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name: Model Manager description: Test, validate, and add new AI models to the eval suite. Use when user asks to add new models, test model access, check pricing, or update models.yml.

Model Manager

Test API access, validate configurations, and add new AI models to the AILANG eval suite.

Quick Start

Most common usage:

# User says: "Can we add GPT-5.1 to the eval suite?"
# This skill will:
# 1. Test API access to GPT-5.1
# 2. Find the correct API model name
# 3. Look up pricing information
# 4. Update models.yml configuration
# 5. Run a test benchmark to verify

When to Use This Skill

Invoke this skill when:

• User asks to "add a new model" to eval suite
• User mentions checking if a model is "accessible" or "available"
• User wants to "test API access" to a model
• User asks to "update models.yml" or "check pricing"
• User says "can we use [model name]?" for evaluations

Available Scripts

scripts/test_model_access.sh <provider> <model-name>

Test API access to a model and display authentication status.

Usage:

# Test OpenAI model
scripts/test_model_access.sh openai gpt-5.1

# Test Anthropic model
scripts/test_model_access.sh anthropic claude-sonnet-4-5-20250929

# Test Google Gemini via Vertex AI
scripts/test_model_access.sh google gemini-3-pro-preview-11-2025

Output:

Testing: openai/gpt-5.1
✓ OPENAI_API_KEY found
✓ API call successful
✓ Model: gpt-5.1-2025-11-13
✓ Tokens: 13 input, 10 output (10 reasoning)
Ready to add to models.yml

scripts/find_model_info.sh <model-keywords>

Search for model information using web search and return API names + pricing.

Usage:

# Find GPT-5.1 info
scripts/find_model_info.sh "GPT-5.1 API model name pricing"

# Find Gemini 3 Pro info
scripts/find_model_info.sh "Gemini 3 Pro API documentation"

Output:

Searching for: GPT-5.1 API model name pricing
✓ Found API names:
  - gpt-5.1 (Thinking mode)
  - gpt-5.1-chat-latest (Instant mode)
✓ Pricing:
  Input: $1.25 per 1M tokens
  Output: $10.00 per 1M tokens
  Cached: $0.125 per 1M tokens

scripts/update_models_yml.sh <friendly-name> <api-name> <provider> <input-price> <output-price>

Add a new model to models.yml configuration.

Usage:

# Add GPT-5.1
scripts/update_models_yml.sh \
  gpt5-1 \
  "gpt-5.1" \
  openai \
  0.00125 \
  0.01

Output:

Adding model to models.yml:
  Friendly name: gpt5-1
  API name: gpt-5.1
  Provider: openai
  Pricing: $0.00125 / $0.01 per 1K tokens

✓ Updated models.yml
✓ Validated YAML syntax
✓ Ready to test

scripts/verify_vertex_model.sh <model-name>

Check if a Gemini model is available in Vertex AI.

Usage:

# Check if Gemini 3 Pro is available
scripts/verify_vertex_model.sh gemini-3-pro-preview-11-2025

Output:

Checking Vertex AI for: gemini-3-pro-preview-11-2025
✓ GCP project: multivac-internal-prod
✓ Access token obtained
✗ Model not found (404)
Recommendation: Monitor for availability, check again in 1-2 weeks

scripts/run_test_benchmark.sh <model-name>

Run a small test benchmark to verify model works end-to-end.

Usage:

# Test GPT-5.1 with fizzbuzz benchmark
scripts/run_test_benchmark.sh gpt5-1

Output:

Running test benchmark: fizzbuzz
Model: gpt5-1
✓ Benchmark completed
✓ Result: PASS (100%)
✓ Tokens: 245 input, 89 output
✓ Cost: $0.002
Model is ready for production use

Workflow

1. Test API Access

First, verify you can call the model:

# Use test_model_access.sh
scripts/test_model_access.sh openai gpt-5.1

What to check:

• API key is set (OPENAI_API_KEY, ANTHROPIC_API_KEY, or gcloud auth)
• API call succeeds (not 401/403/404)
• Model returns expected structure
• Token usage is reported

For Gemini models:

• Uses Vertex AI (not public API)
• Requires gcloud auth application-default login
• Check availability with verify_vertex_model.sh

2. Find Model Information

Search for official documentation:

# Find API model name and pricing
scripts/find_model_info.sh "GPT-5.1 API documentation pricing"

What to gather:

• Exact API model name (e.g., gpt-5.1 not GPT-5.1)
• Provider (openai, anthropic, google)
• Input price per 1K tokens
• Output price per 1K tokens
• Context limits (if relevant)
• Special features (adaptive reasoning, caching, etc.)

Reference: See resources/provider_endpoints.md

3. Update models.yml

Add the model configuration:

# Add to models.yml
scripts/update_models_yml.sh \
  <friendly-name> \
  <api-name> \
  <provider> \
  <input-per-1k> \
  <output-per-1k>

Naming conventions:

• Friendly name: gpt5-1, claude-sonnet-4-5, gemini-3-pro
• API name: Exact string for API calls
• Use hyphens, lowercase

Also update:

• Model suites (benchmark_suite, extended_suite, dev_models)
• Add notes about special features
• Document agent CLI support (if available)

4. Run Test Benchmark

Verify end-to-end:

# Test with a simple benchmark
scripts/run_test_benchmark.sh <model-name>

What to verify:

• Benchmark completes successfully
• Results are reasonable (not garbage output)
• Token usage matches expectations
• Cost calculation works
• No errors in logs

5. Document the Model

Update relevant documentation:

• Add model to this skill's resource guide
• Note any special parameters (e.g., max_completion_tokens for GPT-5.1)
• Document authentication requirements
• Add to teaching prompts if needed

6. Optional: Run Full Eval

If model looks good:

# Run small eval suite
ailang eval-suite --models <model-name> --benchmarks fizzbuzz,recursion_factorial

# Run full suite (expensive!)
make eval-baseline EVAL_VERSION=vX.Y.Z FULL=true

Resources

Provider Endpoints

See resources/provider_endpoints.md for:

• API endpoint URLs for each provider
• Authentication methods
• How to test access manually
• Common errors and fixes

Pricing Guide

See resources/pricing_guide.md for:

• How to find official pricing
• Price conversion (per 1M → per 1K)
• Cost calculation verification
• Caching and discounts

Progressive Disclosure

This skill loads information progressively:

1. Always loaded: This SKILL.md file (workflow and script descriptions)
2. Execute as needed: Scripts in scripts/ (testing, updating, verification)
3. Load on demand: Resources (detailed endpoint docs, pricing references)

Notes

Important:

• Always test API access BEFORE updating models.yml
• Vertex AI (Gemini) requires gcloud auth, not API key
• GPT-5.1+ uses max_completion_tokens instead of max_tokens
• New models may not be available in all regions immediately
• Check for preview/beta status before adding to production suites

Prerequisites:

• API keys set in environment (OPENAI_API_KEY, ANTHROPIC_API_KEY)
• For Gemini: gcloud CLI installed and authenticated
• For Gemini: GCP project set (gcloud config set project PROJECT_ID)
• curl, python3, and jq available in PATH

Files modified by this skill:

• internal/eval_harness/models.yml - Model configurations
• (Optional) prompts/vX.Y.Z.md - Teaching prompts
• (Optional) .claude/skills/model-manager/resources/ - Local model database