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Affichage de 40 skills collectés sur 180.
Use when writing C++ code with `axllm` for deciding between context maps, trajectory context policy, offline optimization (ACE/GEPA), and memory recall for long-context agents.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for agent memory, recall callbacks, dynamic skill discovery, loaded-skill state, and used-skill tracking.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for agent tracing, centralized and multi-tenant usage accounting, action logs, runtime diagnostics, replay, and production debugging.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for agent optimization, verified agent-playbook evolution, evaluators, judges, optimizer artifacts, BootstrapFewShot, and GEPA.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for RLM executor loops, AxCodeRuntime sessions, runtime envelopes, process runtimes, and optional runtime profiles.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for agents, child delegation, tools, MCP, citations, persistent playbook learning, stage instructions, runtime state, final typed responses, and direct-respond executor skipping.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for named deployment profiles, generic provider clients, model selection, OpenAI-compatible calls, Responses, Gemini, Anthropic, routers, and balancers.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for audio input/output, OpenAI Responses audio mapping, realtime event folding, and generated package audio examples.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for flows, nodes, program graphs, nested programs, dynamic options, caching, and optimizer components.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for AxGen programs, forward calls, indexed multi-sampling, result pickers, streaming, tools, assertions, traces, usage, and output parsing.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for GEPA, Pareto tradeoffs, reflection clients, metric budgets, optimizer state, and artifacts.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for using the generated Ax package, factory functions, package docs, examples, and API reference.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for the playbook() context-engineering surface, agent-bound verified evolution, run-end learning, online updates, and rendering a playbook into a program.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for reward-scored generation, iterative candidate improvement, evaluator feedback, and optimizer-backed refinement patterns.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for string signatures, field descriptors, JSON schema output, validation, and typed tool argument shapes.
Langue du texte source : anglais
Use when writing C++ code with `axllm` for Typesafe Jev boolean/class/rubric score signatures, decision evidence and provenance, value descriptions, configurable Noul conversion, native Noul/Choice/Score, structured criteria and hybrid generation.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for deciding between context maps, trajectory context policy, offline optimization (ACE/GEPA), and memory recall for long-context agents.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for agent memory, recall callbacks, dynamic skill discovery, loaded-skill state, and used-skill tracking.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for agent tracing, centralized and multi-tenant usage accounting, action logs, runtime diagnostics, replay, and production debugging.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for agent optimization, verified agent-playbook evolution, evaluators, judges, optimizer artifacts, BootstrapFewShot, and GEPA.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for RLM executor loops, AxCodeRuntime sessions, runtime envelopes, process runtimes, and optional runtime profiles.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for agents, child delegation, tools, MCP, citations, persistent playbook learning, stage instructions, runtime state, final typed responses, and direct-respond executor skipping.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for named deployment profiles, generic provider clients, model selection, OpenAI-compatible calls, Responses, Gemini, Anthropic, routers, and balancers.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for audio input/output, OpenAI Responses audio mapping, realtime event folding, and generated package audio examples.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for flows, nodes, program graphs, nested programs, dynamic options, caching, and optimizer components.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for AxGen programs, forward calls, indexed multi-sampling, result pickers, streaming, tools, assertions, traces, usage, and output parsing.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for GEPA, Pareto tradeoffs, reflection clients, metric budgets, optimizer state, and artifacts.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for using the generated Ax package, factory functions, package docs, examples, and API reference.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for the playbook() context-engineering surface, agent-bound verified evolution, run-end learning, online updates, and rendering a playbook into a program.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for reward-scored generation, iterative candidate improvement, evaluator feedback, and optimizer-backed refinement patterns.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for string signatures, field descriptors, JSON schema output, validation, and typed tool argument shapes.
Langue du texte source : anglais
Use when writing Go code with `github.com/ax-llm/ax/packages/go` for Typesafe Jev boolean/class/rubric score signatures, decision evidence and provenance, value descriptions, configurable Noul conversion, native Noul/Choice/Score, structured criteria and…
Langue du texte source : anglais
Use when writing Java code with `dev.axllm:ax` for deciding between context maps, trajectory context policy, offline optimization (ACE/GEPA), and memory recall for long-context agents.
Langue du texte source : anglais
Use when writing Java code with `dev.axllm:ax` for agent memory, recall callbacks, dynamic skill discovery, loaded-skill state, and used-skill tracking.
Langue du texte source : anglais
Use when writing Java code with `dev.axllm:ax` for agent tracing, centralized and multi-tenant usage accounting, action logs, runtime diagnostics, replay, and production debugging.
Langue du texte source : anglais
Use when writing Java code with `dev.axllm:ax` for agent optimization, verified agent-playbook evolution, evaluators, judges, optimizer artifacts, BootstrapFewShot, and GEPA.
Langue du texte source : anglais
Use when writing Java code with `dev.axllm:ax` for RLM executor loops, AxCodeRuntime sessions, runtime envelopes, process runtimes, and optional runtime profiles.
Langue du texte source : anglais
Use when writing Java code with `dev.axllm:ax` for agents, child delegation, tools, MCP, citations, persistent playbook learning, stage instructions, runtime state, final typed responses, and direct-respond executor skipping.
Langue du texte source : anglais
Use when writing Java code with `dev.axllm:ax` for named deployment profiles, generic provider clients, model selection, OpenAI-compatible calls, Responses, Gemini, Anthropic, routers, and balancers.
Langue du texte source : anglais
Use when writing Java code with `dev.axllm:ax` for audio input/output, OpenAI Responses audio mapping, realtime event folding, and generated package audio examples.
Langue du texte source : anglais
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