ax-cpp-agent-observability

name	ax-cpp-agent-observability
description	Use when writing C++ code with `axllm` for agent tracing, centralized and multi-tenant usage accounting, action logs, runtime diagnostics, replay, and production debugging.
version	23.0.14

AxAgent Observability For C++

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

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.

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::DeepSeekResponsesClient, 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.