evidence: screenshots, optional repro videos, and detailed steps for every issue.
DeepseekModel
官方收录技能
质量 优秀 · 90
v1.0.0
获取
https://deepseekmodel.com/api/download.php?id=callstackincubator-agent-skills-plugins-vendored-agents-skills-dogfood-skill-md&format=skill
下载 .skill
标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name dogfood description Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", or "test this app" on mobile. Produces a structured report with reproducible evidence: screenshots, optional repro videos, and detailed steps for every issue. allowed-tools Bash(agent-device:*), Bash(npx agent-device:*) 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 user@example.com 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 session 1. Initialize mkdir -p {OUTPUT_DIR}/screenshots {OUTPUT_DIR}/videos cp {SKILL_DIR}/templates/dogfood-report-template.md {OUTPUT_DIR}/report.md 2. Launch/Auth Start a named session and launch target app: agent-device --session {SESSION} open {TARGET_APP} --platform {PLATFORM} agent-device --session {SESSION} snapshot -i If 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 -i For 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 -i Map 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 -i after UI transitions to avoid stale refs. Periodically capture logs path and 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 path 5. 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.mp4 Reproduce 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.png Capture final broken state: sleep 2 agent-device --session {SESSION} screenshot {OUTPUT_DIR}/screenshots/issue-{NNN}-result.png Stop recording: agent-device --session {SESSION} record stop Append 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}.png Set 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} close Report 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 fill for clear-then-type semantics; use type for 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
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该技能未提供触发词。
下载的 .skill 包内含以下字段。
| 字段 | 说明 |
|---|---|
| format | 格式标识(skill/v1) |
| skill_id | 技能唯一 ID |
| name | 技能名称 |
| version | 版本号 |
| description | 技能描述 |
| category | 所属分类(数组) |
| trigger_words | 触发词列表 |
| tags | 标签列表 |
| source | 来源标识 |
| source_url | 来源链接(本页地址) |
| exported_at | 导出时间(每次下载生成) |
| system_prompt | 系统提示词正文 |
| model_config | 模型参数:provider / model / temperature / max_tokens / top_p |
| examples | 示例 |
| install_guide | 各平台导入说明(Coze / Dify / Claude / 自定义框架) |