Loading...
Loading...
Found 1,943 Skills
Apply Structural Equation Modeling (SEM) to test hypothesized causal structures by combining measurement models (CFA) and structural models (path analysis). Use this skill when the user needs to validate latent constructs, test mediation or moderation paths, assess model fit with CFI/TLI/RMSEA/SRMR, or when they ask 'do these variables form a causal chain', 'how do I test my theoretical model', or 'is my measurement model valid'.
Implement Elo rating system to rank items or players from pairwise comparison outcomes. Use this skill when the user needs to rank items from head-to-head matchups, build a competitive rating system, or evaluate relative quality from comparison data — even if they say 'player rating', 'ranking from comparisons', or 'competitive scoring system'.
Apply Porter's Diamond Model to analyze national competitive advantage for a specific industry. Use this skill when the user needs to evaluate why certain nations dominate particular industries, assess a country's attractiveness for industry investment, or diagnose gaps in national competitiveness using the four determinants plus government and chance.
AscendC Operator Precision Evaluation. Generate a comprehensive precision test case set (≥30 cases) for the compiled and installed operator, run the tests and generate a precision verification report. Keywords: precision test, precision evaluation, precision report, accuracy, error analysis. After execution, YOU MUST display the overview, failure summary and key findings in the current conversation, and must not only attach the report path.
Evaluate the quality of CAW (Cobo Agentic Wallet) Agent in local Claude Code, and generate scoring data and analysis reports. Use when: Users want to run CAW evaluation, conduct evaluation, test Skill, assess Agent quality, generate evaluation reports, or say "run evaluation", "evaluate CAW", "eval", "score". For weak model / openclaw evaluation, please use caw-eval-openclaw (only installed on openclaw servers).
Command-line interface for CloudAnalyzer — Agent-friendly harness for CloudAnalyzer, a QA platform for mapping, localization, and perception outputs. Supports 27 commands across 8 groups: point cloud evaluation, trajectory evaluation, ground segmentation QA, config-driven quality gates, baseline evolution, processing, visualization, and interactive REPL.
UI design and review should apply Nielsen's 10 Usability Heuristics — the foundational principles for evaluating and improving usability. Use when auditing an interface, designing interaction flows, writing error messages, or reviewing any UI for usability issues.
Apply Benjamin Graham's value investing framework to evaluate stocks, portfolio allocation, and investment vs. speculation decisions. Trigger on: "Is this stock worth buying?", "Is this investment or speculation?", "How should I allocate my portfolio?", "Is this company a good value?", "should I sell in a downturn?", "evaluate this stock for a defensive investor".
A methodology for iteratively improving agent-facing text instructions (skills / slash commands / task prompts / CLAUDE.md sections / code-generation prompts) by having a bias-free executor actually run them and evaluating two-sidedly (executor self-report + instruction-side metrics). Keep iterating until improvements plateau. Use it right after creating or substantially revising a prompt or skill, or when you want to attribute an agent's unexpected behavior to ambiguity on the instruction side.
Evaluate solutions through multi-round debate between independent judges until consensus
Laws of UX critique skill. Use when evaluating mockups, screenshots, design specs, prototypes, flows, onboarding, checkout, dashboards, forms, or design-review requests, even when the user does not say UX or name a law. Output the 2-4 most relevant laws with specific application and law-grounded recommendations. Do not use for pure frontend implementation code review, WCAG/accessibility audits, or brand/visual-identity critique unless interaction usability is also in scope.
[Hyper] Optimize an existing codebase through baseline-first experiments, binary evaluation, and one-mutation-at-a-time iteration. Use for codebase autoresearch, measured bottleneck reduction, benchmarked code optimization, and evidence-backed refactors.