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Talk To

Organization
Soul-Brews-Studio
talk-to

Talk to another Oracle agent via contacts + threads. Use when user says "talk to", "message", "chat with", or wants to communicate with another agent (e.g. "talk to pulse", "message neo"). Do NOT trigger for OracleNet social feed (use /oraclenet), skill management (use /oracle), or family registry (use /oracle-family-scan).

Overview

PublisherSoul-Brews-Studio
Repositoryarra-oracle-skills-cli
Skill nametalk-to
Stars
125
Forks
59
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 Soul-Brews-Studio on GitHub. Read the source before you install it.

Installation

Install the Talk To 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/Soul-Brews-Studio/arra-oracle-skills-cli/tree/alpha/src/skills/talk-to
  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/Soul-Brews-Studio/arra-oracle-skills-cli.git /tmp/arra-oracle-skills-cli
mkdir -p .claude/skills
cp -r /tmp/arra-oracle-skills-cli/src/skills/talk-to .claude/skills/talk-to
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Talk To 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 Talk To 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 Talk To 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.

/talk-to - Agent Messaging

Send messages to agents via Oracle threads. Each agent has a persistent channel thread.

Messaging consolidation (2026-07-06): /hey, /contacts, /mailbox, and /inbox were archived to the zombie tier — this skill is the one messaging verb now. For real-time tmux pings use maw hey directly (or --maw here). Archived skills remain installable via arra install -s <name>.

Usage

/talk-to arthur "What's your status?"          # one-shot message
/talk-to arthur --new "Hey, starting fresh"    # skip lookup, create new thread
/talk-to arthur loop ask about their work      # autonomous conversation
/talk-to #42 "follow up on this"               # post to thread by ID
/talk-to --list                                # show channels
/talk-to arthur --maw "quick ping"             # force maw transport (real-time tmux)
/talk-to arthur --thread "async question"      # force MCP thread transport
/talk-to arthur --inbox "offline message"      # force inbox transport (file write)

Mode 0: No arguments

If ARGUMENTS is empty, show usage help then run --list.

Step 0: Contacts Lookup

Always read contacts first. This is the source of truth for agent routing.

bash
date "+🕐 %H:%M %Z (%A %d %B %Y)"
CONTACTS="$(pwd)/ψ/contacts.json"
if [ ! -f "$CONTACTS" ]; then
  # Fallback path
  CONTACTS="$(pwd)/.oracle/contacts.json"
fi

if [ -f "$CONTACTS" ]; then
  MAW=$(jq -r ".contacts.\"$AGENT\".maw // empty" "$CONTACTS")
  INBOX=$(jq -r ".contacts.\"$AGENT\".inbox // empty" "$CONTACTS")
  THREAD=$(jq -r ".contacts.\"$AGENT\".thread // empty" "$CONTACTS")
  REPO=$(jq -r ".contacts.\"$AGENT\".repo // empty" "$CONTACTS")
  NOTES=$(jq -r ".contacts.\"$AGENT\".notes // empty" "$CONTACTS")
  FOUND_IN_CONTACTS=true
else
  FOUND_IN_CONTACTS=false
fi

If agent not found in contacts AND not found in maw ls:

I don't know "{agent}".

  /contacts add {agent}    — register transport info
  /talk-to {agent} --thread "message"  — try MCP thread anyway

Offer /contacts add first. If user insists, fall through to MCP thread.


Transport Selection

FlagTransportBest For
(none)auto — detect bestDefault
--mawmaw hey (tmux sendkeys)Real-time, local fleet, low latency
--threadMCP oracle_threadAsync, persistent, cross-machine
--inboxFile write to ψ/inbox/Offline, no maw/MCP needed

Auto-detect logic (when no flag):

  1. Check ψ/contacts.json → has maw field? → use maw hey
  2. No contacts? → maw ls 2>/dev/null | grep -q "{agent}" fallback → use maw hey
  3. Neither? → use MCP thread (async, persistent)
bash
# Auto-detect: contacts-first, maw ls fallback
if [ -n "$MAW" ]; then
  echo "USE_MAW (from contacts: $MAW)"
elif maw ls 2>/dev/null | grep -q "{agent}"; then
  echo "USE_MAW (from maw ls)"
else
  echo "USE_THREAD"
fi

Replying to a message another oracle sent you (#434)

A ping arrives in your context looking like [m5:digger] …. The reflex is to answer in your own transcript — but that text goes to Nat, not to digger, who is sitting in a different pane waiting. Reply with maw hey or the conversation is one-sided and nobody notices for hours.

bash
maw hey <their-oracle-name> 'your reply'     # name, not a pane id

Never reply to a pane id. maw peek %3001 works, so it is tempting to paste that same %3001 into maw hey — it hard-errors (bare target '%3001' not found locally). Pane ids are a peek-only handle. maw ls -v is the source of truth for targets; a bare maw ls | grep finds the row but not the addressable name, which is why the auto-detect above should be treated as a hint, not an answer:

bash
maw ls -v | grep -i <name>      # resolves the real target
maw hey <target> ping --dry-run # confirm it resolves BEFORE sending

--dry-run is the cheap check. It costs nothing and catches a wrong target before the message goes somewhere confusing.

When using --maw:

  1. Compose message from intent
  2. Use contacts maw name if available: maw hey {MAW or agent-oracle} '{message}'
  3. Optionally maw peek {agent} to check response
  4. Confirm: Sent via maw to {agent}

When using --inbox:

  1. Compose message from intent
  2. Check contacts for inbox path — if empty, error: No inbox path for {agent}. Run /contacts show {agent}
  3. Write message file:
    bash
    SELF="$(basename $(pwd) | sed 's/-oracle$//')"
    echo "$MESSAGE" > "$INBOX/$(date +%Y%m%d_%H%M)_from_${SELF}.md"
  4. Confirm: Dropped to {agent}'s inbox

When using --thread (or auto-detected thread): Fall through to Mode 3 (one-shot) below.

Routing

PatternUse
channel:{agent}Persistent per-agent channel
topic:{agent}:{slug}Topic-specific thread (with --topic)
#{id}Direct thread reference by ID

Mode 1: --list

  1. arra_threads() (no status filter)
  2. Filter titles starting with channel: or topic:, exclude closed
  3. Display: channel:arthur (#42) pending — 12 msgs

Mode 2: --new (fast create)

Skip lookup. One MCP call.

  1. Compose message from intent
  2. arra_thread({ title: "channel:{agent}", message, role: "human" })
  3. Notify: Bash maw hey {MAW or agent-oracle} 'Thread #{id} from {self}: {preview}'
    • If maw hey fails → warn only, don't error (thread already sent)
  4. Confirm: Created channel:{agent} (thread #{id})

Mode 3: One-shot (default)

  1. Compose message from intent
  2. If first arg is #{id} → post directly to that thread ID
  3. Otherwise: arra_threads() → find channel:{agent}, create if missing
  4. Post message to thread
  5. Notify: Bash maw hey {MAW or agent-oracle} 'Thread #{id} from {self}: {preview}'
    • If maw hey fails → warn only, don't error (thread already sent)
  6. arra_thread_read({ threadId }) → show any agent responses
  7. Confirm: Posted to channel:{agent} (thread #{id})

Mode 4: loop (autonomous conversation)

Like Ralph loop — AI drives the conversation autonomously. No user prompts between turns.

  1. Find or create thread (channel:{agent}, or --new to skip lookup)
  2. Compose opening message from user's intent and post it
  3. Autonomous loop (max 10 iterations): a. arra_thread_read({ threadId }) — check for new messages b. If agent responded: read their response, compose a thoughtful follow-up, post it c. If no new response: compose a follow-up question or probe deeper, post it d. After each exchange, briefly note what you learned e. Stop when: enough insight gathered, conversation circling, or 10 iterations hit
  4. Notify (once, after opening message): Bash maw hey {MAW or agent-oracle} 'Thread #{id} from {self}: {preview}'
    • If maw hey fails → warn only, don't error
  5. Show summary:
    Conversation with {agent} (thread #{id}) — {n} messages, {iterations} turns
    
    Key insights:
    - [insight 1]
    - [insight 2]
  6. Leave thread open for future use

The goal is insight extraction. You are having a conversation on behalf of the human to learn something useful.

Parsing Rules

  • First arg = agent name (lowercase), #id (thread ref), or --list
  • --new = skip lookup, create fresh
  • loop = autonomous conversation (AI drives, no user prompts)
  • --topic "slug" = use topic:{agent}:{slug} instead of channel:{agent}
  • Everything else = the message/intent

Message Composition

CRITICAL: You are the composer. The user gives intent, you write the message.

  • Compose a clear, natural message from the user's intent
  • Post immediately — do NOT ask the user what to say
  • Do NOT use AskUserQuestion for message content
  • Show what you posted after sending

If the message already reads like a direct message (e.g. "What's your status?"), post as-is.

Auto Notification (maw hey)

After posting to a thread, notify the target agent via maw hey:

maw hey {MAW or agent-oracle} 'Thread #{id} from {self}: {first 60 chars of message}'
  • {MAW} = contacts maw field (e.g. "mawjs-oracle") — preferred over {agent}-oracle
  • {self} = current Oracle's name (e.g. "Mother Oracle")
  • {preview} = first ~60 chars of the posted message
  • Runs once per /talk-to invocation (not per loop iteration)
  • Fail-safe: if maw hey errors, log warning and continue — the thread is the source of truth

Important Notes

  • Agent names are always lowercase
  • Thread titles are the routing key — never modify existing thread titles
  • One channel thread per agent (reuse, don't recreate)
  • #{id} lets users reference any thread directly — no lookup needed
  • All messages attributed with role: "human"

ARGUMENTS: $ARGUMENTS

Frequently asked questions

What does the Talk To AI skill do?

Talk to another Oracle agent via contacts + threads. Use when user says "talk to", "message", "chat with", or wants to communicate with another agent (e.g. "talk to pulse", "message neo"). Do NOT trigger for OracleNet social feed (use /oraclenet), skill management (use /oracle), or family registry (use /oracle-family-scan).

Why use Talk To on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Soul-Brews-Studio/arra-oracle-skills-cli/tree/alpha/src/skills/talk-to. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Talk To?

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 Talk To?

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

Is the Talk To AI skill free?

Yes. It is published on GitHub by Soul-Brews-Studio 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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