# Ax Cpp Agent 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.

- Skill: `ax-llm/ax-cpp-agent-observability` (Agent Skill)
- Install (CLI): `npx skillmds@latest add ax-llm/ax-cpp-agent-observability`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ax-llm/ax-cpp-agent-observability/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: ax-llm (https://skillmd.com/u/ax-llm)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/ax-llm/ax-cpp-agent-observability

---

# 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

```cpp
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.

```cpp
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::AxCancellationToken`, `axllm::AxAIServiceAbortedError`, `axllm::get_supported_ai_models`, `axllm::AxCredentialRequest`, `axllm::AxCredentialProvider`, `axllm::AIClient::owned_worker_factory`, `axllm::AxChatSession`, `axllm::AxStreamHandler`, `axllm::OpenAICompatibleClient`, `axllm::OpenAIResponsesClient`, `axllm::GoogleGeminiClient`, `axllm::AnthropicClient`, `axllm::AxUsageContext`, `axllm::AxUsageEvent`, `axllm::AxUsageObserver`, `axllm::set_usage_observer`, `axllm::AxRuntimeHooks`, `axllm::AxRateLimitInfo`, `axllm::AxRateLimiter`, `axllm::AxTracer`, `axllm::AxMeter`, `axllm::AxGlobals`, `axllm::set_rate_limiter`, `axllm::set_tracer`, `axllm::set_meter`, `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`, `axllm::AxAgent::add_child_agent`
- 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.