slug: humanloop
provider: Humanloop
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: Prompts
  spec_file: humanloop-prompts-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.78
  evidence: POST /prompts/call "Call a Prompt (invoke the underlying model and log the result)"; "Create
    or upsert Prompt"; "Log a Prompt call"
  reason: Versioned prompt assets plus model invocation and logging are the core artefacts of LLM application
    lifecycle management, i.e. AI/ML model lifecycle and MLOps. No other candidate covers prompt engineering.
- tag: Evaluators
  spec_file: humanloop-evaluators-api-openapi.yml
  capability_id: BC-610.60
  capability_id_l1: BC-610
  capability_name: Artificial Intelligence Management
  confidence: 0.72
  evidence: List Evaluators / Upsert Evaluator / Get Evaluator; vendor offers "evaluation runs (LLM-as-judge
    and code-based), online evaluators"
  reason: Evaluators are LLM-as-judge / code evaluation artefacts governing model output quality — squarely
    AI/ML model lifecycle and responsible-AI tooling. Maps to Artificial Intelligence Management.