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Found 1,927 Skills
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.
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.
Honestly evaluate AI work quality using a two-axis scoring system. Use after completing a task, code review, or work session to get an unbiased assessment. Detects score inflation, forces devil's advocate reasoning, and persists scores across sessions.
Evaluate Omni AI query generation accuracy by running test prompts through the Omni CLI, comparing generated query JSON against expected results, and scoring accuracy. Use this skill whenever someone wants to evaluate Omni AI, benchmark Blobby, run regression tests, compare AI output across branches or configurations, test prompt variations, measure AI quality, run A/B tests on model changes, assess impact of context changes, or any variant of "run evals", "test Blobby", "benchmark query generation", "compare AI results", "regression test", "how accurate is the AI", or "measure the impact of my changes".
Find and evaluate research datasets for any scientific question. Teaches how to reason about data needs, search across public repositories, evaluate dataset fitness, and identify access requirements. Use whenever users ask to find data, search for datasets, identify cohort studies, or need data for analysis. Also use when users ask about a specific survey or cohort (NHANES, HRS, UK Biobank, TCGA, etc.), when they want to know what data exists for a research question, or when they need to compare available data sources. If the user mentions "where can I get data" or "is there a dataset for X", this is the right skill.
This skill should be used when the user wants to run baseline evaluations on existing agent skills, regenerate transcripts after a model upgrade, or check whether a skill still solves the gap it was authored for. Common triggers include "rerun the baselines", "re-eval skill X", "test all the skills", "check for skill drift", and "run the evals". Bakes in verbatim transcript capture (no paraphrasing), deterministic-only grading (regex / contains / file_exists — no LLM-as-judge), and the iteration-N workspace convention. Skip when authoring a new skill (use skill-creator) or modifying skill content directly.
Retrieve sector P/E ratios using Octagon MCP. Use when comparing company valuations to sector benchmarks, analyzing sector valuations across exchanges, and understanding market-wide valuation trends.
Evaluate whether figures and plots in a manuscript effectively communicate the claims they support. Audits chart-type fit, axis design, visual hierarchy, data density, caption interpretation, perceptual accuracy, and narrative arc across 8 dimensions. Triggers on: "do my figures work", "check my plots", "are my graphs clear", "figure audit", "do my figures support my claims", "visualization review", "figure rhetoric", "plot review", "chart critique", "visual argument check". Companion to manuscript-review §12 (legibility) and figure-table-quality (rendering).
Test C# MCP servers at multiple levels: unit tests for individual tools and integration tests using the MCP client SDK. USE FOR: unit testing MCP tool methods, integration testing with in-memory MCP client/server, end-to-end testing via MCP protocol, testing HTTP MCP servers with WebApplicationFactory, mocking dependencies in tool tests, creating evaluations for MCP servers, writing eval questions, measuring tool quality. DO NOT USE FOR: testing MCP clients (this is server testing only), load or performance testing, testing non-.NET MCP servers, debugging server issues (use mcp-csharp-debug).
Analyze equity securities, factor models, and equity portfolio construction. Use when the user asks about stocks, equity valuation ratios, index construction methods, or style analysis. Also trigger when users mention 'P/E ratio', 'growth vs value', 'market cap weighting', 'sector allocation', 'GICS classification', 'earnings per share', 'Fama-French factors', 'CAPM', 'dividend yield', 'PEG ratio', 'EV/EBITDA', or ask which factors explain equity returns.