483 skills · sorted by relevance
Write and edit READMEs, guides, and other documentation using the code as evidence. Improve structure, wording, and terminology while checking related pages and links against the project's contribution process and documentation style guide.
Make 3D canvas output sharper on Retina and other high-density displays. Coordinate rendering and post-processing resolution, preserve pointer accuracy, and verify fixed 200% rendering or automatic scaling with measured performance and explicit fallbacks.
Check academic references for existence, accurate publication details, and support for the claims being cited. This guide explains how to verify sources, obtain bibliography entries, and flag references that cannot be confirmed.
Find academic papers through Google Scholar and PubMed, retrieve publication details from identifiers, and build BibTeX reference files. Check author and publication information, detect duplicates, and standardize formatting before using references in a manuscript.
Check academic references for existence, accurate publication details, and support for cited claims. Provides a writing-time verification workflow using WebSearch and Google Scholar, including BibTeX retrieval and clear handling of references that cannot be verified.
Guide economic time series analysis from initial plots to forecasting. Use Python, R, and Stata examples to check whether statistical properties remain stable over time, choose models, diagnose errors, and examine relationships between multiple series.
Turn a recurring workflow into an agent skill, or improve an existing one. Draft instructions, compare test outputs against a baseline, review quality and resource usage, and refine the description that determines when the skill is invoked.
Search for academic papers, retrieve publication details from identifiers such as DOIs, and create BibTeX reference records. Check existing bibliographies for missing information, duplicate entries, invalid identifiers, and formatting problems before using them in research writing.
Check code and agent outputs, track reliability scores, and roll back changes that fail a chosen threshold. Includes quality reports, live monitoring, and integration with automated build and deployment workflows.
Train, deploy, and run predictions with neural networks using Flow Nexus and E2B sandboxes, isolated computing environments. Use existing model templates, distribute training across multiple environments, and check training progress and model performance.
Turn a rough request into a structured AI prompt with a clear goal, output format, and constraints. For complex work, add smaller tasks, separate creator and reviewer roles, and explicit checks for accuracy and uncertainty.
Check specific documentation pages against source code, one factual claim at a time. Receive verdicts showing supported, partly supported, contradicted, or unsupported statements, with code file and line references and suggested corrections.
Find academic papers, retrieve publication details, and build BibTeX reference files for scholarly writing. Check identifiers, missing information, duplicate entries, and mismatches between manuscript citations and the bibliography, with tools for formatting and validation.
Audit XML sitemaps by checking their structure and listed URLs against actual page conditions. Find errors, redirects, pages excluded from indexing, missing eligible pages, and inaccurate modification dates to identify sitemap problems affecting indexing.
Choose methods for differential equations with conditions specified at boundaries. The skill guides problem classification, shooting methods, finite differences, numerical solvers, and eigenvalue problems, with command examples for exploring solutions and checking numerical accuracy.
Edit large code files through the Morph Apply API without reading the entire file first. Provide a change description and a code snippet with placement markers to add error handling, insert logging, or apply several related changes together.
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
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Implements the NOWAIT technique for efficient reasoning in R1-style LLMs. Use when optimizing inference of reasoning models (QwQ, DeepSeek-R1, Phi4-Reasoning, Qwen3, Kimi-VL, QvQ), reducing chain-of-thought token usage by 27-51% while preserving accuracy. Triggers on "optimize reasoning", "reduce thinking tokens", "efficient inference", "suppress reflection tokens", or when working with verbose CoT outputs.
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Deterministic mathematical computation using SymPy. Use for ANY math operation requiring exact/verified results - basic arithmetic, algebra (simplify, expand, factor, solve equations), calculus (derivatives, integrals, limits, series), linear algebra (matrices, determinants, eigenvalues), trigonometry, number theory (primes, GCD/LCM, factorization), and statistics. Ensures mathematical accuracy by using symbolic computation rather than LLM estimation.
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Comprehensive citation management for academic research. Resolve bibliographic identifiers, extract accurate metadata, validate citations, deduplicate references, and generate properly formatted BibTeX entries. This skill should be used when you need to verify citation information, convert DOIs/PMIDs/arXiv IDs to BibTeX, or ensure reference accuracy in scientific writing.
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Run TAO Data Services KPI analysis for object detection, comparing inference annotations against ground truth to compute per-class TP/FP/FN/TN, precision, recall, accuracy, and AP at a fixed IoU. Use when an object detection workflow needs per-class mAP reported after inference, or when the user asks to "run KPI analyze", "compute detection mAP", or "score my OD predictions against ground truth".
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Performance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config. Not for accuracy / RAGAS scoring (use rag-eval) or for deploying / repairing services (use rag-blueprint).
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Format messages for Slack with pixel-perfect accuracy. Converts Markdown to rich HTML (for copy-paste into Slack) or Slack mrkdwn (for API/webhook). Use when the user asks to write a Slack message, announcement, or notification, format something "for Slack", preview how content looks in Slack, or send a message via Slack webhook. Also trigger when user mentions Slack formatting, mrkdwn, or wants to share Markdown content in Slack channels.
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Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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