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SkillsMP has collected 15 skills from NVIDIA-AI-Blueprints/aiq. Open a skill to review its source and details.
Showing 15 of 15 collected skills.
Use when composing, adapting, or validating an AI-Q workflow YAML under configs/ — selecting a shipped profile, enabling tools and data_source_registry sources, wiring chat or direct data-science workflows, configuring NeMo Relay and general.telemetry…
Use this skill to turn researched or computed numeric data into source-grounded charts. It has two delivery modes and picks one from the tools available to you. When an `execute` tool (sandbox) is available, render a PNG chart plus its CSV with…
Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
Use when customizing AI-Q agent behavior through Jinja2 prompt templates or per-agent model selection — editing prompts under src/aiq_agent/agents/*/prompts/, adding template variables, or assigning/swapping LLMs per agent role via config (the llms section…
Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure.
Use when changing AI-Q continuous integration, pre-commit, or contributor governance — editing .github/workflows/ (ci, ui, skills-eval, request-nvskills-ci), .pre-commit-config.yaml hooks, .github/CODEOWNERS, .coderabbit.yaml, copy-pr-bot, or the…
Use when validating an AI-Q change before opening or merging a PR — choosing and running the right Python, frontend, docs, or eval checks for the surfaces you touched instead of one fixed command list.
Use when adding or changing an AI-Q data source under sources/, registering it as a NeMo Agent Toolkit function, wiring it into the data_source_registry for UI toggles, or validating retrieval behavior with tests.
Use when adding or changing a general-purpose AI-Q tool (a NeMo Agent Toolkit function) under sources/, defining its FunctionBaseConfig schema, registering it with @register_function, wiring it into an agent's tools list, or testing it.
Use this skill for converting researched facts or user-provided data into structured tables by writing code, then running Python/pandas calculations in the job-scoped sandbox. This skill is for numeric normalization, tabular analysis, rankings, growth rates,…
Use this skill during research for lightweight forecast evidence analysis: base-rate checks, prediction-market anchors, scenario ranges, directional factor summaries, implied probabilities, and monitoring indicators. Triggers: "forecast", "prediction",…
Use this skill for small deterministic calculations during research when pandas/table analysis is unnecessary. Triggers: "calculate", "arithmetic", "unit conversion", "percentage point", "expected value", "weighted average", "range", "ratio", "sanity check",…
Use this skill when the final answer strategy calls for a long-form report, publication-quality research writeup, comprehensive analysis, deep dive, whitepaper-style narrative, or detailed cited Markdown report. Triggers: "long_form_report", "long-form…
Use when preparing, opening, or updating an AI-Q pull request — scoping the branch, signing commits with DCO, filling the PR template with real validation evidence, and following the copy-pr-bot CI and merge flow.
Use this skill when the final answer strategy calls for a prediction, forecast, probability estimate, price target, expected value, threshold outcome, scenario outlook, or prediction-style research report. This skill takes priority over general long-form…