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Simulator Chat

Organization
corezoid
simulator-chat

Simulator.Company chat & messaging specialist — sending messages to a user, and creating or reusing p2p (1:1) and group chats. In Simulator a chat is an actor of the Events system form (data.chatType = "p2p" | "group"), its participants are the actor's access-rule members, and its messages are `comment` reactions. Use when the user wants to "message", "write to", "DM", "send a message to" someone, "open a chat with", "start a conversation", or "reply in the chat". Activate on "write a message to user N", "send N a message", "open a chat with", "message someone", "напиши повідомлення користувачу", "надішли повідомлення", "відкрий чат з", "почни розмову з", "напиши юзеру", "напиши сообщение пользователю", "отправь сообщение", "открой чат с", "напиши в чат". For comments/approvals on an arbitrary actor (not a chat) use `simulator-reactions`; for files use `simulator-attachments`; for sharing/access in general use `simulator-access`.

Overview

Publishercorezoid
Repositorysimulator-ai-plugin
Skill namesimulator-chat
Stars
61
Forks
13
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 corezoid on GitHub. Read the source before you install it.

Installation

Install the Simulator Chat 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/corezoid/simulator-ai-plugin/tree/main/plugins/simulator/skills/simulator-chat
  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/corezoid/simulator-ai-plugin.git /tmp/simulator-ai-plugin
mkdir -p .claude/skills
cp -r /tmp/simulator-ai-plugin/plugins/simulator/skills/simulator-chat .claude/skills/simulator-chat
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Simulator Chat 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 Simulator Chat 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 Simulator Chat 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.

Curated tool names (v2 server): searchUsers, getUsers, getSystemActor, getForms, filterActors, createActor, getActorByRef, saveAccessRules, createReaction, getReactions. Call them by these exact names. There is no dedicated "create chat" / "send message" tool — a chat is composed from these.

Simulator.Company Chat Specialist

In Simulator.Company a chat is an actor of the Events system form:

  • data.chatType = "p2p" → a 1:1 chat · "group" → a group chat · empty → a plain event / SIP meeting (not a chat).
  • Participants = the chat actor's access-rule members (keyed by userId) — not a data field. The creator is the implicit owner; other participants are added with saveAccessRules.
  • Messages = comment reactions posted under the chat actor.

There is no server-side "p2p has exactly two members / don't duplicate" enforcement — this skill owns that discipline, and it must match the platform's standard p2p convention or two clients will create duplicate chats for the same pair. The convention:

  • Deterministic ref = p2pConversation_<minUserId>_<maxUserId> — both participants' raw workspace userIds sorted ascending, joined with _. This is the p2p dedup key; the UI finds/reuses a chat only by this ref.
  • title = <nickA>:p2p:<nickB> — nicks ordered by the same ascending userId sort.
  • data = { chatType:"p2p", startDate:<nowSec>, endDate:<nowSec>, scheduleMeeting:false }.
  • Participants are added by a separate saveAccessRules call (never inline in the create body); the creator is owner implicitly.

Read $CLAUDE_PLUGIN_ROOT/docs/entities/chats.md for the full model, the verbatim Events-form field list, and the current-user constraint.

Reply to the user in their own language.


Test case: "write a message to user N"

This is the canonical flow. Each step names the exact tool.

1 — Resolve user N

searchUsers(query="N")          # accId defaults to the active workspace

Take N's userId from the result (e.g. 4210). If several match, ask the user which one (or show name + email). getUsers lists everyone if you need to browse.

getSystemActor(objType="user", objId=<userId>) returns N's system "twin" actor. You usually do not need it to chat — membership uses the raw userId — but it get-or-creates the twin if some flow needs N represented as an actor.

2 — Resolve the Events form id (per workspace)

getForms(formTypes="system")    # find the row whose title == "Events" → its id

The Events form id differs per workspace, so don't hardcode it. (You may instead pass formName="Events" to createActor and let it resolve the id.)

3 — Build the canonical ref + title (reuse key)

The p2p dedup key needs both userIds. The recipient's came from step 1; resolve the sender's userId too (see the box below), then:

ids   = sortAscending(senderUserId, N_userId)        # numeric ascending
ref   = "p2pConversation_" + ids[0] + "_" + ids[1]   # e.g. p2pConversation_4210_4310
title = nick(ids[0]) + ":p2p:" + nick(ids[1])        # e.g. olena:p2p:petro

Getting the sender's userId. There is no PAPI "current user" endpoint, and the auth token carries the caller's saId+nick, not the per-workspace userId. So: ask the user, take it from context, or getUsers and match the token's saId/nick to a member's id. If you cannot get it, fall back to discovery-by-member in step 4 and skip the ref (note: a ref-less chat may be duplicated later by the web UI, which keys reuse on ref).

4 — Find an existing chat (reuse, don't duplicate)

Canonical — by the deterministic ref, exactly as the web UI does:

getActorByRef(formId=<EventsFormId>, ref=<ref>)     # found → reuse its id, skip to step 6

Fallback when the sender's userId is unknown — discover by participant (still finds UI-created chats, since the recipient is an access member):

filterActors(formId=<EventsFormId>, q="chatType=p2p", members="<N_userId>:view")

5 — Create the p2p chat (only if none exists)

createActor(
  formName="Events",                       # or formId=<EventsFormId>
  title=<title>,                           # "<nickA>:p2p:<nickB>"
  ref=<ref>,                               # p2pConversation_<minId>_<maxId> — REQUIRED for UI reuse
  data={ "chatType": "p2p",
         "startDate": <nowUnixSeconds>,
         "endDate":   <nowUnixSeconds>,
         "scheduleMeeting": false })        # plain unix SECONDS on Events — not a calendar object

startDate/endDate are required by the Events form. On a chat they are just "now" as integer unix seconds (the nested calendar {startDate,endDate,...} object used elsewhere does not apply here).

Then add N as the second participant (the creator is owner implicitly — do not add a self access-rule):

saveAccessRules(
  objType="actor", objId="<newChatId>",
  rules=[{ "action":"create",
           "data":{ "userId": <N_userId>,
                    "privs":{ "view":true, "modify":true, "remove":true } } }])

saveAccessRules is applied asynchronously and returns a taskId; posting the message next still works.

6 — Post the message (a comment reaction)

createReaction(type="comment", actorId="<chatId>", description="<the message text>")

That comment reaction under the chat actor is the chat message. To read the conversation back: getReactions(actorId="<chatId>", view="flat", orderValue="ASC").


Variations

  • Group chat. Create with data.chatType="group" and no ref (the UI gives group chats no dedup), then saveAccessRules (or bulkSaveAccessRules) for every participant userId. To find a group's members later, filter by them: filterActors(members="11:view,22:view,33:view", q="chatType=group").
  • Reply in a thread. Pass parentId=<reactionId> to createReaction (see simulator-reactions).
  • Attach a file to a message. Upload first (uploadBase64 → attachId), then createReaction(..., attachments=[{attachId:<id>}]) — see simulator-attachments.
  • Post quietly (no notification). createReaction(..., notify=false).
  • Hand the message to the AI agent. createReaction(..., extra={mcp:true}) runs the platform AI agent on it under the requesting user's access (see simulator-reactions).

Reuse & safety rules

  • Always look up (step 4) before creating (step 5). Creating a second p2p Events actor for the same pair silently produces a duplicate chat — the platform does not dedupe; only the deterministic ref does.
  • Always set the canonical ref on create (p2pConversation_<minId>_<maxId>) so the web UI reuses the same chat instead of making its own duplicate.
  • Participants are access rules, never data fields. Do not store member ids in data, and do not add a self access-rule (the creator is owner implicitly).
  • Confirm before messaging on the user's behalf if the message is outward-facing — a chat message notifies the recipient.
  • A chat needs chatType set; an Events actor without it is a plain event/meeting, and comments on it are ordinary discussion, not chat messages.

Relationship to the other skills

SkillBoundary
simulator-agentsDelegating work to a person as an agent (assess who fits, then act / task / message) — it composes this p2p flow for its "message the person" outcome.
simulator-reactionsGeneric comments/approvals/ratings on any actor (a chat message is a comment reaction — that skill covers the reaction mechanics).
simulator-actorsThe Events actor's own data fields and the actor data value protocol.
simulator-accessAccess rules in general (chat participants are access-rule members).
simulator-attachmentsFiles on a message/actor.
simulator-initLogin + workspace selection (needed before any of this).

Reference Documents

PathWhen to read
$CLAUDE_PLUGIN_ROOT/docs/entities/chats.mdThe chat model: Events form, chatType, members-as-access, messages-as-reactions
$CLAUDE_PLUGIN_ROOT/docs/entities/reactions.mdReaction types, tree/threading, AI-agent reactions
$CLAUDE_PLUGIN_ROOT/docs/entities/system-forms.mdThe Events system form among the built-ins

Tips

  • accId/workspace defaults to the active one — make sure simulator-init ran first.
  • The Events form id is per workspace — resolve it (getForms/formName), never hardcode.
  • On Events, startDate/endDate are plain unix seconds, both "now" for a chat.
  • Canonical reuse = getActorByRef(ref="p2pConversation_<minId>_<maxId>") (matches the web UI); it needs both userIds — the sender's isn't in the token (saId/nick only, no PAPI /me), so derive it or fall back to filterActors(members=…, q="chatType=p2p").
  • A message is just createReaction(type="comment", actorId=<chatId>, description=...).

Frequently asked questions

What does the Simulator Chat AI skill do?

Simulator.Company chat & messaging specialist — sending messages to a user, and creating or reusing p2p (1:1) and group chats. In Simulator a chat is an actor of the Events system form (data.chatType = "p2p" | "group"), its participants are the actor's access-rule members, and its messages are `comment` reactions. Use when the user wants to "message", "write to", "DM", "send a message to" someone, "open a chat with", "start a conversation", or "reply in the chat". Activate on "write a message to user N", "send N a message", "open a chat with", "message someone", "напиши повідомлення користу...

Why use Simulator Chat on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/corezoid/simulator-ai-plugin/tree/main/plugins/simulator/skills/simulator-chat. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Simulator Chat?

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 Simulator Chat?

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

Is the Simulator Chat AI skill free?

Yes. It is published on GitHub by corezoid 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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