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Found 1,907 Skills
Execute a comprehensive NestJS Project Health Audit. Analyzes tech stack, architecture, API design, data layer, testing, code quality, CI/CD, and documentation. Produces a Google Docs-ready report with section scores and weighted overall score. Use when the user asks to audit a NestJS project, run a health check, evaluate backend quality, or assess technical debt. Triggers on: 'nestjs audit', 'health audit', 'backend audit', 'nestjs health', 'node audit', 'api audit', 'project quality check'.
Create a new runbook with guided assistance. A runbook is a structured markdown document that tells a coding agent how to accomplish a complex, multi-step task with evaluation loops and quality gates. Use this skill whenever the user wants to create, build, scaffold, or write a runbook — including 'create runbook', 'new runbook', 'build a runbook', 'make a runbook', 'runbook wizard', 'help me write a runbook', 'I need a runbook for...', 'automate this task with a runbook', or 'turn this into a runbook'. Also trigger when the user describes a multi-step agent task that would benefit from structured evaluation and iteration loops, even if they don't use the word 'runbook' — for example, 'I want to build an automated pipeline that evaluates its own output' or 'create a repeatable process with quality gates'.
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".
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.
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".
Converts CXAS golden evaluations to SCRAPI SimulationEvals test cases. Use when generating high-level, goal-oriented test cases from turn-by-turn evaluation JSONs, and when enriching test expectations with inferred tool calls.
Create institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.
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
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.
Evaluates test quality using Dave Farley's 8 properties. Use when reviewing tests, assessing test suite quality, or analyzing test effectiveness against TDD best practices.
Retrieve market capitalization data for a single company using Octagon MCP. Use when you need the current market value, valuation context, or size classification for any publicly traded stock.