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Found 1,903 Skills
Create code-based evaluators for LangSmith-traced agents with step-by-step collaborative guidance through inspection, evaluation logic, and testing.
Testing framework for evaluating Databricks skills. Use when building test cases for skills, running skill evaluations, comparing skill versions, or creating ground truth datasets with the Generate-Review-Promote (GRP) pipeline. Triggers include "test skill", "evaluate skill", "skill regression", "ground truth", "GRP pipeline", "skill quality", and "skill metrics".
Build and revise Rive Luau scripts across Node, Layout, Converter, Path Effect, Transition Condition, Listener Action, Util, and Test protocols. Use when the user asks to write or modify Rive scripts, choose protocols, wire script inputs or data binding, debug runtime behavior, or plan unit tests for script logic.
Evaluate complex requests from 3 independent perspectives (Creative, Pragmatic, Comprehensive), reach consensus, then produce complete outputs. Use for architecture decisions, creative content, analysis, and any task where multiple valid approaches exist.
This skill is used when users explicitly request "review NSFC proposals", "simulate expert review", or "evaluate NSFC applications". It simulates the perspective of domain experts to conduct multi-dimensional reviews of NSFC proposals, outputting graded issues and actionable modification suggestions. ⚠️ Not applicable: when users only want to write/modify a specific section of a proposal (use the nsfc-*-writer series skills instead), only want to understand review criteria (answer directly), or have no clear "review/evaluate" intent.
Fetch, organize, and analyze LangSmith traces for debugging and evaluation. Use when you need to: query traces/runs by project, metadata, status, or time window; download traces to JSON; organize outcomes into passed/failed/error buckets; analyze token/message/tool-call patterns; compare passed vs failed behavior; or investigate benchmark and production failures.
Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.
Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models
Comprehensive primary skill for agents working with Weights & Biases. Covers both the W&B SDK (training runs, metrics, artifacts, sweeps) and the Weave SDK (GenAI traces, evaluations, scorers). Includes helper libraries, gotcha tables, and data analysis patterns. Use this skill whenever the user asks about W&B runs, Weave traces, evaluations, training metrics, loss curves, model comparisons, or any Weights & Biases data — even if they don't say "W&B" explicitly.
INVOKE THIS SKILL when creating, running, or analyzing Arize experiments. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI.
A decision-support framework that evaluates systems, architectures, and strategies through the entropy (decay) vs negentropy (growth) lens, while surfacing tacit knowledge gaps. Use this skill whenever the user is making architecture decisions, evaluating system designs, reviewing technical approaches, choosing between options, auditing existing systems, or planning strategies. Also trigger when the user explicitly asks to "apply the negentropy lens", mentions "entropy", "negentropy", "tacit knowledge", "knowledge engine", or "flip the switch". Nudge activation when you detect the user is at a decision point — even if they haven't asked for this lens — by briefly noting the entropic/negentropic dimension before proceeding.
Design click/first-click tests to evaluate navigation and information findability.