agent-device-evidence

Records iOS: Native and Android: Native MP4 evidence for the test or repro steps declared in an Expensify GitHub PR or issue. The source of truth is the test/repro steps themselves, not the surrounding code or context - the skill works equally well on a PR's ### Tests section, an issue's ## Action Performed: block, or any future Markdown body where steps are clearly authored.

Specializes the agent-device skill: delegates device lifecycle (bundle ID, Metro, device pick, session, open) to its Bring-up, then captures one artifact per declared flow per platform, writes a JSON manifest, and surfaces local file paths.

The skill is autonomous and non-interactive. It never pauses for user input mid-run. All inputs are provided at invocation time; all failures surface as structured errors with exit codes.

HybridApp-only (the parent skill's pre-flight enforces this). Standalone (non-HybridApp) builds are out of scope - production mobile evidence runs against HybridApp.

Scope

In scope: iOS: Native (iOS Simulator), Android: Native (Android Emulator), HybridApp dev build only. Inputs may come from PRs or issues - the skill does not gate on code changes.

Out of scope: Android: mWeb Chrome, iOS: mWeb Safari, iOS: mWeb Chrome, Windows: Chrome, MacOS: Chrome / Safari. Decline with EXIT 4 and point to a browser-driver skill (playwright-app-testing). Standalone (non-HybridApp) builds. Decline with EXIT 7 BRING_UP_FAILED per the parent skill's gate.

Inputs

Bare numbers are rejected (PRs and issues share the GitHub number namespace; the URL path is the safe disambiguator). No interactive prompts.

Triage gates (run in order, before any device work)

1. Detect source kind from the URL: /pull/N → PR, /issues/N → issue. Anything else → exit 8 BAD_INPUT.

2. Fetch the source body:

   • PR: gh pr view <num> --json title,body
   • Issue: gh issue view <num> --json title,body,labels

3. Platform resolution - in priority order:

   1. --platforms arg (CSV, wins all).
   2. PR source: explicit prose markers in title or ### Tests body - iOS only, Android only, On iOS:, On Android:.
   3. Issue source: the ## Platforms: checkbox list. Filled boxes denote where the bug reproduces; restrict to the matching native platforms.
   4. Default: both ios and android.

   Aliases: iOS: Native ≡ iOS: App (both → ios); Android: Native ≡ Android: App (both → android). All mWeb / Windows / MacOS variants are out of scope.

   If the only platforms matched are out of scope (e.g. an issue checks only MacOS: Chrome / Safari), exit 4 PLATFORM_UNSUPPORTED.

4. Steps parsing - extract the steps section and produce a flow list (see below). If the flow list is empty, exit 3 NO_FLOWS.

Steps parsing

See references/steps-parsing.md.

Phase 1 cache

Simple map: flow steps → .ad script. If the steps haven't changed, reuse the cached script and skip the warm-up.

• Path: ~/.cache/agent-device-evidence/.ad-cache/<fingerprint>.ad
• Fingerprint: sha256(precondition + json(steps) + platform). Platform is included so iOS and Android don't share an entry (different selectors).
• Hit → copy to $TEST_FLOW.ad, mark cached: true in the manifest, skip Phase 1, proceed to Phase 2.
• Miss → run Phase 1, write the script to the cache on success.

The skill does not delete, invalidate, or retry cache entries. If a cached .ad is stale, the flow is marked phase2_failed. To recover, edit the steps (which changes the fingerprint) or wipe ~/.cache/agent-device-evidence/.ad-cache/ externally.

Capture loop (per flow per platform)

Two phases per flow. Lifecycle delegated to the parent skill's bring-up. Phase 1 is skipped on cache hit (see above).

Shared setup (run once per platform, before the first flow)

1. Run the agent-device bring-up for the target platform. The parent skill resolves bundle ID, starts Metro, picks/confirms the device, manages session, and opens the app for sanity verification. Capture the resolved $APP_ID (bundle ID) and $DEVICE_NAME for re-opens in Phases 1 and 2.

   • If bring-up fails for any reason (HybridApp gate, missing dev build, Metro start, simulator boot, etc.), exit 7 BRING_UP_FAILED and surface the parent skill's error verbatim.
   • Selector discipline (id > role+label, no coordinate fallback unless 0 a11y nodes) follows the parent skill's flows/README.md.
   • Non-interactive overrides for the parent bring-up (this skill never prompts):
     • Device pick (parent step 5, "If multiple are booted, ask the user which"): pick the first booted device in agent-device devices --json order, deterministically. Log the choice in the manifest under device_selected.
     • Session reuse vs reset (parent step 6, line 73): always reset for sessions not created in the current invocation - run agent-device close --shutdown --session <name> without prompting. Phase 1 and Phase 2 both rely on cold starts, so reuse of stale sessions is never desired here.

2. Close the bring-up session so each phase starts cold:

   agent-device close
   

3. Set up run directory - persistent, append-only:

   SOURCE_KIND=<pr|issue>; SOURCE_NUM=<num>; RUN_TS=$(date -u +%Y%m%dT%H%M%SZ)
   RUN_DIR="$HOME/.cache/agent-device-evidence/$SOURCE_KIND-$SOURCE_NUM/$RUN_TS"
   mkdir -p "$RUN_DIR/ios" "$RUN_DIR/android"
   

Phase 1 - Warm-up (per flow, no camera)

Goal: produce a deterministic .ad script of the successful command sequence, plus per-step still candidates. Drives autonomously from cold start. No recording.

Skip if cached. Before any device work, consult the Phase 1 cache. On hit, copy the cached .ad to $TEST_FLOW.ad, mark cached: true in the manifest, and proceed straight to Phase 2.

On cache miss:

1. Open the app with the bring-up's resolved values:

   agent-device open "$APP_ID" --device "$DEVICE_NAME"
   

2. Drive setup actions based on the flow's Precondition: block (if any) and what the steps imply. Setup actions go into the .ad script up to the marker; everything after the marker is what Phase 2 records.

3. Drive the test flow - one numbered step at a time. For each step:

   • Send the step text verbatim to the agent-device LLM driver.
   • On success, append the final, successful action to $TEST_FLOW.ad. Do not append actions that needed retries on different selectors.
   • If a value is explicit in the step (e.g. "Enter $42.50"), pass it through verbatim. If not, the LLM picks a context-appropriate value and the chosen value is recorded in params: in the manifest.
   • The post-action agent-device snapshot (taken for selector matching) is saved as a candidate still - flow-<id>-step-<n>-<label>.png. Free side-effect.

4. Verify final state - agent-device is exists "<selector>" on the post-condition implied by the last step.

5. Close session - agent-device close.

6. Sanity-check the script is non-empty:

   test -s "$TEST_FLOW.ad" || { record per-flow status "phase1_failed: empty script"; continue }
   

7. Write to cache - on success, copy $TEST_FLOW.ad to ~/.cache/agent-device-evidence/.ad-cache/<fingerprint>.ad and write the meta sidecar.

Phase 2 - Recording (per flow, deterministic replay)

Goal: clean MP4 of only the test-flow steps. No snapshots on camera, no retries, no LLM thinking time.

1. Open the app fresh with the bring-up's resolved values:

   agent-device open "$APP_ID" --device "$DEVICE_NAME"
   

2. Replay setup silently - everything in the .ad script up to the marker. Off-camera. The app reaches the test starting state.

3. Start recording:

   agent-device record start "$RUN_DIR/$PLATFORM/flow-$ID.mp4" --fps 24
   

   Android: adb screenrecord has a 3-min hard cap. Per-flow MP4s rarely hit this; if a flow exceeds, mark status: phase2_failed and continue.

4. Replay test-flow portion:

   agent-device replay "$TEST_FLOW.ad" --from-marker
   

5. Stop recording:

   agent-device record stop
   

6. Close session - agent-device close.

7. Verify artifact:

   test -s "$RUN_DIR/$PLATFORM/flow-$ID.mp4" && file "$RUN_DIR/$PLATFORM/flow-$ID.mp4" \
     || { mark phase2_failed; continue }
   

On Phase 2 replay failure: mark the flow phase2_failed and continue to the next flow.

Multi-flow chunking

Multiple flows in one PR share a single Phase 2 session (one agent-device open + replay-to-marker), with record start / record stop per flow. State carries between flows unless Phase 1 flagged requires_cold_start: true for a flow, in which case Phase 2 closes and re-opens before that flow.

Single-step verify-only flows

For flows classified kind: still:

• Phase 1 still drives autonomously to the verification screen.
• Phase 2 opens fresh, replays setup, takes one screenshot at the verification screen via agent-device screenshot, and writes flow-<id>.png. No record start/stop.

Output

Run-output layout

~/.cache/agent-device-evidence/
├── .ad-cache/                            # cross-source Phase 1 cache (see "Phase 1 cache")
│   ├── <fingerprint>.ad
│   └── <fingerprint>.meta.json
└── <source-kind>-<source-num>/           # per-source run output, e.g. pr-89475/ or issue-89855/
    └── <run-ts>/
        ├── manifest.json
        ├── ios/
        │   ├── flow-1.mp4
        │   ├── flow-1-step-2-tap-signin.png
        │   ├── flow-2.png   (still-only flow)
        │   └── ...
        └── android/
            └── ...

Run output is persistent across reboots and append-only - the skill never deletes prior runs or cache entries.

Manifest schema

See references/manifest-schema.md.

Handoff

After all platforms, the skill prints the run directory and lists per-flow paths. The user drags each artifact into the PR's ### Screenshots/Videos section (or attaches to the issue, depending on source). The skill never edits the source.

Exit codes

Cost guards

Hitting any cap marks the flow phase1_failed / phase2_failed and proceeds to the next flow.

Error handling

See references/error-handling.md.

Out of scope (do not do these)

The skill must not attempt any of the following. If a request implies one of these, refuse or delegate.

• Mobile web and Desktop platforms (iOS: mWeb Safari, Android: mWeb Chrome, MacOS: Chrome / Safari) - belong in playwright-app-testing or a future browser-driver skill. Exit 4 PLATFORM_UNSUPPORTED.
• Standalone (non-HybridApp) builds - parent skill is HybridApp-only and this specialization inherits the gate. Production mobile evidence runs against HybridApp.
• Device lifecycle (Metro, simulator boot, bundle ID resolution, session reuse, app install verification) - fully delegated to the parent skill's Bring-up. Do not call agent-device metro prepare, xcrun simctl, or is-hybrid-app.sh directly.
• Editing the PR body or posting PR comments - the skill only writes local files. The user handles upload.
• Interactive prompts of any kind - CI is the eventual host; the skill must run end-to-end without human input.
• Test data cleanup. Accounts/expenses/workspaces created during runs accumulate; rely on periodic test-account reset.