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Deepchat Cli

OrganizationPopular
ThinkInAIXYZ
deepchat-cli

Use DeepChat's bundled CLI control plane for model inference, image/video/speech generation, transcription, OCR, artifact inspection, public configuration, Skills, and MCP operations. Activate when a user asks to invoke DeepChat capabilities that are not already exposed as a more specific tool, compare models, run a benchmark, inspect DeepChat runtime state, or manage DeepChat through the CLI.

Overview

PublisherThinkInAIXYZ
Repositorydeepchat
Skill namedeepchat-cli
Stars
6.3K
Forks
734
Bundled files
Instructions only
LicenseApache-2.0
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 ThinkInAIXYZ on GitHub. Read the source before you install it.

Installation

Install the Deepchat Cli 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/ThinkInAIXYZ/deepchat.git /tmp/deepchat
mkdir -p .claude/skills
cp -r /tmp/deepchat/resources/skills/deepchat-cli .claude/skills/deepchat-cli
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deepchat Cli 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 Deepchat Cli 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 Deepchat Cli 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.

DeepChat CLI

Use the bundled deepchat command to ask the running DeepChat main process to perform supported operations. The main process remains the sole owner of providers, credentials, Skills, MCP servers, artifacts, Agent runs, and approvals.

Command rules

  • Every command must begin exactly with deepchat <domain> <verb>. Put --json, --jsonl, --timeout, and all domain options after the domain and verb.
  • Execute one standalone command per exec call. Do not use pipes, redirection, command separators, command substitution, environment assignments, or shell wrappers around deepchat.
  • Quote every user-controlled argument for the current shell. Never interpolate untrusted text into an unquoted command.
  • Prefer --json for one result and --jsonl for streaming or benchmark collection. Use text mode only when its output will be returned directly to the user.
  • Do not inspect authentication environment variables or DeepChat's local descriptor. Authorization is injected only after the command has passed the normal shell permission check.
  • A shell approval authorizes command execution. Sensitive mutations can additionally pause for a renderer approval; wait for that decision and never attempt to manufacture confirmation data.
  • Use deepchat help or deepchat <domain> <verb> --help only when the options below are insufficient. Do not probe undocumented routes.

Agent file and recursion boundaries

  • Agent callers may consume a DeepChat-owned artifact with --artifact <id> and inspect metadata with artifact describe.
  • Do not use --file, --out, --overwrite, artifact get, or artifact delete. Agent callers cannot upload arbitrary local bytes, download artifact bytes, or choose output paths.
  • Do not call agent run or run watch. An Agent cannot recursively create a detached Agent run, and waiting on its own currently executing run would deadlock it. Use run get for a nonblocking snapshot or run cancel to request cancellation.
  • Generated media remains in DeepChat's artifact spool. Return the artifact metadata or ID so the application can render or reuse it.

Discovery and model calls

text
deepchat system status --json
deepchat system capabilities --json
deepchat system doctor --json
deepchat provider list --enabled-only --json
deepchat model list --provider <provider-id> --json
deepchat model config-get --provider <provider-id> --model <model-id> --json
deepchat model invoke --provider <provider-id> --model <model-id> --prompt <quoted-text> --jsonl

Always discover provider and model IDs rather than guessing them. model invoke is a raw provider call: it does not create a chat session, run tools, or start an Agent loop.

Media, transcription, and OCR

text
deepchat image generate --provider <provider-id> --model <model-id> --prompt <quoted-text> --jsonl
deepchat video generate --provider <provider-id> --model <model-id> --prompt <quoted-text> --jsonl
deepchat audio speak --provider <provider-id> --model <model-id> --text <quoted-text> --jsonl
deepchat audio transcribe --provider <provider-id> --model <model-id> --artifact <artifact-id> --json
deepchat ocr status --json
deepchat ocr extract --artifact <artifact-id> --json
deepchat artifact describe --id <artifact-id> --json

Use the provider/model lists to choose a compatible runtime. OCR is local and does not require a provider. OCR text is returned inline and is not written to the artifact spool.

Public configuration and management

Read-only operations:

text
deepchat settings get --json
deepchat skill list --json
deepchat mcp list --json

Agent callers may request renderer approval for preference-only settings, query-free HTTPS Skill installation, and adding a new disabled HTTPS remote MCP configuration. Only perform one when it directly satisfies the user's request:

text
deepchat settings set --key <public-key> --value <json-scalar> --json
deepchat skill install --url <https-url> --json
deepchat mcp add --name <server-name> --stdin --json

The Agent setting allowlist is limited to presentation preferences such as font size/family, artifact effects, auto-scroll, notifications, and copy-with-reasoning. Agent Skill URLs cannot carry credentials, query parameters, or fragments. The main process classifies MCP input before approval and rejects stdio commands, non-HTTPS endpoints, headers, authorization bindings, or configurations too large to review safely. Provider/model configuration, credential writes, local Skill archives, Skill enable/disable/removal, MCP update/runtime control/removal, and every destructive operation require the DeepChat UI or a human terminal.

Benchmark discipline

  • Pin provider/model IDs and pass per-invocation options; do not mutate global defaults to prepare a benchmark.
  • Record structured output, exit status, wall time, and errors. Preserve failed samples.
  • For OCR, distinguish cache hit, cache miss with warm runtime, cold runtime after app restart, and offline availability. ocr clear-cache initializes the resource graph but does not start the OCR helper, so classify the next extraction from its reported pre-extraction runtime state.
  • Run samples sequentially unless the benchmark explicitly measures concurrency; Agent compute is rate-limited and bounded by the main process.

Frequently asked questions

What does the Deepchat Cli AI skill do?

Use DeepChat's bundled CLI control plane for model inference, image/video/speech generation, transcription, OCR, artifact inspection, public configuration, Skills, and MCP operations. Activate when a user asks to invoke DeepChat capabilities that are not already exposed as a more specific tool, compare models, run a benchmark, inspect DeepChat runtime state, or manage DeepChat through the CLI.

Why use Deepchat Cli on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ThinkInAIXYZ/deepchat/tree/dev/resources/skills/deepchat-cli. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Deepchat Cli?

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 Deepchat Cli?

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

Is the Deepchat Cli AI skill free?

Yes. It is published on GitHub by ThinkInAIXYZ under the Apache-2.0 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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