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Slack E2e

OrganizationPopular
openclaw
slack-e2e

Test Slack with Convex-leased user OAuth or QA bots; check credentials, exercise owned messages, prove Gateway behavior, and distinguish API evidence from real Slack client interactions.

Overview

Publisheropenclaw
Repositoryopenclaw
Skill nameslack-e2e
Stars
391K
Forks
82.2K
Bundled files
4
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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by openclaw on GitHub. Read the source before you install it.

Installation

Install the Slack E2e 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.
    https://github.com/openclaw/openclaw/tree/main/.agents/skills/slack-e2e
  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/openclaw/openclaw.git /tmp/openclaw
mkdir -p .claude/skills
cp -r /tmp/openclaw/.agents/skills/slack-e2e .claude/skills/slack-e2e
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Slack E2e 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 Slack E2e 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 Slack E2e 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.

Slack agent E2E

Choose the proof

GoalEntry pointBoundary
Check shared user OAuthRead-only command belowUser/workspace identity and channel history; no Gateway
Exercise user-authored textSame command with --smokeCreate, read, edit, delete, verify absence; no Gateway reply claim
Prove OpenClaw ingress, replies, tools, files, or restartExisting QA Lab lane belowLeased driver/SUT bots and an isolated Gateway
Prove real clicks, slash commands, or renderingAuthorized Slack clientActual client observation, not reconstructed API data

Start from a source checkout with normal dependencies and an existing Convex login. If needed, ask the operator to run convex login or the cached bunx --no-install convex login. The broker provides the authorized pool; agents do not need to copy Slack tokens. Login alone cannot supply a missing pool credential or grant Slack permissions.

User OAuth: no QA Lab run

bash
node .agents/skills/slack-e2e/scripts/user-oauth-smoke.mjs
node .agents/skills/slack-e2e/scripts/user-oauth-smoke.mjs --smoke

The default is read-only in Slack; both modes acquire, heartbeat, and release a Convex lease. --smoke creates one synthetic, unmentioned top-level message, checks stored authorship, edits it, and deletes that exact message. Existing workspace listeners can still observe it. Each command uses a new private artifact directory and prints a safe result plus its path.

Read user OAuth setup and recovery for the pool payload, permissions, result interpretation, and failure handling. This skill-owned command reuses the existing lease helper; it changes no QA Lab code or release lane and starts no Gateway or model. It does not add a user-driver option to qa slack.

Existing Gateway lane

Use the source-checkout QA Lab owner for Gateway proof, not a separate bot runner. A run owns a leased driver/SUT pair, a temporary Gateway, native fixture receipts, and private artifacts. The driver has no Socket Mode connection: the SUT Gateway exclusively owns the app token and event delivery.

  1. Use the existing Convex login above. No Slack tokens, broker secrets, model credentials, app creation, or scope grants belong in the command line.

  2. Inspect the available scenarios and run readiness:

    bash
    pnpm openclaw qa slack --list-scenarios
    pnpm openclaw qa slack --doctor --output-dir .artifacts/qa-e2e/slack-doctor

    Doctor checks the actual lease: distinct bot identities in one workspace, both bots' channel access, the owned Gateway connection, and advertised OAuth scopes. Known missing scopes fail with their actor and exact names. Missing scope metadata means mutation capability is unverified, not granted. Missing optional file/reaction scopes do not block text-only flows; they block the affected native operations before dispatch. Doctor's full lifecycle capability verdict remains separate from mandatory connection readiness. A pool/login/permission failure is an owner prerequisite, not a reason to rotate credentials until one passes. Every subsequent run checks its own lease.

  3. Run the native lifecycle recipe:

    bash
    pnpm openclaw qa slack \
      --scenario-file qa/scenarios/channels/slack-e2e-lifecycle.yaml \
      --output-dir .artifacts/qa-e2e/slack-lifecycle

    --doctor and --scenario-file default to Convex, the CI role, and mock-openai. This is real Slack/Gateway transport with a deterministic model. Explicit overrides remain available; ordinary curated qa slack defaults do not change. Use a unique output directory per run. Additional --scenario-file arguments select additional complete YAML scenarios.

  4. Read the summary, evidence, and cleanup result before claiming success. Choose feature recipes for native operations or model-tool evidence, and runtime recipes for config/restart, custom flows, cancellation, artifacts, and recovery.

Evidence boundary

SurfaceWhat automation proves
Mention/quiet ingress, owned edits/deletes, reactions, upload, thread repliesFixture/API operations and explicit stored readback; not model tool calls
Correlated SUT replyA stored reply from the leased SUT after ingress; mock or live model must be named
Gateway debug-proxy captureSlack accepted a Gateway API write; neither Socket Mode event delivery nor rendering
Block Kit, file IDs, reaction stateStored structure/identity only
Human slash invocation, real button clicks, Agent View, visible rendering, human typingManual/Mantis client lane; bot/API evidence is insufficient

For visual or human-interaction requests, use an authorized, logged-in Slack client; the maintained Mantis workflow is in docs/concepts/qa-e2e-automation/operator-flow.md. Check which surface it actually captured: --approval-checkpoints renders API message data, not the Slack client. A Slack sign-in screenshot is not proof of a workspace action. Preserve inspected client screenshots alongside native evidence. Posting slash text through the API is not a slash invocation; Gateway approval RPCs are not button clicks. Do not infer typing from assistant status or start another Socket Mode recorder with the SUT app token.

Completion

Report scenario/model lane, stored native identities or safe counts, artifact paths, cleanup outcome, missing permissions, and any manual-only gap. Keep raw Gateway capture, channel IDs, messages, media, and lease material private; publish only sanitized proof. A successful API response with failed stored readback, an uncertain send, or failed cleanup is not an end-to-end pass.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Slack E2e AI skill do?

Test Slack with Convex-leased user OAuth or QA bots; check credentials, exercise owned messages, prove Gateway behavior, and distinguish API evidence from real Slack client interactions.

Why use Slack E2e on TypingMind?

Because you install it once and use it with any model. Slack E2e 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 Slack E2e in TypingMind?

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

Which AI models can use Slack E2e?

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 Slack E2e?

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

Is the Slack E2e AI skill free?

It is published on GitHub by openclaw. Check the repository for licensing terms. 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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