Beam

OrganizationPopular

openclaw

beam

Publish a redacted local coding session to an authenticated read-only Beam catalog.

Overview

Publisher	openclaw
Repository	`agent-skills`
Skill name	`beam`
Stars	1.1K
Forks	109
Bundled files	6
License	MIT
Links	Skill source Repository

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.
6 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 Beam AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/openclaw/agent-skills/tree/main/skills/beam
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.

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/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/beam .claude/skills/beam

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Beam 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 Beam 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 Beam 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.

Beam

Use when the user explicitly asks to beam, publish, or share the current local coding session with an authenticated OpenClaw receiver.

Contract

Treat invoking this skill as approval for one snapshot upload to the named destination.
Never upload raw JSONL, reasoning, system/developer prompts, tool output, environment values, credentials, browser state, cookies, or local paths.
The helper is self-contained: it resolves and parses exact Claude Code or Codex transcripts, then uploads only locally redacted user/assistant messages and compact tool counts.
Beam is a read-only projection. Do not connect a node, expose a terminal, resume the local harness remotely, or grant the receiver filesystem/tool access.
Require HTTPS except for loopback development endpoints.
Authenticate with BEAM_ACCESS_TOKEN, BEAM_AUTH_TOKEN, or an interactive cloudflared access login. Never print those values.
Live synchronization is opt-in persistent behavior. Do not install hooks unless the user explicitly asks for live Beam updates.

Snapshot

Set or obtain the destination receiver URL first:

bash
export BEAM_ENDPOINT="https://example.internal/api/v1/beam/sessions"

Prefer the harness-specific exact identifier. Resolve the directory containing this SKILL.md as BEAM_SKILL_DIR first.

Claude Code exposes the current session id:

bash
node "$BEAM_SKILL_DIR/scripts/beam" publish \
  --endpoint "$BEAM_ENDPOINT" \
  --session-id "${CLAUDE_SESSION_ID}"

In Codex, resolve the directory containing this SKILL.md as BEAM_SKILL_DIR; normal shell-tool children expose the current thread id:

bash
node "$BEAM_SKILL_DIR/scripts/beam" publish \
  --endpoint "$BEAM_ENDPOINT" \
  --thread-id "$CODEX_THREAD_ID"

Prefer exact harness metadata when available:

Claude Code: ${CLAUDE_SESSION_ID} identifies the current local conversation; the helper finds its transcript.
Codex shell tools: CODEX_THREAD_ID identifies the current thread.
Hook adapters: pass their JSON to beam hook; transcript_path is authoritative.
Exact fallback: Beam scans only the native Claude/Codex session roots for the supplied id and fails closed on no match or ambiguity.

Useful options:

bash
node "$BEAM_SKILL_DIR/scripts/beam" publish --endpoint "$BEAM_ENDPOINT" --session /path/to/session.jsonl
node "$BEAM_SKILL_DIR/scripts/beam" publish --endpoint "$BEAM_ENDPOINT" --thread-id "$CODEX_THREAD_ID"
node "$BEAM_SKILL_DIR/scripts/beam" publish --endpoint "$BEAM_ENDPOINT" --title "Fix upload flow"
node "$BEAM_SKILL_DIR/scripts/beam" publish --endpoint "$BEAM_ENDPOINT" --complete
node "$BEAM_SKILL_DIR/scripts/beam" publish --endpoint "$BEAM_ENDPOINT" --dry-run

--dry-run prints the sanitized payload locally and performs no network request.

On success, return only the Beam URL and a short disclosure summary: source harness, shared message count, whether older entries were truncated, and whether the beam is complete. The URL uses the endpoint-derived Control UI base path followed by /beam/<title-slug>-<id-prefix>, for example https://gateway.example.com/beam/fix-upload-flow-0123456789ab. The title comes from --title or the first shared user message. The stable ID suffix identifies the session; links with an earlier title remain valid.

The helper also accepts bare /beam/<id-prefix> links and, during rollout, the current server's exact /chat/<agent>?catalog=beam&host=gateway&thread=<full-beam-id> response. It still rejects the obsolete ?session=catalog:... beta form.

Live Hooks

The helper accepts the snake_case JSON emitted by both Claude Code and Codex lifecycle hooks:

bash
node "$BEAM_SKILL_DIR/scripts/beam" hook --endpoint "$BEAM_ENDPOINT" --quiet

Configure root Stop hooks for turn-by-turn updates. Claude Code can also use SessionEnd for finalization; Codex finalization uses an explicit publish --complete. See:

references/claude-code-hooks.json
references/codex-hooks.toml

Hook failures must not block the coding session. Keep them quiet on success; log one concise redacted error on failure.

Full installation, authentication, data-boundary, and hook documentation: README.md.

Development

bash
node --check skills/beam/scripts/beam
node --check skills/beam/scripts/beam-session.js
node --test skills/beam/scripts/beam.test.mjs
scripts/validate-skills

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 Beam AI skill do?

Publish a redacted local coding session to an authenticated read-only Beam catalog.

Why use Beam on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openclaw/agent-skills/tree/main/skills/beam. 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 Beam?

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 Beam?

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

Is the Beam AI skill free?

Yes. It is published on GitHub by openclaw 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Beam

Contract

Snapshot

Live Hooks

Development

Bundled files

Frequently asked questions

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