Nexu E2E Testing — OpenClaw Gateway

Run end-to-end verification of the Nexu → OpenClaw gateway stack locally.

Known Constraints

The OpenClaw gateway has architectural constraints that block naive E2E approaches. Read this before attempting any gateway testing.

Key insight: All HTTP and CLI approaches use the embedded agent path via agentCommand() (imported from commands/agent.js). Only messages arriving through connected channels (Slack/Discord) go through dispatchInboundMessage() → auto-reply pipeline → ensureSkillSnapshot(), which is the code path that uses the session store.

Viable Test Methods

1. Vitest Unit/Integration Tests (Primary)

Write .test.ts files inside the OpenClaw worktree and run with vitest. This is the only reliable way to test internal functions like ensureSkillsWatcher, getSkillsSnapshotVersion, ensureSkillSnapshot.

cd <OPENCLAW_WORKTREE>
OPENCLAW_TEST_FAST=1 npx vitest run src/agents/skills/refresh.test.ts

Key patterns:

• Mock chokidar with vi.mock("chokidar", ...)
• Use await import("./refresh.js") for dynamic imports after mocking
• Use unique workspace paths per test (/tmp/test-<name>-${Date.now()})
• OPENCLAW_TEST_FAST=1 skips filesystem scanning in session-updates

2. openclaw agent CLI or HTTP Smoke Tests

For "do skills load after restart" verification. Does NOT test session-store caching logic (all use embedded agent path).

CLI approach:

# Prerequisites: gateway must be running with a valid workspace
OPENCLAW_STATE_DIR=~/.openclaw \
OPENCLAW_CONFIG_PATH=<config-with-local-workspace> \
openclaw agent --session-id "<session>" --message "<msg>" --json --timeout 60

HTTP approach (OpenAI-compatible):

curl -s http://localhost:18789/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <gw-token>" \
  -d '{"model":"default","messages":[{"role":"user","content":"list your skills"}]}'

Parse results (CLI JSON output):

| python3 -c "
import json,sys
d=json.load(sys.stdin)
entries=d.get('result',{}).get('meta',{}).get('systemPromptReport',{}).get('skills',{}).get('entries',[])
managed=[e['name'] for e in entries if e['name'] in ('static-deploy','test-greeting')]
print(f'Skills: {len(entries)}, Managed: {managed}')
"

3. Connected Channel (Slack/Discord)

The only way to test the full auto-reply pipeline with session-store caching. Requires a running channel with active bot.

Gateway Setup for Testing

Config Pitfall: /data/ workspace path

Production configs have "workspace": "/data/openclaw/workspaces/..." which doesn't exist locally. Create a test config:

cat ~/.openclaw/openclaw.json | python3 -c "
import json, sys
cfg = json.load(sys.stdin)
cfg['agents']['list'][0]['workspace'] = '/tmp/openclaw-test-workspace'
json.dump(cfg, sys.stdout, indent=2)
" > /tmp/openclaw-test-config.json

Start gateway with test config

OPENCLAW_STATE_DIR=~/.openclaw \
OPENCLAW_CONFIG_PATH=/tmp/openclaw-test-config.json \
openclaw gateway run --allow-unconfigured --bind loopback --port 18789 --force --verbose

Wait for port readiness (not just process start)

for i in $(seq 1 15); do
  lsof -i :18789 -P 2>/dev/null | grep -q LISTEN && break
  sleep 1
done

WebSocket Protocol Reference

If you ever need to attempt WS testing (e.g., after implementing device pairing):

Restart Verification Checklist

When verifying a fix that involves skills/sessions after gateway restart:

1. Build the fix: cd <worktree> && pnpm build
2. Link globally: cd <worktree> && pnpm link --global
3. Verify version: openclaw --version
4. Write unit tests in the worktree for core logic (vitest)
5. Run smoke test: gateway restart → openclaw agent → check skill count
6. Check sessions.json at ~/.openclaw/agents/<agent>/sessions/sessions.json for snapshot versions
7. Check logs at gateway stdout for skill watcher events

Session Store Locations

~/.openclaw/agents/<agent-id>/sessions/sessions.json   # Session entries with skillsSnapshot
~/.openclaw/agents/<agent-id>/sessions/<session-id>.jsonl  # Session transcript

Key fields in session entry:

• skillsSnapshot.version — timestamp, should be non-zero after fix
• skillsSnapshot.skills[] — array of loaded skill names and locations
• skillsSnapshot.prompt — the <available_skills> XML injected into system prompt