Agent skill

DeepChat Provider Integration

by ThinkInAIXYZ in ThinkInAIXYZ/deepchat

Guides adding an LLM provider to DeepChat through explicit source changes: collect the provider details, pick a transport path and add registry entries and tests.

Apache-2.0Auto-check passedDevelopment

Install DeepChat Provider Integration

skills CLI
$ npx skills add ThinkInAIXYZ/deepchat --skill add-provider -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ThinkInAIXYZ/deepchat add-provider --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ThinkInAIXYZ/deepchat.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/add-provider .claude/skills/add-provider && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
add-provider
GitHub stars
6.4k
Token cost
~1.2k tokens
SKILL.md length
496 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
Apache-2.0

At a glance

Guides adding an LLM provider to DeepChat through explicit source changes: collect the provider details, pick a transport path and add registry entries and tests.

  • Works in 7 steps: Read… → Inspect the current provider files… → Classify the request into one supported… → …
  • Adding a new OpenAI-compatible provider to DeepChat
  • SKILL.md covers Goal, Required Inputs, Supported Paths and Guardrails, plus 2 more sections
  • Calls pnpm

What it does

This skill guides a developer through adding an LLM provider to DeepChat with explicit, reviewable source changes. Provider display data lives in the public provider configuration, runtime behavior is mapped to a known transport, and a special provider implementation is used only when the API's behavior requires one.

Before editing, the agent collects the provider ID in kebab case, display name, API type, default base URL, auth type, model metadata source, a test model and check strategy, official URLs and any request quirks. It then follows one of three paths: an OpenAI-compatible API, an existing native transport such as Anthropic, Gemini, Vertex, Azure, Bedrock, Ollama or ACP, or a special provider with its own adapter, instance manager entry and settings UI.

Guardrails forbid adding a runtime definition type or generated manifests, installing provider SDK packages automatically, and executing provider logic in the renderer. Each path lists the typical files to touch and the provider registry or creation tests to add.

When your agent uses it

  • Adding a new OpenAI-compatible provider to DeepChat
  • Mapping a provider onto an existing native transport
  • Writing a special provider adapter for unusual auth or streaming
  • Adding provider auth, model catalog mapping or profile config

Example prompts

  • “Add a new OpenAI-compatible provider called acme-ai to DeepChat with a default base URL and API key auth.”
  • “Map this provider to the existing Anthropic transport and add the registry entry and tests.”
  • “This provider uses OAuth and a custom streaming format; scaffold a special provider adapter.”

Requirements

  • A checkout of the DeepChat repository

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Read docs/features/provider-runtime/spec.md when the provider work touches the provider runtime
  2. Inspect the current provider files before editing
  3. Classify the request into one supported path.
  4. Add the smallest explicit source changes for that path.
  5. After implementation, assess provider creation, auth handling, and model discovery for durable
  6. Update an active SDD plan.md as coherent implementation slices land, when one exists. For a
  7. Run

What it can do on your machine

Read from SKILL.md and the folder at commit bfa6d76. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pnpm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pnpm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

DeepChat Provider Integration loads about 1.2k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 496 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ThinkInAIXYZ/deepchat at commit bfa6d76, republished under its Apache-2.0 licence (© ThinkInAIXYZ). 496 words, ~1,169 tokens.

Download SKILL.mdSave it as .claude/skills/add-provider/SKILL.md (or your agent's skills folder).
name
add-provider
description
Add a DeepChat LLM provider through explicit reviewed source changes. Use when a developer asks Codex to add a provider, provider profile, upstream provider config, model catalog mapping, provider auth behavior, or a special provider adapter in this repository.

Add Provider

Goal

Generate DeepChat provider integration changes against the current provider architecture. Keep provider display data in PublicProviderConf, map runtime behavior to known transports, and use a special provider implementation only when the API behavior requires one.

Required Inputs

Collect or derive these before editing source:

  • Provider ID in kebab case.
  • Display name.
  • API type or known transport family.
  • Default base URL.
  • Auth type: API key, no auth, OAuth, profile credentials, or provider-specific credential.
  • Model metadata source: built-in config, provider-db, config-db, live model fetch, or custom only.
  • Test model ID and check strategy.
  • Official website, API key URL, docs URL, model list URL.
  • Request quirks: headers, endpoint suffixes, route rewrites, streaming shape, tool-call support, reasoning support, image/audio/embedding endpoints, or proxy requirements.

Supported Paths

OpenAI-Compatible API

Use this when the provider supports OpenAI Chat Completions or Responses-compatible HTTP APIs.

Typical files:

  • src/main/provider/defaults.ts
  • src/main/provider/providerId.ts
  • src/main/provider/providerRegistry.ts for runtime strategies and derived public catalog membership
  • test/main/** provider registry or creation tests
Existing Native Transport

Use this when the provider maps to an existing DeepChat transport such as Anthropic, Gemini, Vertex, Azure, Bedrock, Ollama, or ACP.

Typical files:

  • src/main/provider/defaults.ts
  • src/main/provider/providerRegistry.ts
  • Settings components only when the existing generic form lacks required fields
  • Focused tests for provider creation and connection checks
Special Provider

Use this when auth, request shape, streaming, discovery, or error handling differs from existing transports.

Typical files:

  • src/main/provider/providers/<providerName>Provider.ts
  • src/main/provider/<providerName>Adapter.ts
  • src/main/provider/managers/providerInstanceManager.ts
  • src/shared/contracts/routes/* and src/renderer/api/*Client.ts for interactive auth
  • src/renderer/settings/components/* for provider-specific settings UI
  • Main and renderer tests covering the new behavior

Guardrails

  • Do not introduce ProviderRuntimeDefinition, generated runtime manifests, or runtime package-name inference.
  • Do not install provider SDK packages automatically.
  • Do not execute provider logic in the renderer.
  • Do not store new OAuth credentials in provider API-key fields.
  • Do not add a special provider when a known transport and explicit config are sufficient.
  • Reject the request when the required inputs cannot identify a safe path.
Show full SKILL.md (186 more words)Show less

Workflow

  1. Read docs/features/provider-runtime/spec.md when the provider work touches the provider runtime scope. Also read plan.md if it exists for an active provider-runtime goal. Treat any legacy tasks.md as migration input rather than another execution tracker.
  2. Inspect the current provider files before editing:
    • src/main/provider/defaults.ts
    • src/main/provider/providerId.ts
    • src/main/provider/providerRegistry.ts
    • src/main/provider/aiSdk/providerFactory.ts
    • src/main/provider/managers/providerInstanceManager.ts
    • src/renderer/settings/components/ProviderApiConfig.vue
  3. Classify the request into one supported path.
  4. Add the smallest explicit source changes for that path.
  5. After implementation, assess provider creation, auth handling, and model discovery for durable regression coverage; add only the smallest contract-level tests warranted.
  6. Update an active SDD plan.md as coherent implementation slices land, when one exists. For a legacy tasks.md, merge remaining work into the existing plan; without one, keep a single-slice complex bug checklist in spec.md and create plan.md for feature, architecture, or multi-slice bug work. Do not update or recreate the task file.
  7. Run:
bash
pnpm run format
pnpm run i18n
pnpm run lint
pnpm run typecheck

Run focused main/renderer tests for any touched provider code.

Output Checklist

Report:

  • Provider ID and API type.
  • Selected path.
  • Files changed.
  • Runtime transport or special provider class.
  • Credential storage location.
  • Model metadata source.
  • Check strategy and test model.
  • Validation commands run.

© ThinkInAIXYZ, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/add-provider of ThinkInAIXYZ/deepchat.

Open the folder on GitHubat commit bfa6d76

Compare with similar skills

DeepChat Provider Integration next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

DeepChat Provider Integration compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
DeepChat Provider Integration this skillThinkInAIXYZ/deepchat6.4k—~1.2kAutomated safety check: PassApache-2.0
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Deep Reviewdyad-sh/dyad22k—~1.4kAutomated safety check: PassCustom licence
Azure AI Projects Python SDKmicrosoft/skills3.1k—~2.8kAutomated safety check: PassMIT
Provider Integrationhex/claude-council857—~635Automated safety check: PassMIT
ModLens Image Vision Bridgeliustack/modlens4.2k—~1.3kAutomated safety check: NotesMIT

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Questions about DeepChat Provider Integration

What does DeepChat Provider Integration do?

Guides adding an LLM provider to DeepChat through explicit source changes: collect the provider details, pick a transport path and add registry entries and tests. This skill guides a developer through adding an LLM provider to DeepChat with explicit, reviewable source changes. Provider display data lives in the public provider configuration, runtime behavior is mapped to a known transport, and a special provider implementation is used only when the API's behavior requires one.

When should I use DeepChat Provider Integration?

DeepChat Provider Integration fits situations like: adding a new OpenAI-compatible provider to DeepChat; mapping a provider onto an existing native transport; writing a special provider adapter for unusual auth or streaming; adding provider auth, model catalog mapping or profile config.

How do I install DeepChat Provider Integration in Claude Code?

Run `npx skills add ThinkInAIXYZ/deepchat --skill add-provider -a claude-code`. Or copy the skill folder (.agents/skills/add-provider in ThinkInAIXYZ/deepchat) into .claude/skills/add-provider in your project. Claude Code loads it when a task matches its description.

How do I install DeepChat Provider Integration in Codex?

Run `npx skills add ThinkInAIXYZ/deepchat --skill add-provider -a codex`. Or copy the skill folder (.agents/skills/add-provider in ThinkInAIXYZ/deepchat) into .agents/skills/add-provider in your project. Codex loads it when a task matches its description.

Can I use DeepChat Provider Integration in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ThinkInAIXYZ/deepchat --skill add-provider -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/add-provider, .gemini/skills/add-provider, .github/skills/add-provider and .opencode/skills/add-provider in your project.

What does DeepChat Provider Integration need to run?

Going by SKILL.md and its folder, DeepChat Provider Integration needs the command-line tools its instructions call (pnpm). Our summary lists: A checkout of the DeepChat repository.

Does DeepChat Provider Integration access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is DeepChat Provider Integration safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does DeepChat Provider Integration use?

DeepChat Provider Integration is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does DeepChat Provider Integration use?

About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to DeepChat Provider Integration?

Skills that share tags, products or a category with DeepChat Provider Integration: AI Daily Digest (vigorX777/ai-daily-digest, 1.6k stars), Deep Review (dyad-sh/dyad, 22k stars), Azure AI Projects Python SDK (microsoft/skills, 3.1k stars) and Provider Integration (hex/claude-council, 857 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains DeepChat Provider Integration?

ThinkInAIXYZ (a GitHub organization) maintains it in ThinkInAIXYZ/deepchat, which has 6,356 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 10, 2026.

Source: ThinkInAIXYZ/deepchat on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.