slug: osmapi
provider: osmAPI
generated_by: planning/capability-mapping/scripts/classify_capabilities.py
model: claude-opus-5
frame:
- Software & Technology
min_confidence: 0.7
capability_model:
  source: https://github.com/vincentmakes/turbo-ea-capabilities
  license: CC-BY-4.0
  attribution: Turbo EA Capabilities by Vincent Verdet — Turbo EA, https://github.com/vincentmakes/turbo-ea-capabilities,
    CC BY 4.0
  notice: NOTICE
edge_count: 2
edges:
- tag: Chat
  spec_file: osmapi-chat-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.75
  evidence: OpenAI-compatible chat completions endpoint routed through osmAPI's unified AI gateway ...
    smart routing across OpenAI, Anthropic, Google, and 14+ LLM providers
  reason: The operation invokes large-language-model inference (createChatCompletion) through an AI gateway.
    For a buyer this realises AI/ML capability operation — Artificial Intelligence Management — rather
    than any customer-service or messaging capability; 'Chat' here is LLM completion, not a conversational
    support channel. Confidence held at 0.75 because the capability definition emphasises model lifecycle/MLOps
    while this surface is inference serving.
- tag: Messages
  spec_file: osmapi-messages-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.7
  evidence: Anthropic-compatible messages endpoint routed through osmAPI's unified AI gateway. Supports
    the native Anthropic message format including system prompts, extended thinking, tool use, and streaming.
  reason: Despite the business-sounding tag, 'Messages' is the Anthropic LLM request format (MessageRequest/MessageResponse)
    — model inference, not corporate or customer communications. Maps to Artificial Intelligence Management;
    0.7 given it is inference serving rather than model lifecycle governance.