About model-researcher
A model research skill for OpenCode users adding custom models to opencode.json. It verifies identifiers, token limits, and provider requirements, then requires user confirmation before configuration and rejects listed legacy models.
Key features
- 01Research model specifications from authoritative sources
- 02Verify API identifiers and token limits
- 03Identify provider and special configuration needs
- 04Present findings for confirmation before changes
- 05Add models to opencode.json
- 06Provide post-configuration validation steps
Use cases
- 01Add a newly released model not listed in models.dev
- 02Configure a model from a self-hosted or proxy provider
- 03Prepare settings for non-default model options
- 04Verify model details before updating configuration
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ igorwarzocha/ opencode-workflows --skill model-researcherAfter installing, type/model-researcherin Claude Code to confirm it loaded.
Bundled filesreferences/provider-patterns.md
Details
From the project READMEModel Researcher
Add new or custom AI models to opencode.json with verified specifications.
<critical_prohibition>
EXTREMELY STRICT: Banned Legacy Models
The following models MUST NOT be used in any configuration as they are DEPRECATED, REPLACED, or OBSOLETE in the current Q4 2025 market:
- OpenAI: GPT-o series (
o1-mini,o1-preview), GPT-4o, GPT-4 Turbo. - Anthropic: Claude 3.5 series (
sonnet-3.5, etc.), Claude 3 series. - Google: Gemini 1.5 series, Gemini 2 series.
- Meta: Llama 3 series.
The market has moved to GPT-5.2, Claude 4.5, and Gemini 3. Any attempt to configure these models MUST be rejected. </critical_prohibition>
<when_to_use>
- Model is too new for models.dev
- Non-standard or custom provider (self-hosted, proxy, enterprise)
- User heard about a new release and wants to use it immediately
- Model exists but with non-default configuration needs
</when_to_use>
<question_tool>
Batching: Use the question tool for 2+ related questions. Single questions → plain text.
Syntax: header ≤12 chars, label 1-5 words, add "(Recommended)" to default.
When to ask: Vague model reference, multiple providers available, or specs unverified.
Critical: MUST confirm specs with user before applying model configuration.
</question_tool>
<critical_rule>
Verify Before Configure
MUST NOT hallucinate model specifications. Models have precise identifiers, context limits, and API requirements. A wrong value means broken requests or wasted tokens.
Before ANY configuration:
- Confirm the model actually exists
- Find the exact model identifier (API name, not marketing name)
- Get verified context and output token limits
- Identify required provider configuration
</critical_rule>
Step 1: Clarify What the User Wants
Ask if unclear:
- "Which provider will you access this through?" (direct API, OpenRouter, Together, self-hosted, etc.)
- "Do you have API access already, or do you need setup help?"
Step 2: Research the Model
Use web search to find authoritative sources:
websearch("${MODEL_NAME} API context limit tokens official documentation")
websearch("${MODEL_NAME} model ID API identifier ${PROVIDER}")
Priority sources (most to least trustworthy):
- Official provider documentation/blog posts
- Provider's API reference or changelog
- Official GitHub repos or release notes
- OpenRouter/Together model pages (they list specs)
- Reputable tech news (for very new announcements)
Red flags - search more if you only find:
- Reddit speculation
- Tweets without official confirmation
- Your own training data (MAY be outdated)
Step 3: Confirm Findings with User
Before touching config, MUST present your research:
I found the following for [MODEL]:
Provider: OpenAI
Model ID: gpt-5.2-2025-12-11
Context limit: 400000 tokens (Direct) | 272000 tokens (OAuth)
Output limit: 128000 tokens
Special options: [e.g., reasoning modes, vision support]
Source: [URL]
Does this match what you expected? Should I add this to your config?
MUST NOT proceed without user confirmation.
Step 4: Apply Configuration
Read the current config first:
read ~/.config/opencode/opencode.json
Then apply using surgical edits. Choose the right pattern:
Pattern A: GPT-5.2 (OpenAI)
OpenAI GPT-5.2 supports specialized reasoning modes via variants (Cycle with ctrl+t). Note that models configured via OAuth plugins (e.g., opencode-openai-codex-auth) often have different enforced limits.
{
"provider": {
"openai": {
"models": {
"gpt-5.2": {
"limit": { "context": 400000, "output": 128000 }, // Use 272000 for OAuth
"variants": {
"pro": {
"reasoningEffort": "xhigh",
"reasoningSummary": "detailed",
},
"thinking": { "reasoningEffort": "high" },
"instant": { "reasoningEffort": "low", "textVerbosity": "low" },
},
},
"gpt-5.2-codex": {
"limit": { "context": 400000, "output": 128000 }, // Use 272000 for OAuth
},
},
},
},
}
Pattern B: Other Labs (DeepSeek, Zhipu, MiniMax, Moonshot)
For labs using OpenAI-compatible or Anthropic-compatible endpoints (Verified Q4 2025):
{
"provider": {
"deepseek": {
"npm": "@ai-sdk/openai-compatible",
"name": "DeepSeek",
"options": { "baseURL": "https://api.deepseek.com" },
"models": {
"deepseek-v3.2": { "limit": { "context": 128000, "output": 32768 } },
},
},
"zhipu": {
"npm": "@ai-sdk/openai-compatible",
"name": "Zhipu AI (ZAI)",
"options": { "baseURL": "https://api.z.ai/api/paas/v4" },
"models": {
"glm-4.7": { "limit": { "context": 200000, "output": 128000 } },
},
},
"minimax": {
"npm": "@ai-sdk/openai-compatible",
"name": "MiniMax",
"options": { "baseURL": "https://api.minimax.chat/v1" },
"models": {
"minimax-m2.1": { "limit": { "context": 204800, "output": 128000 } },
},
},
"moonshot": {
"npm": "@ai-sdk/openai-compatible",
"name": "Moonshot AI (Kimi)",
"options": { "baseURL": "https://api.moonshot.cn/v1" },
"models": {
"kimi-k2-thinking": { "limit": { "context": 256000, "output": 64000 } },
},
},
},
}
Pattern C: Claude 4.5 Opus (Extended Thinking)
For models that need specific options like Anthropic's extended thinking:
{
"provider": {
"anthropic": {
"models": {
"claude-4-5-opus-thinking": {
"id": "claude-4-5-opus-20251124",
"name": "Claude 4.5 Opus (Extended Thinking)",
"options": {
"thinking": {
"type": "enabled",
"budgetTokens": 32000,
},
},
},
},
},
},
}
Step 5: Validate
After editing, remind user to test:
Config updated. To verify it works:
1. Restart OpenCode or run: opencode
2. Run /models and select [model name]
3. Send a test message
If you see errors, check:
- API key is set (run /connect if needed)
- Model ID matches provider's documentation exactly
- Context limits aren't higher than the model actually supports
<research_queries>
| Scenario | Search Query |
|---|---|
| New OpenAI model | "gpt-5.2" site:openai.com OR site:platform.openai.com |
| New Anthropic model | "claude-4.5" site:anthropic.com API |
| New Google model | "gemini 3" site:ai.google.dev context window |
| OpenRouter availability | "${MODEL}" site:openrouter.ai |
| Together AI availability | "${MODEL}" site:together.ai |
| Self-hosted specs | "${MODEL}" context length output tokens huggingface |
</research_queries>
<spec_checklist>
Before configuring, ensure you have:
- Model ID: Exact API identifier (not marketing name)
- Context limit: Maximum input tokens
- Output limit: Maximum output/completion tokens
- Provider: Which service hosts it
- Base URL: For custom providers only
- Special options: Vision, reasoning modes, thinking budgets
- Availability: Is it actually accessible (not waitlist-only)?
</spec_checklist>
<handling_uncertainty>
If you cannot verify specifications:
- Be honest: "I couldn't find official documentation for the exact context limit."
- Provide best guess with source: "Based on [source], it appears to be 128k, but this isn't confirmed."
- Suggest conservative defaults: "I'll configure with 100k context as a safe starting point. You can increase it once you confirm the actual limit."
- Recommend checking: "Try the provider's /models endpoint or documentation for exact specs."
</handling_uncertainty>
References
references/provider-patterns.md- Common provider configuration examples