allenai

This skill should be used when the user asks to "generate theories", "theorize about", "what theories explain", "form scientific theories", "literature-driven theories", "hypothesize", "form hypotheses", "generate hypotheses", "what hypotheses explain", "run the theorizer", or wants AI-generated, literature-grounded scientific theories or hypotheses about a research question.

Show the user the agent's work on a research project and save iterations on the user's behalf. Scaffold rendering and deploy infrastructure (Quarto today, GitHub Pages, dev container), show the rendered output, save iterations. Doesn't handle research execution (use `research-step`).

Look up or search papers, authors, citations, and full-text snippets on Semantic Scholar. Use for fast, targeted queries about a paper, author, or specific named research artifact (benchmark, dataset, model, method, etc.) — not comprehensive reports.

Local document metadata index for files used by Asta skills and tools. Use this skill when the user asks to store a document "in Asta" or retrieve "from Asta". Use it when the user references an "Asta document" or anything with an `asta://` URI.

Create, configure, and monitor AutoDiscovery runs. Use when the user asks about their runs, experiments, discoveries, wants to check status, or wants to start a new discovery run.

Run scientific (software) experiments. Use when the user asks to "run an experiment", "run an investigation", or "research with Asta." Also use this skill to analyze experimental data generate a research report from it. The user may refer to this system by its internal project name, "Panda."

This skill should be used when the user asks to "find papers", "search for papers", "what does the literature say", "find research on", "academic papers about", "literature review", "cite papers", or needs to answer questions using academic literature.

Build a searchable Asta document index from a collection of local PDF files. Use when the user asks to "index these PDFs", "put these PDFs into an Asta index", "index these PDFs using Asta", "build a local paper index", "make these PDFs searchable", or "create an index from these papers".

Run a VLA model evaluation against a simulation benchmark. Use this skill whenever the user wants to evaluate, benchmark, test, or run a model on a sim environment — even if they say it casually like 'try OpenVLA on LIBERO' or 'get me CALVIN scores'. Covers the full workflow: serving the model, launching the benchmark, sharding for speed, merging results, and interpreting output.

Add a new simulation benchmark to the VLA evaluation harness. Use this skill whenever the user wants to integrate, create, or add a new benchmark or simulation environment — e.g. 'add ManiSkill3', 'integrate OmniGibson', 'hook up a new sim'. Also use when they ask how benchmarks are structured or want to understand the benchmark interface.

Add a new VLA model server to the evaluation harness. Use this skill whenever the user wants to integrate, create, or add a new model — e.g. 'add OpenVLA server', 'integrate RT-2', 'hook up my model', 'write a model server'. Also use when they ask how model servers work or want to understand the server interface.

Runnable evaluation template scripts for ML tasks. Match task_type to template, adapt CONFIG, run.

Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.

Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.

Update the body of a GitHub pull request. Use when the user asks to update, edit, or modify a PR description/body.

Monitor Beaker experiments until completion. Use when the user asks to monitor, check, or track a Beaker experiment.

Local document metadata index for scientific documents

Local document metadata index for scientific documents

This skill should be used when the user asks to "create a verification script", "write a test training run", "make a quick training job", "verify my change with a short run", "launch a smoke test", or wants a small Beaker job to validate that a feature works end-to-end on GPUs. Also triggers when the user mentions creating a modified 190M script to test a specific behavior.

This skill should be used when the user asks to "start a task", "run a verifier", "verify my solution", "work on a Harbor task", "pier start", "pier verify", or needs to interactively work on Harbor benchmark tasks.