Observability Use when writing C++ code with `axllm` for agent tracing, centralized and multi-tenant usage accounting, action logs, runtime diagnostics, replay, and production debugging. cpp skills skill-agent-observability packages/cpp/skills/ax-cpp-agent-observability/SKILL.md skill Observability

AxAgent Observability For C++

Use when writing C++ code with axllm for agent tracing, centralized and multi-tenant usage accounting, action logs, runtime diagnostics, replay, and production debugging.

Install

Install only this skill for C++:

Shell
npx skills add https://ax-llm.github.io/ax/cpp/ --skill 'ax-cpp-agent-observability'

Published skill file: ax-cpp-agent-observability/SKILL.md.

Source

Skill Instructions

This skill helps an agent write C++ code with the generated Ax package axllm. Use the generated package API, examples, and manifests; do not import TypeScript-only APIs unless you are editing the TypeScript package.

When To Use

  • Inspect agent traces, runtime envelopes, usage, or action logs.
  • Register the process-wide usage observer and attribute model calls by tenant, user, request, run, or feature.
  • Attach callbacks for model/tool activity and runtime progress.
  • Debug agent loops through generated package state and examples.

Package Facts

  • Language: C++.
  • Package: axllm.
  • Package API docs: API.md and axir-api.json.
  • Capability manifest: axir-capabilities.json.
  • Runnable examples: examples/.
  • Real network support: yes.
  • Scripted no-key transport support: yes.
  • Runtime profiles: javascript-quickjs, python-pyodide.

Core Pattern

C++
auto helper = axllm::agent("question:string -> answer:string");
auto out = helper.forward(llm, { {"question", "How should I proceed?"} });

Centralized Usage Observer

Use the process-wide usage observer for application accounting across many agents, API routes, tenants, and users. Keep per-agent usage accessors for inspecting one agent instance after a run.

C++
axllm::set_usage_observer(
    [&usage_queue](axllm::AxUsageEvent event) {
      usage_queue.push(std::move(event));
    });
// Later: axllm::set_usage_observer({});
  • The observer receives one normalized event for each completed chat or embedding call that reports provider usage. A fully consumed stream emits once; an unconsumed or cancelled stream may not emit.
  • Events include the operation, AI/provider name, model, normalized tokens, streaming flag, optional usage context, and available session or remote request IDs.
  • Attach usageContext in AI service options for stable application or environment defaults. Attach it in call or agent-forward option maps for tenant, user, request, run, and feature attribution.
  • Per-call context overrides service defaults. Nested attributes are shallow-merged.
  • The observer is process-wide, best-effort, and fail-open. Registering again replaces the previous observer. Clear it during test teardown or shutdown when appropriate.
  • The observer runs on the request path. Production callbacks should synchronously enqueue into a bounded concurrent queue and return immediately, then persist or aggregate out of band. Use a shared durable pipeline across processes or serverless instances.
  • Keep identifiers opaque and attributes low-cardinality. Do not attach prompts, responses, secrets, or other sensitive payloads.
  • Calculate currency cost downstream against a versioned provider/model pricing table.
  • Runnable provider example: src/examples/cpp/generation/usage_observer.cpp.

Relevant API Surface

  • AxAI: axllm::ai, axllm::OpenAICompatibleClient, axllm::OpenAIResponsesClient, axllm::GoogleGeminiClient, axllm::AnthropicClient, axllm::AxUsageContext, axllm::AxUsageEvent, axllm::AxUsageObserver, axllm::set_usage_observer, axllm::AxBalancer, axllm::AxBalancerAdaptiveStrategy, axllm::AxBalancerStatsStore, axllm::AxInMemoryBalancerStatsStore, axllm::create_balancer_route_stats, axllm::update_balancer_route_stats, axllm::sample_balancer_route_health, axllm::MultiServiceRouter, axllm::ProviderRouter
  • Agents And RLM: axllm::agent, axllm::AxAgent
  • Runtime Profiles: axllm::ProcessCodeRuntime, axllm::RuntimeCapabilities, axllm::RuntimeEnvelope, javascript-quickjs, python-pyodide

Guardrails

  • Start from package examples for exact native syntax before inventing a new call shape.
  • Use provider-api examples only when the user explicitly has provider credentials available.
  • Use no-key examples for deterministic local checks and provider request mapping.
  • Treat AxIR as the source of generated package truth: if package docs disagree with source code, update the compiler and regenerate packages.
  • Do not copy repo-maintainer skills from tools/*/skills/ into user packages.
Docs