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SkillsMP has collected 16 skills from NVIDIA-NeMo/labs-OO-Agents. Open a skill to review its source and details.
Showing 16 of 16 collected skills.
How to manage context blocks (system prompt sections) in NOOA. Use when configuring what appears in an agent's LLM prompt — adding, overriding, suppressing, or positioning blocks. Covers the unified Context API, well-known framework keys, and the…
Author agents with NVIDIA-labs Object Oriented Agents (NOOA). Use when writing or modifying an Agent subclass, agentic methods (ellipsis bodies), docstring prompts, structured output contracts, strategy selection (CodeAct/Predict), visibility control,…
Make NOOA agent types render useful documentation for the LLM — doc(), spec(), hidden, Annotated field descriptions, and pformat/pprint tuning. Use when designing Pydantic models/dataclasses the LLM will see, controlling what appears in doc(self), hiding…
Capture execution traces from NOOA. Use when instrumenting an agent run, writing traces to JSONL files, sending traces to the viewer or an OTLP/Langfuse/Phoenix backend, controlling which methods are traced, or when traces are mysteriously missing.
Reactive input for NOOA agents — Channel/QueueManager for queued and event-mode input, race() turn dispatch, spawn() background jobs with JobHandle, and the bundled producers (monitor a shell command, cron ticks, one-shot timers, file tails). Use when an…
Advanced tuning of NOOA strategies — CodeAct prefill (understanding, disabling, custom, pre-ellipsis code), loop guards (max_iterations, retries, text-only stop), truncation tuning (TruncationConfig/CaptureConfig/FormatConfig), code restrictions…
Manage what a NOOA agent sees and remembers — context blocks, event history and queries, history summarization, and persistent memory/storage. Use when pinning information into the system prompt, querying past events, bounding context growth in long…
Intercept and observe NOOA execution — middleware via event_manager.intercept() (guardrails, input/output transforms, blocking), event observers via event_manager.on() (react to Task/Error/LLMComplete/turn events), and the InstrumentationHooks protocol for…
Let NOOA agents extend themselves — persistent skill libraries the agent writes and hot-reloads (SkillWriting / self.libs, LibraryManager), in-cell helper functions and standalone @strategy sub-calls (MethodWriting), and @slash_command user actions. Use when…
Give a NOOA agent capabilities — methods as tools, built-in tools (ShellTools, TodoManager), MCP servers, agent skills (Skill/TextSkill/SkillRegistry), and multimodal media. Use when adding tools or external integrations to an agent, wiring MCP, or packaging…
Analyze NOOA execution traces programmatically with the trace-explorer CLI and Python API. Use when debugging why an agent run failed, inspecting LLM turns and code executions, diffing two runs, aggregating errors across an eval experiment, or root-causing…
Run and use the NOOA trace viewer — the web UI + OTLP receiver for browsing agent traces and eval results. Use when starting the viewer, importing/exporting/deleting traces, querying the viewer's REST API, or wiring an agent run so traces show up at…
Render and refine the system prompt of a nooa agent. Use when the user wants to inspect, debug, or improve an agent's prompt, context blocks, or tool documentation.
Solve an interactive grid game iteratively — observe, hypothesize, experiment, record knowledge, and submit action sequences until every level is won.
Solve an interactive grid game by learning a compressed world model (encode state to a latent z, learn a predict function), planning action sequences by search over it, and recording hypotheses, plans and knowledge to memory.
Explore and debug agent execution traces. Use when the user asks to analyze a trace, debug an agent run, investigate errors in a trace, or when they paste a trace-explorer prompt from the viewer UI.