pr-test

name	pr-test
description	E2E manual testing of PRs/branches using docker compose, agent-browser, and API calls. TRIGGER when user asks to manually test a PR, test a feature end-to-end, or run integration tests against a running system.
user-invocable	true
argument-hint	[worktree path or PR number] — tests the PR in the given worktree. Optional flags: --fix (auto-fix issues found)
metadata	{"author":"autogpt-team","version":"2.0.0"}

Manual E2E Test

Test a PR/branch end-to-end by building the full platform, interacting via browser and API, capturing screenshots, and reporting results.

Critical Requirements

These are NON-NEGOTIABLE. Every test run MUST satisfy ALL the following:

1. Screenshots at Every Step

• Take a screenshot at EVERY significant test step — not just at the end
• Every test scenario MUST have at least one BEFORE and one AFTER screenshot
• Name screenshots sequentially: {NN}-{action}-{state}.png (e.g., 01-credits-before.png, 02-credits-after.png)
• If a screenshot is missing for a scenario, the test is INCOMPLETE — go back and take it

2. Screenshots MUST Be Posted to PR

• Push ALL screenshots to a temp branch test-screenshots/pr-{N}
• Post a PR comment with ALL screenshots embedded inline using GitHub raw URLs
• This is NOT optional — every test run MUST end with a PR comment containing screenshots
• If screenshot upload fails, retry. If it still fails, list failed files and require manual drag-and-drop/paste attachment in the PR comment

3. State Verification with Before/After Evidence

• For EVERY state-changing operation (API call, user action), capture the state BEFORE and AFTER
• Log the actual API response values (e.g., credits_before=100, credits_after=95)
• Screenshot MUST show the relevant UI state change
• Compare expected vs actual values explicitly — do not just eyeball it

4. Negative Test Cases Are Mandatory

• Test at least ONE negative case per feature (e.g., insufficient credits, invalid input, unauthorized access)
• Verify error messages are user-friendly and accurate
• Verify the system state did NOT change after a rejected operation

5. Test Report Must Include Full Evidence

Each test scenario in the report MUST have:

• Steps: What was done (exact commands or UI actions)
• Expected: What should happen
• Actual: What actually happened
• API Evidence: Before/after API response values for state-changing operations
• Screenshot Evidence: Before/after screenshots with explanations

State Manipulation for Realistic Testing

When testing features that depend on specific states (rate limits, credits, quotas):

1. Use Redis CLI to set counters directly:

   # Find the Redis container
   REDIS_CONTAINER=$(docker ps --format '{{.Names}}' | grep redis | head -1)
   # Set a key with expiry
   docker exec $REDIS_CONTAINER redis-cli SET key value EX ttl
   # Example: Set rate limit counter to near-limit
   docker exec $REDIS_CONTAINER redis-cli SET "rate_limit:user:[e-mail]" 99 EX 3600
   # Example: Check current value
   docker exec $REDIS_CONTAINER redis-cli GET "rate_limit:user:[e-mail]"
   

2. Use API calls to check before/after state:

   # BEFORE: Record current state
   BEFORE=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/credits | jq '.credits')
   echo "Credits BEFORE: $BEFORE"
   
   # Perform the action...
   
   # AFTER: Record new state and compare
   AFTER=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/credits | jq '.credits')
   echo "Credits AFTER: $AFTER"
   echo "Delta: $(( BEFORE - AFTER ))"
   

3. Take screenshots BEFORE and AFTER state changes — the UI must reflect the backend state change

4. Never rely on mocked/injected browser state — always use real backend state. Do NOT use agent-browser eval to fake UI state. The backend must be the source of truth.

5. Use direct DB queries when needed:

   # Query via Supabase's PostgREST or docker exec into the DB
   docker exec supabase-db psql -U supabase_admin -d postgres -c "SELECT credits FROM user_credits WHERE user_id = '...';"
   

6. After every API test, verify the state change actually persisted:

   # Example: After a credits purchase, verify DB matches API
   API_CREDITS=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/credits | jq '.credits')
   DB_CREDITS=$(docker exec supabase-db psql -U supabase_admin -d postgres -t -c "SELECT credits FROM user_credits WHERE user_id = '...';" | tr -d ' ')
   [ "$API_CREDITS" = "$DB_CREDITS" ] && echo "CONSISTENT" || echo "MISMATCH: API=$API_CREDITS DB=$DB_CREDITS"
   

Arguments

• $ARGUMENTS — worktree path (e.g. $REPO_ROOT) or PR number
• If --fix flag is present, auto-fix bugs found and push fixes (like pr-address loop)

Step 0: Resolve the target

# If argument is a PR number, find its worktree
gh pr view {N} --json headRefName --jq '.headRefName'
# If argument is a path, use it directly

Determine:

• REPO_ROOT — the root repo directory: git -C "$WORKTREE_PATH" worktree list | head -1 | awk '{print $1}' (or git rev-parse --show-toplevel if not a worktree)
• WORKTREE_PATH — the worktree directory
• PLATFORM_DIR — $WORKTREE_PATH/autogpt_platform
• BACKEND_DIR — $PLATFORM_DIR/backend
• FRONTEND_DIR — $PLATFORM_DIR/frontend
• PR_NUMBER — the PR number (from gh pr list --head $(git branch --show-current))
• PR_TITLE — the PR title, slugified (e.g. "Add copilot permissions" → "add-copilot-permissions")
• RESULTS_DIR — $REPO_ROOT/test-results/PR-{PR_NUMBER}-{slugified-title}

Create the results directory:

PR_NUMBER=$(cd $WORKTREE_PATH && gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT --json number --jq '.[0].number')
PR_TITLE=$(cd $WORKTREE_PATH && gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT --json title --jq '.[0].title' | tr '[:upper:]' '[:lower:]' | sed 's/[^a-z0-9]/-/g' | sed 's/--*/-/g' | sed 's/^-//;s/-$//' | head -c 50)
RESULTS_DIR="$REPO_ROOT/test-results/PR-${PR_NUMBER}-${PR_TITLE}"
mkdir -p $RESULTS_DIR

Test user credentials (for logging into the UI or verifying results manually):

• Email: [e-mail]
• Password: testtest123

Step 1: Understand the PR

Before testing, understand what changed:

cd $WORKTREE_PATH

# Read PR description to understand the WHY
gh pr view {N} --json body --jq '.body'

git log --oneline dev..HEAD | head -20
git diff dev --stat

Read the PR description (Why / What / How) and changed files to understand: 0. Why does this PR exist? What problem does it solve?

1. What feature/fix does this PR implement?
2. How does it work? What's the approach?
3. What components are affected? (backend, frontend, copilot, executor, etc.)
4. What are the key user-facing behaviors to test?

Step 2: Write test scenarios

Based on the PR analysis, write a test plan to $RESULTS_DIR/test-plan.md:

# Test Plan: PR #{N} — {title}

## Scenarios
1. [Scenario name] — [what to verify]
2. ...

## API Tests (if applicable)
1. [Endpoint] — [expected behavior]
   - Before state: [what to check before]
   - After state: [what to verify changed]

## UI Tests (if applicable)
1. [Page/component] — [interaction to test]
   - Screenshot before: [what to capture]
   - Screenshot after: [what to capture]

## Negative Tests (REQUIRED — at least one per feature)
1. [What should NOT happen] — [how to trigger it]
   - Expected error: [what error message/code]
   - State unchanged: [what to verify did NOT change]

Be critical — include edge cases, error paths, and security checks. Every scenario MUST specify what screenshots to take and what state to verify.

Step 3: Environment setup

3a. Copy .env files from the root worktree

The root worktree ($REPO_ROOT) has the canonical .env files with all API keys. Copy them to the target worktree:

# CRITICAL: .env files are NOT checked into git. They must be copied manually.
cp $REPO_ROOT/autogpt_platform/.env $PLATFORM_DIR/.env
cp $REPO_ROOT/autogpt_platform/backend/.env $BACKEND_DIR/.env
cp $REPO_ROOT/autogpt_platform/frontend/.env $FRONTEND_DIR/.env

3b. Configure copilot authentication

The copilot needs an LLM API to function. Two approaches (try subscription first):

Option 1: Subscription mode (preferred — uses your Claude Max/Pro subscription)

The claude_agent_sdk Python package bundles its own Claude CLI binary — no need to install @anthropic-ai/claude-code via npm. The backend auto-provisions credentials from environment variables on startup.

Run the helper script to extract tokens from your host and auto-update backend/.env (works on macOS, Linux, and Windows/WSL):

# Extracts OAuth tokens and writes CLAUDE_CODE_OAUTH_TOKEN + CLAUDE_CODE_REFRESH_TOKEN into .env
bash $BACKEND_DIR/scripts/refresh_claude_token.sh --env-file $BACKEND_DIR/.env

How it works: The script reads the OAuth token from:

• macOS: system keychain ("Claude Code-credentials")
• Linux/WSL: ~/.claude/.credentials.json
• Windows: %APPDATA%/claude/.credentials.json

It sets CLAUDE_CODE_OAUTH_TOKEN, CLAUDE_CODE_REFRESH_TOKEN, and CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true in the .env file. On container startup, the backend auto-provisions ~/.claude/.credentials.json inside the container from these env vars. The SDK's bundled CLI then authenticates using that file. No claude login, no npm install needed.

Note: The OAuth token expires (~24h). If copilot returns auth errors, re-run the script and restart: $BACKEND_DIR/scripts/refresh_claude_token.sh --env-file $BACKEND_DIR/.env && docker compose up -d copilot_executor

Option 2: OpenRouter API key mode (fallback)

If subscription mode doesn't work, switch to API key mode using OpenRouter:

# In $BACKEND_DIR/.env, ensure these are set:
CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=false
CHAT_API_KEY=<value of OPEN_ROUTER_API_KEY from the same .env>
CHAT_BASE_URL=https://openrouter.ai/api/v1
CHAT_USE_CLAUDE_AGENT_SDK=true

Use sed to update these values:

ORKEY=$(grep "^OPEN_ROUTER_API_KEY=" $BACKEND_DIR/.env | cut -d= -f2)
[ -n "$ORKEY" ] || { echo "ERROR: OPEN_ROUTER_API_KEY is missing in $BACKEND_DIR/.env"; exit 1; }
perl -i -pe 's/CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true/CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=false/' $BACKEND_DIR/.env
# Add or update CHAT_API_KEY and CHAT_BASE_URL
grep -q "^CHAT_API_KEY=" $BACKEND_DIR/.env && perl -i -pe "s|^CHAT_API_KEY=.*|CHAT_API_KEY=$ORKEY|" $BACKEND_DIR/.env || echo "CHAT_API_KEY=$ORKEY" >> $BACKEND_DIR/.env
grep -q "^CHAT_BASE_URL=" $BACKEND_DIR/.env && perl -i -pe 's|^CHAT_BASE_URL=.*|CHAT_BASE_URL=https://openrouter.ai/api/v1|' $BACKEND_DIR/.env || echo "CHAT_BASE_URL=https://openrouter.ai/api/v1" >> $BACKEND_DIR/.env

3c. Stop conflicting containers

# Stop any running app containers (keep infra: supabase, redis, rabbitmq, clamav)
docker ps --format "{{.Names}}" | grep -E "rest_server|executor|copilot|websocket|database_manager|scheduler|notification|frontend|migrate" | while read name; do
  docker stop "$name" 2>/dev/null
done

3e. Build and start

cd $PLATFORM_DIR && docker compose build --no-cache 2>&1 | tail -20
if [ ${PIPESTATUS[0]} -ne 0 ]; then echo "ERROR: Docker build failed"; exit 1; fi

cd $PLATFORM_DIR && docker compose up -d 2>&1 | tail -20
if [ ${PIPESTATUS[0]} -ne 0 ]; then echo "ERROR: Docker compose up failed"; exit 1; fi

Note: If the container appears to be running old code (e.g. missing PR changes), use docker compose build --no-cache to force a full rebuild. Docker BuildKit may sometimes reuse cached COPY layers from a previous build on a different branch.

Expected time: 3-8 minutes for build, 5-10 minutes with --no-cache.

3f. Wait for services to be ready

# Poll until backend and frontend respond
for i in $(seq 1 60); do
  BACKEND=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:8006/docs 2>/dev/null)
  FRONTEND=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:3000 2>/dev/null)
  if [ "$BACKEND" = "200" ] && [ "$FRONTEND" = "200" ]; then
    echo "Services ready"
    break
  fi
  sleep 5
done

3h. Create test user and get auth token

ANON_KEY=$(grep "NEXT_PUBLIC_SUPABASE_ANON_KEY=" $FRONTEND_DIR/.env | sed 's/.*NEXT_PUBLIC_SUPABASE_ANON_KEY=//' | tr -d '[:space:]')

# Signup (idempotent — returns "User already registered" if exists)
RESULT=$(curl -s -X POST 'http://localhost:8000/auth/v1/signup' \
  -H "apikey: $ANON_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"email":"[e-mail]","password":"testtest123"}')

# If "Database error finding user", restart supabase-auth and retry
if echo "$RESULT" | grep -q "Database error"; then
  docker restart supabase-auth && sleep 5
  curl -s -X POST 'http://localhost:8000/auth/v1/signup' \
    -H "apikey: $ANON_KEY" \
    -H 'Content-Type: application/json' \
    -d '{"email":"[e-mail]","password":"testtest123"}'
fi

# Get auth token
TOKEN=$(curl -s -X POST 'http://localhost:8000/auth/v1/token?grant_type=password' \
  -H "apikey: $ANON_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"email":"[e-mail]","password":"testtest123"}' | jq -r '.access_token // ""')

Use this token for ALL API calls:

curl -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/...

3i. Disable onboarding for test user

The frontend redirects to /onboarding when the VISIT_COPILOT step is not in completedSteps. Mark it complete via the backend API so every browser test lands on the real feature UI:

ONBOARDING_RESULT=$(curl -s --max-time 30 -X POST \
  "http://localhost:8006/api/onboarding/step?step=VISIT_COPILOT" \
  -H "Authorization: Bearer $TOKEN")
echo "Onboarding bypass: $ONBOARDING_RESULT"

# Verify it took effect
ONBOARDING_STATUS=$(curl -s --max-time 30 \
  "http://localhost:8006/api/onboarding/completed" \
  -H "Authorization: Bearer $TOKEN" | jq -r '.is_completed')
echo "Onboarding completed: $ONBOARDING_STATUS"
if [ "$ONBOARDING_STATUS" != "true" ]; then
  echo "ERROR: onboarding bypass failed — browser tests will hit /onboarding instead of the target feature. Investigate before proceeding."
  exit 1
fi

Step 4: Run tests

Service ports reference

Service	Port	URL
Frontend	3000	http://localhost:3000
Backend REST	8006	http://localhost:8006
Supabase Auth (via Kong)	8000	http://localhost:8000
Executor	8002	http://localhost:8002
Copilot Executor	8008	http://localhost:8008
WebSocket	8001	http://localhost:8001
Database Manager	8005	http://localhost:8005
Redis	6379	localhost:6379
RabbitMQ	5672	localhost:5672

API testing

Use curl with the auth token for backend API tests. For EVERY API call that changes state, record before/after values:

# Example: List agents
curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/graphs | jq . | head -20

# Example: Create an agent
curl -s -X POST http://localhost:8006/api/graphs \
  -H "Authorization: Bearer $TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{...}' | jq .

# Example: Run an agent
curl -s -X POST "http://localhost:8006/api/graphs/{graph_id}/execute" \
  -H "Authorization: Bearer $TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"data": {...}}'

# Example: Get execution results
curl -s -H "Authorization: Bearer $TOKEN" \
  "http://localhost:8006/api/graphs/{graph_id}/executions/{exec_id}" | jq .

State verification pattern (use for EVERY state-changing API call):

# 1. Record BEFORE state
BEFORE_STATE=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/{resource} | jq '{relevant_fields}')
echo "BEFORE: $BEFORE_STATE"

# 2. Perform the action
ACTION_RESULT=$(curl -s -X POST ... | jq .)
echo "ACTION RESULT: $ACTION_RESULT"

# 3. Record AFTER state
AFTER_STATE=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/{resource} | jq '{relevant_fields}')
echo "AFTER: $AFTER_STATE"

# 4. Log the comparison
echo "=== STATE CHANGE VERIFICATION ==="
echo "Before: $BEFORE_STATE"
echo "After: $AFTER_STATE"
echo "Expected change: {describe what should have changed}"

Browser testing with agent-browser

# Close any existing session
agent-browser close 2>/dev/null || true

# Use --session-name to persist cookies across navigations
# This means login only needs to happen once per test session
agent-browser --session-name pr-test open 'http://localhost:3000/login' --timeout 15000

# Get interactive elements
agent-browser --session-name pr-test snapshot | grep "textbox\|button"

# Login
agent-browser --session-name pr-test fill {email_ref} "[e-mail]"
agent-browser --session-name pr-test fill {password_ref} "testtest123"
agent-browser --session-name pr-test click {login_button_ref}
sleep 5

# Dismiss cookie banner if present
agent-browser --session-name pr-test click 'text=Accept All' 2>/dev/null || true

# Navigate — cookies are preserved so login persists
agent-browser --session-name pr-test open 'http://localhost:3000/copilot' --timeout 10000

# Take screenshot
agent-browser --session-name pr-test screenshot $RESULTS_DIR/01-page.png

# Interact with elements
agent-browser --session-name pr-test fill {ref} "text"
agent-browser --session-name pr-test press "Enter"
agent-browser --session-name pr-test click {ref}
agent-browser --session-name pr-test click 'text=Button Text'

# Read page content
agent-browser --session-name pr-test snapshot | grep "text:"

Key pages:

• /copilot — CoPilot chat (for testing copilot features)
• /build — Agent builder (for testing block/node features)
• /build?flowID={id} — Specific agent in builder
• /library — Agent library (for testing listing/import features)
• /library/agents/{id} — Agent detail with run history
• /marketplace — Marketplace

Checking logs

# Backend REST server
docker logs autogpt_platform-rest_server-1 2>&1 | tail -30

# Executor (runs agent graphs)
docker logs autogpt_platform-executor-1 2>&1 | tail -30

# Copilot executor (runs copilot chat sessions)
docker logs autogpt_platform-copilot_executor-1 2>&1 | tail -30

# Frontend
docker logs autogpt_platform-frontend-1 2>&1 | tail -30

# Filter for errors
docker logs autogpt_platform-executor-1 2>&1 | grep -i "error\|exception\|traceback" | tail -20

Copilot chat testing

The copilot uses SSE streaming. To test via API:

# Create a session
SESSION_ID=$(curl -s -X POST 'http://localhost:8006/api/chat/sessions' \
  -H "Authorization: Bearer $TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{}' | jq -r '.id // .session_id // ""')

# Stream a message (SSE - will stream chunks)
curl -N -X POST "http://localhost:8006/api/chat/sessions/$SESSION_ID/stream" \
  -H "Authorization: Bearer $TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"message": "Hello, what can you help me with?"}' \
  --max-time 60 2>/dev/null | head -50

Or test via browser (preferred for UI verification):

agent-browser --session-name pr-test open 'http://localhost:3000/copilot' --timeout 10000
# ... fill chat input and press Enter, wait 20-30s for response

Step 5: Record results and take screenshots

Take a screenshot at EVERY significant test step — before and after interactions, on success, and on failure. This is NON-NEGOTIABLE.

Required screenshot pattern for each test scenario:

# BEFORE the action
agent-browser --session-name pr-test screenshot $RESULTS_DIR/{NN}-{scenario}-before.png

# Perform the action...

# AFTER the action
agent-browser --session-name pr-test screenshot $RESULTS_DIR/{NN}-{scenario}-after.png

Naming convention:

# Examples:
# $RESULTS_DIR/01-login-page-before.png
# $RESULTS_DIR/02-login-page-after.png
# $RESULTS_DIR/03-credits-page-before.png
# $RESULTS_DIR/04-credits-purchase-after.png
# $RESULTS_DIR/05-negative-insufficient-credits.png
# $RESULTS_DIR/06-error-state.png

Minimum requirements:

• At least TWO screenshots per test scenario (before + after)
• At least ONE screenshot for each negative test case showing the error state
• If a test fails, screenshot the failure state AND any error logs visible in the UI

Step 6: Show results to user with screenshots

CRITICAL: After all tests complete, you MUST show every screenshot to the user using the Read tool, with an explanation of what each screenshot shows. This is the most important part of the test report — the user needs to visually verify the results.

For each screenshot:

1. Use the Read tool to display the PNG file (Claude can read images)
2. Write a 1-2 sentence explanation below it describing:
   • What page/state is being shown
   • What the screenshot proves (which test scenario it validates)
   • Any notable details visible in the UI

Format the output like this:

### Screenshot 1: {descriptive title}
[Read the PNG file here]

**What it shows:** {1-2 sentence explanation of what this screenshot proves}

---

After showing all screenshots, output a detailed summary table:

#	Scenario	Result	API Evidence	Screenshot Evidence
1	{name}	PASS/FAIL	Before: X, After: Y	01-before.png, 02-after.png
2	...	...	...	...

IMPORTANT: As you show each screenshot and record test results, persist them in shell variables for Step 7:

# Build these variables during Step 6 — they are required by Step 7's script
# NOTE: declare -A requires Bash 4.0+. This is standard on modern systems (macOS ships zsh
# but Homebrew bash is 5.x; Linux typically has bash 5.x). If running on Bash <4, use a
# plain variable with a lookup function instead.
declare -A SCREENSHOT_EXPLANATIONS=(
  ["01-login-page.png"]="Shows the login page loaded successfully with SSO options visible."
  ["02-builder-with-block.png"]="The builder canvas displays the newly added block connected to the trigger."
  # ... one entry per screenshot, using the same explanations you showed the user above
)

TEST_RESULTS_TABLE="| 1 | Login flow | PASS | N/A | 01-login-before.png, 02-login-after.png |
| 2 | Credits purchase | PASS | Before: 100, After: 95 | 03-credits-before.png, 04-credits-after.png |
| 3 | Insufficient credits (negative) | PASS | Credits: 0, rejected | 05-insufficient-credits-error.png |"
# ... one row per test scenario with actual results

Step 7: Post test report as PR comment with screenshots

Upload screenshots to the PR using the GitHub Git API (no local git operations — safe for worktrees), then post a comment with inline images and per-screenshot explanations.

This step is MANDATORY. Every test run MUST post a PR comment with screenshots. No exceptions.

CRITICAL — NEVER post a bare directory link like https://github.com/.../tree/.... Every screenshot MUST appear as ![name](raw_url) inline in the PR comment so reviewers can see them without clicking any links. After posting, the verification step below greps the comment for ![ tags and exits 1 if none are found — the test run is considered incomplete until this passes.

# Upload screenshots via GitHub Git API (creates blobs, tree, commit, and ref remotely)
REPO="Significant-Gravitas/AutoGPT"
SCREENSHOTS_BRANCH="test-screenshots/pr-${PR_NUMBER}"
SCREENSHOTS_DIR="test-screenshots/PR-${PR_NUMBER}"

# Step 1: Create blobs for each screenshot and build tree JSON
# Retry each blob upload up to 3 times. If still failing, list them at end of report.
shopt -s nullglob
SCREENSHOT_FILES=("$RESULTS_DIR"/*.png)
if [ ${#SCREENSHOT_FILES[@]} -eq 0 ]; then
  echo "ERROR: No screenshots found in $RESULTS_DIR. Test run is incomplete."
  exit 1
fi
TREE_JSON='['
FIRST=true
FAILED_UPLOADS=()
for img in "${SCREENSHOT_FILES[@]}"; do
  BASENAME=$(basename "$img")
  B64=$(base64 < "$img")
  BLOB_SHA=""
  for attempt in 1 2 3; do
    BLOB_SHA=$(gh api "repos/${REPO}/git/blobs" -f content="$B64" -f encoding="base64" --jq '.sha' 2>/dev/null || true)
    [ -n "$BLOB_SHA" ] && break
    sleep 1
  done
  if [ -z "$BLOB_SHA" ]; then
    FAILED_UPLOADS+=("$img")
    continue
  fi
  if [ "$FIRST" = true ]; then FIRST=false; else TREE_JSON+=','; fi
  TREE_JSON+="{\"path\":\"${SCREENSHOTS_DIR}/${BASENAME}\",\"mode\":\"100644\",\"type\":\"blob\",\"sha\":\"${BLOB_SHA}\"}"
done
TREE_JSON+=']'

# Step 2: Create tree, commit, and branch ref
TREE_SHA=$(echo "$TREE_JSON" | jq -c '{tree: .}' | gh api "repos/${REPO}/git/trees" --input - --jq '.sha')

# Resolve parent commit so screenshots are chained, not orphan root commits
PARENT_SHA=$(gh api "repos/${REPO}/git/refs/heads/${SCREENSHOTS_BRANCH}" --jq '.object.sha' 2>/dev/null || echo "")
if [ -n "$PARENT_SHA" ]; then
  COMMIT_SHA=$(gh api "repos/${REPO}/git/commits" \
    -f message="test: add E2E test screenshots for PR #${PR_NUMBER}" \
    -f tree="$TREE_SHA" \
    -f "parents[]=$PARENT_SHA" \
    --jq '.sha')
else
  COMMIT_SHA=$(gh api "repos/${REPO}/git/commits" \
    -f message="test: add E2E test screenshots for PR #${PR_NUMBER}" \
    -f tree="$TREE_SHA" \
    --jq '.sha')
fi

gh api "repos/${REPO}/git/refs" \
  -f ref="refs/heads/${SCREENSHOTS_BRANCH}" \
  -f sha="$COMMIT_SHA" 2>/dev/null \
  || gh api "repos/${REPO}/git/refs/heads/${SCREENSHOTS_BRANCH}" \
    -X PATCH -f sha="$COMMIT_SHA" -F force=true

Then post the comment with inline images AND explanations for each screenshot:

REPO_URL="https://raw.githubusercontent.com/${REPO}/${SCREENSHOTS_BRANCH}"

# Build image markdown using uploaded image URLs; skip FAILED_UPLOADS (listed separately)

IMAGE_MARKDOWN=""
for img in "${SCREENSHOT_FILES[@]}"; do
  BASENAME=$(basename "$img")
  TITLE=$(echo "${BASENAME%.png}" | sed 's/^[0-9]*-//' | sed 's/-/ /g' | awk '{for(i=1;i<=NF;i++) $i=toupper(substr($i,1,1)) tolower(substr($i,2))}1')
  # Skip images that failed to upload — they will be listed at the end
  IS_FAILED=false
  for failed in "${FAILED_UPLOADS[@]}"; do
    [ "$(basename "$failed")" = "$BASENAME" ] && IS_FAILED=true && break
  done
  if [ "$IS_FAILED" = true ]; then
    continue
  fi
  EXPLANATION="${SCREENSHOT_EXPLANATIONS[$BASENAME]}"
  if [ -z "$EXPLANATION" ]; then
    echo "ERROR: Missing screenshot explanation for $BASENAME. Add it to SCREENSHOT_EXPLANATIONS in Step 6."
    exit 1
  fi
  IMAGE_MARKDOWN="${IMAGE_MARKDOWN}
### ${TITLE}
![${BASENAME}](${REPO_URL}/${SCREENSHOTS_DIR}/${BASENAME})
${EXPLANATION}
"
done

# Write comment body to file to avoid shell interpretation issues with special characters
COMMENT_FILE=$(mktemp)
# If any uploads failed, append a section listing them with instructions
FAILED_SECTION=""
if [ ${#FAILED_UPLOADS[@]} -gt 0 ]; then
  FAILED_SECTION="
## ⚠️ Failed Screenshot Uploads
The following screenshots could not be uploaded via the GitHub API after 3 retries.
**To add them:** drag-and-drop or paste these files into a PR comment manually:
"
  for failed in "${FAILED_UPLOADS[@]}"; do
    FAILED_SECTION="${FAILED_SECTION}
- \`$(basename "$failed")\` (local path: \`$failed\`)"
  done
  FAILED_SECTION="${FAILED_SECTION}

**Run status:** INCOMPLETE until the files above are manually attached and visible inline in the PR."
fi

cat > "$COMMENT_FILE" <<INNEREOF
## E2E Test Report

| # | Scenario | Result | API Evidence | Screenshot Evidence |
|---|----------|--------|-------------|-------------------|
${TEST_RESULTS_TABLE}

${IMAGE_MARKDOWN}
${FAILED_SECTION}
INNEREOF

gh api "repos/${REPO}/issues/$PR_NUMBER/comments" -F body=@"$COMMENT_FILE"
rm -f "$COMMENT_FILE"

# Verify the posted comment contains inline images — exit 1 if none found
# Use separate --paginate + jq pipe: --jq applies per-page, not to the full list
LAST_COMMENT=$(gh api "repos/${REPO}/issues/$PR_NUMBER/comments" --paginate 2>/dev/null | jq -r '.[-1].body // ""')
if ! echo "$LAST_COMMENT" | grep -q '!\['; then
  echo "ERROR: Posted comment contains no inline images (![). Bare directory links are not acceptable." >&2
  exit 1
fi
echo "✓ Inline images verified in posted comment"

The PR comment MUST include:

1. A summary table of all scenarios with PASS/FAIL and before/after API evidence
2. Every successfully uploaded screenshot rendered inline; any failed uploads listed with manual attachment instructions
3. A 1-2 sentence explanation below each screenshot describing what it proves

This approach uses the GitHub Git API to create blobs, trees, commits, and refs entirely server-side. No local git checkout or git push — safe for worktrees and won't interfere with the PR branch.

Step 8: Evaluate and post a formal PR review

After the test comment is posted, evaluate whether the run was thorough enough to make a merge decision, then post a formal GitHub review (approve or request changes). This step is mandatory — every test run MUST end with a formal review decision.

Evaluation criteria

Re-read the PR description:

gh pr view "$PR_NUMBER" --json body --jq '.body' --repo "$REPO"

Score the run against each criterion:

Criterion	Pass condition
Coverage	Every feature/change described in the PR has at least one test scenario
All scenarios pass	No FAIL rows in the results table
Negative tests	At least one failure-path test per feature (invalid input, unauthorized, edge case)
Before/after evidence	Every state-changing API call has before/after values logged
Screenshots are meaningful	Screenshots show the actual state change, not just a loading spinner or blank page
No regressions	Existing core flows (login, agent create/run) still work

Decision logic

ALL criteria pass                            → APPROVE
Any scenario FAIL or missing PR feature      → REQUEST_CHANGES (list gaps)
Evidence weak (no before/after, vague shots) → REQUEST_CHANGES (list what's missing)

Post the review

REVIEW_FILE=$(mktemp)

# Count results
PASS_COUNT=$(echo "$TEST_RESULTS_TABLE" | grep -c "PASS" || true)
FAIL_COUNT=$(echo "$TEST_RESULTS_TABLE" | grep -c "FAIL" || true)
TOTAL=$(( PASS_COUNT + FAIL_COUNT ))

# List any coverage gaps found during evaluation (populate this array as you assess)
# e.g. COVERAGE_GAPS=("PR claims to add X but no test covers it")
COVERAGE_GAPS=()

If APPROVING — all criteria met, zero failures, full coverage:

cat > "$REVIEW_FILE" <<REVIEWEOF
## E2E Test Evaluation — APPROVED

**Results:** ${PASS_COUNT}/${TOTAL} scenarios passed.

**Coverage:** All features described in the PR were exercised.

**Evidence:** Before/after API values logged for all state-changing operations; screenshots show meaningful state transitions.

**Negative tests:** Failure paths tested for each feature.

No regressions observed on core flows.
REVIEWEOF

gh pr review "$PR_NUMBER" --repo "$REPO" --approve --body "$(cat "$REVIEW_FILE")"
echo "✅ PR approved"

If REQUESTING CHANGES — any failure, coverage gap, or missing evidence:

FAIL_LIST=$(echo "$TEST_RESULTS_TABLE" | grep "FAIL" | awk -F'|' '{print "- Scenario" $2 "failed"}' || true)

cat > "$REVIEW_FILE" <<REVIEWEOF
## E2E Test Evaluation — Changes Requested

**Results:** ${PASS_COUNT}/${TOTAL} scenarios passed, ${FAIL_COUNT} failed.

### Required before merge

${FAIL_LIST}
$(for gap in "${COVERAGE_GAPS[@]}"; do echo "- $gap"; done)

Please fix the above and re-run the E2E tests.
REVIEWEOF

gh pr review "$PR_NUMBER" --repo "$REPO" --request-changes --body "$(cat "$REVIEW_FILE")"
echo "❌ Changes requested"

rm -f "$REVIEW_FILE"

Rules:

• In --fix mode, fix all failures before posting the review — the review reflects the final state after fixes
• Never approve if any scenario failed, even if it seems like a flake — rerun that scenario first
• Never request changes for issues already fixed in this run

Fix mode (--fix flag)

When --fix is present, the standard is HIGHER. Do not just note issues — FIX them immediately.

Fix protocol for EVERY issue found (including UX issues):

1. Identify the root cause in the code — read the relevant source files
2. Write a failing test first (TDD): For backend bugs, write a test marked with pytest.mark.xfail(reason="..."). For frontend/Playwright bugs, write a test with .fixme annotation. Run it to confirm it fails as expected.
3. Screenshot the broken state: agent-browser screenshot $RESULTS_DIR/{NN}-broken-{description}.png
4. Fix the code in the worktree
5. Rebuild ONLY the affected service (not the whole stack):

   cd $PLATFORM_DIR && docker compose up --build -d {service_name}
   # e.g., docker compose up --build -d rest_server
   # e.g., docker compose up --build -d frontend
   

6. Wait for the service to be ready (poll health endpoint)
7. Re-test the same scenario
8. Screenshot the fixed state: agent-browser screenshot $RESULTS_DIR/{NN}-fixed-{description}.png
9. Remove the xfail/fixme marker from the test written in step 2, and verify it passes
10. Verify the fix did not break other scenarios (run a quick smoke test)
11. Commit and push immediately:

cd $WORKTREE_PATH
git add -A
git commit -m "fix: {description of fix}"
git push

12. Continue to the next test scenario

Fix loop (like pr-address)

test scenario → find issue (bug OR UX problem) → screenshot broken state
→ fix code → rebuild affected service only → re-test → screenshot fixed state
→ verify no regressions → commit + push
→ repeat for next scenario
→ after ALL scenarios pass, run full re-test to verify everything together

Key differences from non-fix mode:

• UX issues count as bugs — fix them (bad alignment, confusing labels, missing loading states)
• Every fix MUST have a before/after screenshot pair proving it works
• Commit after EACH fix, not in a batch at the end
• The final re-test must produce a clean set of all-passing screenshots

Known issues and workarounds

Problem: "Database error finding user" on signup

Cause: Supabase auth service schema cache is stale after migration. Fix: docker restart supabase-auth && sleep 5 then retry signup.

Problem: Copilot returns auth errors in subscription mode

Cause: CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true but CLAUDE_CODE_OAUTH_TOKEN is not set or expired. Fix: Re-extract the OAuth token from macOS keychain (see step 3b, Option 1) and recreate the container (docker compose up -d copilot_executor). The backend auto-provisions ~/.claude/.credentials.json from the env var on startup. No npm install or claude login needed — the SDK bundles its own CLI binary.

Problem: agent-browser can't find chromium

Cause: The Dockerfile auto-provisions system chromium on all architectures (including ARM64). If your branch is behind dev, this may not be present yet. Fix: Check if chromium exists: which chromium || which chromium-browser. If missing, install it: apt-get install -y chromium and set AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium in the container environment.

Problem: agent-browser selector matches multiple elements

Cause: text=X matches all elements containing that text. Fix: Use agent-browser snapshot to get specific ref=eNN references, then use those: agent-browser click eNN.

Problem: Frontend shows cookie banner blocking interaction

Fix: agent-browser click 'text=Accept All' before other interactions.

Problem: Container loses npm packages after rebuild

Cause: docker compose up --build rebuilds the image, losing runtime installs. Fix: Add packages to the Dockerfile instead of installing at runtime.

Problem: Services not starting after docker compose up

Fix: Wait and check health: docker compose ps. Common cause: migration hasn't finished. Check: docker logs autogpt_platform-migrate-1 2>&1 | tail -5. If supabase-db isn't healthy: docker restart supabase-db && sleep 10.

Problem: Docker uses cached layers with old code (PR changes not visible)

Cause: docker compose up --build reuses cached COPY layers from previous builds. If the PR branch changes Python files but the previous build already cached that layer from dev, the container runs dev code. Fix: Always use docker compose build --no-cache for the first build of a PR branch. Subsequent rebuilds within the same branch can use --build.

Problem: agent-browser open loses login session

Cause: Without session persistence, agent-browser open starts fresh. Fix: Use --session-name pr-test on ALL agent-browser commands. This auto-saves/restores cookies and localStorage across navigations. Alternatively, use agent-browser eval "window.location.href = '...'" to navigate within the same context.

Problem: Supabase auth returns "Database error querying schema"

Cause: The database schema changed (migration ran) but supabase-auth has a stale schema cache. Fix: docker restart supabase-db && sleep 10 && docker restart supabase-auth && sleep 8. If user data was lost, re-signup.