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Nexu E2e Test

OrganizationPopular
nexu-io
nexu-e2e-test

Use when verifying OpenClaw gateway fixes end-to-end, testing skill loading after restart, or running integration tests against the local Nexu+OpenClaw stack. Triggers on "e2e test", "verify fix", "test gateway", "test skills loading".

Overview

Publishernexu-io
Repositorynexu
Skill namenexu-e2e-test
Stars
3.3K
Forks
263
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nexu-io on GitHub. Read the source before you install it.

Installation

Install the Nexu E2e Test AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nexu-io/nexu.git /tmp/nexu
mkdir -p .claude/skills
cp -r /tmp/nexu/skills/localdev/nexu-e2e-test .claude/skills/nexu-e2e-test
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nexu E2e Test in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Nexu E2e Test on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Nexu E2e Test is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

ApproachBlockerStatus
HTTP POST /v1/chat/completionsEndpoint exists (openai-http.ts) but uses agentCommand() — same embedded agent path as CLI, bypasses session storeWorks for smoke tests (same as CLI)
HTTP POST /v1/responsesEndpoint exists (openresponses-http.ts) but also uses agentCommand()Works for smoke tests (same as CLI)
WebSocket chat.sendRequires device pairing for operator.write scope — clearUnboundScopes() in message-handler.ts:483-488 clears all self-declared scopes without device identityDead end without device keys
openclaw agent --session-idUses embedded agent path (sessionKey=unknown), bypasses session store cacheWorks for smoke tests, NOT for session-store bugs
Direct module import from distRollup bundles with hashed filenames, can't import individual modulesDead end
tsx from /tmpModule resolution fails for imports outside project rootDead end
Vitest in-project .test.tsFull module resolution, mocking, TypeScript supportPrimary method

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.

bash
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:

bash
# 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):

bash
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):

bash
| 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:

bash
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

bash
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)

bash
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):

DetailValue
Frame format{"type": "req", "id": "<uuid>", "method": "...", "params": {...}} (NOT JSON-RPC)
Protocol version3 (as of 2026.2.25)
Valid client IDsgateway-client, cli, webchat-ui, openclaw-control-ui, node-host, test, webchat, fingerprint, openclaw-probe, openclaw-macos, openclaw-ios, openclaw-android (defined in protocol/client-info.ts)
Valid client modeswebchat, cli, ui, backend, node, probe, test
Auth flowChallenge → connect RPC with nonce → needs device identity for write scopes
Scope for chat.sendoperator.write — requires device pairing, token-only auth gets zero scopes
Scope exceptioncontrolUiAuthPolicy.allowBypass: true preserves scopes without device identity (dev/control-UI only, see message-handler.ts:489-542)

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

Frequently asked questions

What does the Nexu E2e Test AI skill do?

Use when verifying OpenClaw gateway fixes end-to-end, testing skill loading after restart, or running integration tests against the local Nexu+OpenClaw stack. Triggers on "e2e test", "verify fix", "test gateway", "test skills loading".

Why use Nexu E2e Test on TypingMind?

Because you install it once and use it with any model. Nexu E2e Test is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Nexu E2e Test in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nexu-io/nexu/tree/main/skills/localdev/nexu-e2e-test. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Nexu E2e Test?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Nexu E2e Test?

As many as you like. As long as a model supports skills, you can use Nexu E2e Test with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Nexu E2e Test AI skill free?

Yes. It is published on GitHub by nexu-io under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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