Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ax-llm/ax/ax-cpp-flownpx skills add ax-llm/ax --skill ax-cpp-flowgit clone --depth 1 https://github.com/ax-llm/axWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00037 | $0.01208 |
| Opus 5 | $0.00018 | $0.00604 |
| Sonnet 5 | $0.00007 | $0.00242 |
| Haiku 4.5 | $0.00004 | $0.00121 |
Grade A, and why
ax-cpp-flow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- ax-python-flow — 86% identical, 85 lines differ
- ax-java-flow — 81% identical, 79 lines differ
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AxFlow 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
- Compose generators, agents, and nested flows into a workflow graph.
- Reason about flow state, node inputs, returns, caching, and errors.
- Use generated package examples for flow graphs and provider-backed flows.
Package Facts
- Language: C++.
- Package:
axllm. - Package API docs:
API.mdandaxir-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 draft = axllm::ax("topicText:string -> draftText:string");
auto wf = axllm::flow(axllm::object({{"id", "docs.coreFlow"}}))
.execute("draft", draft, axllm::object({
{"reads", axllm::array({"topicText"})},
{"writes", axllm::array({"draftResult", "draftText"})}
}))
.returns(axllm::object({{"draftText", "draftText"}}));
More Patterns
Typed programs
Build each flow node from its own input/output contract.
auto classifier = axllm::ax("requestText:string -> route:class \"support, sales, engineering\"");
auto responder = axllm::ax("requestText:string, route:string -> responseText:string");
Class decision
Declare reads and writes so the responder waits for the typed route.
auto branch_flow = axllm::flow(axllm::object({{"id", "docs.branchFlow"}}))
.execute("classifier", classifier, axllm::object({{"reads", axllm::array({"requestText"})}, {"writes", axllm::array({"classifierResult", "route"})}}))
.execute("responder", responder, axllm::object({{"reads", axllm::array({"requestText", "route"})}, {"writes", axllm::array({"responderResult", "responseText"})}}))
.returns(axllm::object({{"route", "route"}, {"responseText", "responseText"}}));
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today Changed dd55674f0262
- 2d ago First seen · 107 lines · 37 tokens per session scan A f699dcd51415
ax-cpp-flow is a skill published in the GitHub repository ax-llm/ax (2,890 stars, last pushed yesterday), licensed Apache-2.0. It adds 37 tokens to every session and 1,208 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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