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Opencode providers

Skill Timmy6942025/opencode-builder-skill/skills/opencode-providers

Kilo/agent skill for building OpenCode extensions, plugins, and integrations

Install
npx -y skills add Timmy6942025/opencode-builder-skill --skill opencode-providers

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Use this skill when configuring LLM providers in OpenCode, setting up API keys, connecting providers via /connect, configuring custom OpenAI-compatible providers, setting up local models (Ollama, llama.cpp, LM Studio), or troubleshooting provider authentication issues. Covers all 75+ supported providers, OpenCode Zen, OpenCode Go, provider-specific options, and environment variable configuration.

SKILL.md

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OpenCode Providers

📚 Official Docs: For the latest information, always refer to the official documentation: https://opencode.ai/docs/providers/

Overview

OpenCode uses the AI SDK and Models.dev to support 75+ LLM providers and local models. Providers are configured through opencode.json and authenticated via the /connect command.

Quick start:

  1. Run /connect in the TUI and select your provider
  2. Enter your API key when prompted
  3. Run /models to select a model

Credentials

API keys added via /connect are stored in ~/.local/share/opencode/auth.json.

Provider Config

Customize providers through the provider section in opencode.json:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "anthropic": {
      "options": {
        "baseURL": "https://api.anthropic.com/v1"
      }
    }
  }
}

Key config fields:

  • npm — AI SDK package (e.g. @ai-sdk/openai-compatible for OpenAI-compatible endpoints, @ai-sdk/openai for /v1/responses endpoints)
  • name — Display name in UI
  • options.baseURL — API endpoint URL
  • options.apiKey — API key (or use /connect)
  • options.headers — Custom headers sent with each request
  • models — Map of model IDs to configurations
  • limit.context — Maximum input tokens the model accepts
  • limit.output — Maximum tokens the model can generate

OpenCode Zen

OpenCode Zen is a curated list of tested and verified models provided by the OpenCode team. It works like any other provider — pay-as-you-go, completely optional.

Setup:

  1. Sign in at opencode.ai/auth, add billing details, copy API key
  2. Run /connect, select OpenCode Zen, paste API key
  3. Run /models to see recommended models

Free models available:

  • DeepSeek V4 Flash Free
  • MiMo-V2.5 Free
  • Nemotron 3 Super Free
  • Big Pickle (stealth model)

Pricing (per 1M tokens, selected models):

ModelInputOutputCached Read
GPT 5.5 (≤272K)$5.00$30.00$0.50
GPT 5.4$2.50$15.00$0.25
Claude Opus 4.8$5.00$25.00$0.50
Claude Sonnet 4.6$3.00$15.00$0.30
Gemini 3.5 Flash$1.50$9.00$0.15
Kimi K2.5$0.60$3.00$0.10
MiniMax M2.7$0.30$1.20$0.06
Qwen3.6 Plus$0.20$1.20$0.02
GPT 5 Nano$0.05$0.40$0.005

Features:

  • Auto-reload: Balance below $5 triggers $20 reload (configurable, can disable)
  • Monthly limits: Set per-workspace and per-member spending caps
  • Teams: Invite teammates, assign roles (Admin/Member), curate model access, bring your own keys
  • Privacy: Zero-retention by default; free models may use data for improvement; OpenAI/Anthropic retain requests 30 days

Model ID format in config: opencode/<model-id> (e.g. opencode/gpt-5.5)

Endpoints:

  • OpenAI models: https://opencode.ai/zen/v1/responses
  • Anthropic models: https://opencode.ai/zen/v1/messages
  • Google models: https://opencode.ai/zen/v1/models/<model>
  • Other models: https://opencode.ai/zen/v1/chat/completions

OpenCode Go

OpenCode Go is a low-cost subscription plan for popular open coding models.

  • $5 first month, $10/month after that
  • Models tested and verified for coding tasks

Setup:

  1. Run /connect, select OpenCode Go, go to opencode.ai/auth
  2. Sign in, add billing, copy API key
  3. Paste API key in terminal
  4. Run /models to see available models

Usage limits:

  • 5 hour limit: $12
  • Weekly limit: $30
  • Monthly limit: $60

Available models:

  • GLM-5
  • GLM-5.1
  • Kimi K2.5
  • Kimi K2.6
  • MiMo-V2.5
  • MiMo-V2.5-Pro
  • MiniMax M2.5
  • MiniMax M2.7
  • Qwen3.6 Plus
  • Qwen3.7 Max
  • DeepSeek V4 Pro
  • DeepSeek V4 Flash

Major Providers

Anthropic (Claude)

Supports Claude Pro/Max OAuth and API keys.

Setup:

  1. Run /connect, select Anthropic
  2. Select Claude Pro/Pro Max for OAuth (opens browser) or Manually enter API Key
  3. Run /models to select model

Available models: Claude Opus 4, Claude Sonnet 4, Claude Haiku 3.5, and others.

Config example:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "anthropic": {
      "options": {
        "baseURL": "https://api.anthropic.com/v1"
      }
    }
  }
}

Note: Claude Pro/Max OAuth is the only supported way to use Anthropic subscriptions. Third-party plugins that use Claude subscriptions are explicitly prohibited by Anthropic and are no longer bundled with OpenCode as of v1.3.0.

OpenAI

Supports ChatGPT Plus/Pro OAuth and API keys.

Setup:

  1. Run /connect, select OpenAI
  2. Select ChatGPT Plus/Pro for OAuth or Manually enter API Key
  3. Run /models to select model

Using API keys: Select Manually enter API Key and paste your key.

xAI

Supports SuperGrok OAuth, device-code flow, and API keys.

Auth Method 1 — SuperGrok OAuth (browser):

  1. Run /connect, select xAI
  2. Select xAI Grok OAuth (SuperGrok Subscription)
  3. Browser opens for consent

Auth Method 2 — SuperGrok device-code (headless/VPS):

  1. Run /connect, select xAI
  2. Select xAI Grok OAuth (Headless/Remote/VPS)
  3. Visit the verification URL on another device and enter the displayed code

Auth Method 3 — API key:

  1. Create API key at console.x.ai
  2. Run /connect, select xAI
  3. Select Manually enter API Key and paste your key

Available models: Grok Beta and others.

GitHub Copilot

Uses device code flow. Requires GitHub Copilot subscription (some models need Pro+).

Setup:

  1. Run /connect, search for GitHub Copilot
  2. Navigate to github.com/login/device and enter the displayed code
  3. Wait for authorization
  4. Run /models to select model
┌ Login with GitHub Copilot
│
│ https://github.com/login/device
│
│ Enter code: 8F43-6FCF
│
└ Waiting for authorization...

Google Vertex AI

Requires Google Cloud project with Vertex AI API enabled.

Environment variables:

export GOOGLE_CLOUD_PROJECT=your-project-id
export VERTEX_LOCATION=global  # optional, defaults to global
export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json

Or authenticate with gcloud:

gcloud auth application-default login

Config example:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "google-vertex": {
      "options": {
        "baseURL": "https://global-aiplatform.googleapis.com"
      }
    }
  }
}

Tip: The global region improves availability at no extra cost. Use regional endpoints (e.g. us-central1) for data residency requirements.

Amazon Bedrock

Supports multiple authentication methods with configurable precedence.

Environment variables:

# Option 1: AWS access keys
export AWS_ACCESS_KEY_ID=XXX
export AWS_SECRET_ACCESS_KEY=YYY

# Option 2: Named AWS profile
export AWS_PROFILE=my-profile

# Option 3: Bedrock bearer token
export AWS_BEARER_TOKEN_BEDROCK=XXX

Config example:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "amazon-bedrock": {
      "options": {
        "region": "us-east-1",
        "profile": "my-aws-profile",
        "endpoint": "https://bedrock-runtime.us-east-1.vpce-xxxxx.amazonaws.com"
      }
    }
  }
}

Available options:

  • region — AWS region (e.g. us-east-1, eu-west-1)
  • profile — Named profile from ~/.aws/credentials
  • endpoint — Custom endpoint URL for VPC endpoints (alias for baseURL)

Authentication methods:

  • AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY — IAM user access keys
  • AWS_PROFILE — Named profiles from ~/.aws/credentials
  • AWS_BEARER_TOKEN_BEDROCK — Long-term API keys from Bedrock console
  • AWS_WEB_IDENTITY_TOKEN_FILE / AWS_ROLE_ARN — EKS IRSA / Kubernetes OIDC

Authentication precedence:

  1. Bearer Token (AWS_BEARER_TOKEN_BEDROCK or /connect token)
  2. AWS Credential Chain (profile, access keys, shared credentials, IAM roles, Web Identity, instance metadata)

Custom inference profiles:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "amazon-bedrock": {
      "models": {
        "anthropic-claude-sonnet-4.5": {
          "id": "arn:aws:bedrock:us-east-1:xxx:application-inference-profile/yyy"
        }
      }
    }
  }
}

Azure OpenAI

Requires Azure OpenAI resource and model deployment.

Setup:

  1. Create Azure OpenAI resource in Azure portal
  2. Deploy a model in Azure AI Foundry (deployment name must match model name)
  3. Run /connect, search for Azure
  4. Enter API key
  5. Set resource name:
export AZURE_RESOURCE_NAME=XXX
  1. Run /models to select deployed model

Note: If you see "I'm sorry, but I cannot assist with that request" errors, change the content filter from DefaultV2 to Default in your Azure resource.

Azure Cognitive Services uses a separate provider with AZURE_COGNITIVE_SERVICES_RESOURCE_NAME.

GitLab Duo

Requires GitLab Premium or Ultimate subscription. Supports OAuth and personal access token.

Setup:

  1. Run /connect, select GitLab
  2. Choose authentication method:
    • OAuth (Recommended): Browser opens for authorization
    • Personal Access Token: Generate at GitLab User Settings > Access Tokens (scopes: api, token starts with glpat-)
  3. Run /models to select model

Available models:

  • duo-chat-haiku-4-5 (default) — Fast responses
  • duo-chat-sonnet-4-5 — Balanced performance
  • duo-chat-opus-4-5 — Most capable

Self-hosted GitLab:

export GITLAB_INSTANCE_URL=https://gitlab.company.com
export GITLAB_TOKEN=glpat-...
export GITLAB_AI_GATEWAY_URL=https://ai-gateway.company.com  # optional

Compliance config (lock to self-hosted):

{
  "$schema": "https://opencode.ai/config.json",
  "small_model": "gitlab/duo-chat-haiku-4-5",
  "share": "disabled"
}

OAuth for self-hosted: Create application with callback URL http://127.0.0.1:8080/callback and scopes api, read_user, read_repository. Set GITLAB_OAUTH_CLIENT_ID env var.

GitLab API tools plugin:

{
  "$schema": "https://opencode.ai/config.json",
  "plugin": ["opencode-gitlab-plugin"]
}

Cloud Providers

Cloudflare AI Gateway

Unified endpoint for OpenAI, Anthropic, Workers AI, and more.

Setup:

  1. Create gateway in Cloudflare dashboard > AI > AI Gateway
  2. Run /connect, search for Cloudflare AI Gateway
  3. Enter Account ID, Gateway ID, and API token

Environment variables:

export CLOUDFLARE_ACCOUNT_ID=your-32-character-account-id
export CLOUDFLARE_GATEWAY_ID=your-gateway-id
export CLOUDFLARE_API_TOKEN=your-api-token

Config:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "cloudflare-ai-gateway": {
      "models": {
        "openai/gpt-4o": {},
        "anthropic/claude-sonnet-4": {}
      }
    }
  }
}

Cloudflare Workers AI

Run AI models on Cloudflare's global network via REST API.

Environment variables:

export CLOUDFLARE_ACCOUNT_ID=your-32-character-account-id
export CLOUDFLARE_API_KEY=your-api-token

DigitalOcean

Supports OAuth (recommended) and Model Access Keys. Inference Routers route requests to optimal models.

OAuth (recommended):

  1. Run /connect, select DigitalOcean, choose Login with DigitalOcean
  2. Authorize in browser
  3. Inference Routers appear as router:<name> in model picker

Model Access Key:

export DIGITALOCEAN_ACCESS_TOKEN=your-model-access-key

Note: Inference Routers are only auto-discovered with OAuth, not with Model Access Keys.

Vercel AI Gateway

Unified endpoint for OpenAI, Anthropic, Google, xAI, and more. Models at list price.

Setup:

  1. Create API key in Vercel dashboard > AI Gateway tab
  2. Run /connect, search for Vercel AI Gateway
  3. Enter API key

Routing options:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "vercel": {
      "models": {
        "anthropic/claude-sonnet-4": {
          "options": {
            "order": ["anthropic", "vertex"],
            "only": ["anthropic"],
            "zeroDataRetention": false
          }
        }
      }
    }
  }
}

SAP AI Core

Access 40+ models from OpenAI, Anthropic, Google, Amazon, Meta, Mistral, and AI21.

Setup:

  1. Create service key in SAP BTP Cockpit
  2. Run /connect, search for SAP AI Core
  3. Enter service key JSON

Environment variables:

export AICORE_SERVICE_KEY='{"clientid":"...","clientsecret":"...","url":"...","serviceurls":{"AI_API_URL":"..."}}'
export AICORE_DEPLOYMENT_ID=your-deployment-id  # optional
export AICORE_RESOURCE_GROUP=your-resource-group  # optional

AI Platform Providers

OpenRouter

Multi-provider gateway with many preloaded models.

Setup:

  1. Create API key at openrouter.ai/settings/keys
  2. Run /connect, search for OpenRouter
  3. Enter API key

Config — add models and provider routing:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "openrouter": {
      "models": {
        "moonshotai/kimi-k2": {
          "options": {
            "provider": {
              "order": ["baseten"],
              "allow_fallbacks": false
            }
          }
        }
      }
    }
  }
}

Together AI

  1. Create account at api.together.ai, click Add Key
  2. Run /connect, search for Together AI, enter key
  3. Run /models to select

Fireworks AI

  1. Create account at app.fireworks.ai, click Create API Key
  2. Run /connect, search for Fireworks AI, enter key
  3. Run /models to select

Groq

  1. Create account at console.groq.com, click Create API Key
  2. Run /connect, search for Groq, enter key
  3. Run /models to select

Cerebras

  1. Create account at inference.cerebras.ai, generate API key
  2. Run /connect, search for Cerebras, enter key
  3. Run /models to select (e.g. Qwen 3 Coder 480B)

DeepSeek

  1. Create account at platform.deepseek.com, create API key
  2. Run /connect, search for DeepSeek, enter key
  3. Run /models to select (e.g. DeepSeek V4 Pro)

Hugging Face

Inference Providers access via 17+ providers.

  1. Create token at huggingface.co/settings/tokens with Inference Providers permission
  2. Run /connect, search for Hugging Face, enter token
  3. Run /models to select

NVIDIA

Free access to Nemotron and open models via build.nvidia.com.

  1. Create account at build.nvidia.com, generate API key
  2. Run /connect, search for NVIDIA, enter key
  3. Run /models to select

Environment variable:

export NVIDIA_API_KEY=nvapi-your-key-here

On-prem / NIM:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "nvidia": {
      "options": {
        "baseURL": "http://localhost:8000/v1"
      }
    }
  }
}

Nebius Token Factory

  1. Create account at tokenfactory.nebius.com, click Add Key
  2. Run /connect, search for Nebius Token Factory, enter key
  3. Run /models to select

Baseten

  1. Create account at app.baseten.co, generate API key
  2. Run /connect, search for Baseten, enter key
  3. Run /models to select

Deep Infra

  1. Create account at deepinfra.com/dash, generate API key
  2. Run /connect, search for Deep Infra, enter key
  3. Run /models to select

Venice AI

  1. Create account at venice.ai, generate API key
  2. Run /connect, search for Venice AI, enter key
  3. Run /models to select (e.g. Llama 3.3 70B)

Moonshot AI

  1. Create account at platform.moonshot.ai/console, create API key
  2. Run /connect, search for Moonshot AI, enter key
  3. Run /models to select (e.g. Kimi K2)

MiniMax

  1. Create account at platform.minimax.io/login, generate API key
  2. Run /connect, search for MiniMax, enter key
  3. Run /models to select (e.g. M2.1)

Cortecs

  1. Create account at cortecs.ai, generate API key
  2. Run /connect, search for Cortecs, enter key
  3. Run /models to select (e.g. Kimi K2 Instruct)

IO.NET

  1. Create account at ai.io.net, generate API key
  2. Run /connect, search for IO.NET, enter key
  3. Run /models to select

FrogBot

  1. Create account at app.frogbot.ai/signup, generate API key
  2. Run /connect, search for FrogBot, enter key
  3. Run /models to select

Z.AI

  1. Create account at z.ai/manage-apikey/apikey-list, create API key
  2. Run /connect, search for Z.AI
  3. If subscribed to GLM Coding Plan, select Z.AI Coding Plan
  4. Enter API key
  5. Run /models to select (e.g. GLM-4.7)

ZenMux

  1. Create API key at zenmux.ai/settings/keys
  2. Run /connect, search for ZenMux, enter key
  3. Run /models to select

LLM Gateway

  1. Create API key at llmgateway.io/dashboard
  2. Run /connect, search for LLM Gateway, enter key
  3. Run /models to select

Config example:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "llmgateway": {
      "models": {
        "glm-4.7": { "name": "GLM 4.7" },
        "gpt-5.2": { "name": "GPT 5.2" },
        "gemini-2.5-pro": { "name": "Gemini 2.5 Pro" }
      }
    }
  }
}

STACKIT

Sovereign European AI model serving (Llama, Mistral, Qwen).

  1. Create auth token in STACKIT Portal > AI Model Serving
  2. Run /connect, search for STACKIT, enter token
  3. Run /models to select

OVHcloud AI Endpoints

  1. Create API key in OVHcloud panel > Public Cloud > AI & Machine Learning > AI Endpoints
  2. Run /connect, search for OVHcloud AI Endpoints, enter key
  3. Run /models to select

Scaleway

  1. Generate API key in Scaleway Console IAM settings
  2. Run /connect, search for Scaleway, enter key
  3. Run /models to select

302.AI

  1. Create account at 302.ai, generate API key
  2. Run /connect, search for 302.AI, enter key
  3. Run /models to select

Helicone

LLM observability platform with logging, monitoring, and analytics.

  1. Create account at helicone.ai, generate API key
  2. Run /connect, search for Helicone, enter key
  3. Run /models to select

Custom config with headers:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "helicone": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Helicone",
      "options": {
        "baseURL": "https://ai-gateway.helicone.ai",
        "headers": {
          "Helicone-Cache-Enabled": "true",
          "Helicone-User-Id": "opencode"
        }
      },
      "models": {
        "gpt-4o": { "name": "GPT-4o" },
        "claude-sonnet-4-20250514": { "name": "Claude Sonnet 4" }
      }
    }
  }
}

Session tracking plugin:

npm install -g opencode-helicone-session

{ "plugin": ["opencode-helicone-session"] }

Common Helicone headers:

HeaderDescription
Helicone-Cache-EnabledEnable response caching (true/false)
Helicone-User-IdTrack metrics by user
Helicone-Property-[Name]Add custom properties
Helicone-Prompt-IdAssociate requests with prompt versions

Local Models

Ollama

Ollama can auto-configure itself for OpenCode. See the Ollama integration docs.

Manual config:

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "ollama": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Ollama (local)",
      "options": {
        "baseURL": "http://localhost:11434/v1"
      },
      "models": {
        "llama2": { "name": "Llama 2" }
      }
    }
  }
}

Tip: If tool calls aren't working, increase num_ctx in Ollama to 16k-32k.

Ollama Cloud

  1. Sign in at ollama.com, go to Settings > Keys, create API key
  2. Run /connect, search for Ollama Cloud, enter key
  3. Pull model info locally first:
ollama pull gpt-oss:20b-cloud
  1. Run /models to select cloud model

llama.cpp

Uses llama-server utility from llama.cpp.

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "llama.cpp": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "llama-server (local)",
      "options": {
        "baseURL": "http://127.0.0.1:8080/v1"
      },
      "models": {
        "qwen3-coder:a3b": {
          "name": "Qwen3-Coder: a3b-30b (local)",
          "limit": {
            "context": 128000,
            "output": 65536
          }
        }
      }
    }
  }
}

LM Studio

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "lmstudio": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "LM Studio (local)",
      "options": {
        "baseURL": "http://127.0.0.1:1234/v1"
      },
      "models": {
        "google/gemma-3n-e4b": { "name": "Gemma 3n-e4b (local)" }
      }
    }
  }
}

Atomic Chat

Desktop app that runs local LLMs behind an OpenAI-compatible API (default: http://127.0.0.1:1337/v1).

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "atomic-chat": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Atomic Chat (local)",
      "options": {
        "baseURL": "http://127.0.0.1:1337/v1"
      },
      "models": {
        "<your-model-id>": { "name": "<your-model-name>" }
      }
    }
  }
}

Tip: If tool calls aren't working, pick a model with strong tool-calling support (e.g. Qwen-Coder or DeepSeek-Coder).

Custom Provider

Add any OpenAI-compatible provider not listed in /connect:

  1. Run /connect, scroll to Other
  2. Enter a unique provider ID
  3. Enter your API key
  4. Configure in opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "myprovider": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "My AI Provider",
      "options": {
        "baseURL": "https://api.myprovider.com/v1",
        "apiKey": "{env:MY_PROVIDER_API_KEY}",
        "headers": {
          "Authorization": "Bearer custom-token"
        }
      },
      "models": {
        "my-model-name": {
          "name": "My Model Display Name",
          "limit": {
            "context": 200000,
            "output": 65536
          }
        }
      }
    }
  }
}

Configuration options:

  • npm — Use @ai-sdk/openai-compatible for /v1/chat/completions endpoints; use @ai-sdk/openai for /v1/responses endpoints
  • apiKey — Set using {env:VAR_NAME} syntax or literal value
  • headers — Custom headers sent with each request
  • limit.context — Maximum input tokens
  • limit.output — Maximum output tokens

The limit fields allow OpenCode to understand remaining context. Standard providers pull these from models.dev automatically.

Environment Variables

VariableProviderDescription
AWS_ACCESS_KEY_IDAmazon BedrockAWS access key
AWS_SECRET_ACCESS_KEYAmazon BedrockAWS secret key
AWS_PROFILEAmazon BedrockNamed AWS profile
AWS_REGIONAmazon BedrockAWS region
AWS_BEARER_TOKEN_BEDROCKAmazon BedrockLong-term Bedrock API key
AWS_WEB_IDENTITY_TOKEN_FILEAmazon BedrockEKS IRSA token file
AWS_ROLE_ARNAmazon BedrockEKS IRSA role ARN
GOOGLE_CLOUD_PROJECTGoogle Vertex AIGCP project ID
GOOGLE_APPLICATION_CREDENTIALSGoogle Vertex AIService account JSON path
VERTEX_LOCATIONGoogle Vertex AIRegion (default: global)
AZURE_RESOURCE_NAMEAzure OpenAIAzure resource name
AZURE_COGNITIVE_SERVICES_RESOURCE_NAMEAzure Cognitive ServicesResource name
NVIDIA_API_KEYNVIDIAAPI key
DIGITALOCEAN_ACCESS_TOKENDigitalOceanModel access key
GITLAB_TOKENGitLab DuoPersonal access token
GITLAB_INSTANCE_URLGitLab DuoSelf-hosted instance URL
GITLAB_AI_GATEWAY_URLGitLab DuoCustom AI Gateway URL
GITLAB_OAUTH_CLIENT_IDGitLab DuoOAuth app client ID (self-hosted)
CLOUDFLARE_ACCOUNT_IDCloudflareAccount ID
CLOUDFLARE_API_KEYCloudflare Workers AIAPI token
CLOUDFLARE_API_TOKENCloudflare AI GatewayAPI token
CLOUDFLARE_GATEWAY_IDCloudflare AI GatewayGateway ID
AICORE_SERVICE_KEYSAP AI CoreService key JSON
AICORE_DEPLOYMENT_IDSAP AI CoreDeployment ID (optional)
AICORE_RESOURCE_GROUPSAP AI CoreResource group (optional)

Troubleshooting

  1. Check auth setup: Run opencode auth list to verify credentials are stored. Does not apply to environment-variable-based providers (Amazon Bedrock, Google Vertex AI, etc.).

  2. Custom provider issues:

    • Ensure provider ID in /connect matches the ID in opencode.json
    • Verify correct npm package:
      • @ai-sdk/openai-compatible for /v1/chat/completions endpoints
      • @ai-sdk/openai for /v1/responses endpoints
      • Provider-specific packages (e.g. @ai-sdk/cerebras) when available
    • Verify options.baseURL is correct

  3. Clear provider cache: If models aren't appearing, try clearing the provider package cache and restarting.

  4. API call errors: Check API key validity, endpoint URL, and model availability with the provider directly.

  5. Local model issues: Ensure the local server (Ollama, llama.cpp, LM Studio) is running and accessible at the configured baseURL.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.