370 skills · sorted by relevance
Explore local or remote repositories with Repomix CLI to understand their structure, locate related code across files, and review file counts and estimated tokens, the units AI models use to process text.
Combine code from local directories or GitHub into one structured file for AI analysis. Examine project structure, search for related code, and check estimated tokens, the units AI models use to process text.
Build a local interactive interface for exploring calculations, simple simulations, and weighted comparisons. Adjust inputs to see how results change, with visible formulas, units, and assumptions that explain what the numbers mean.
Turn feature ideas into backlog items, a team's planned units of work, using Why, What, and Acceptance Criteria. Connect each item to business goals and define observable outcomes in independent pieces sized for one sprint.
Create, edit, and validate URDF files describing robot structure. Check links, joints, coordinate frames, units, mesh placement, and mass properties, then use CAD Viewer to inspect the model and review each movable joint.
Audit Google Mobile Ads SDK integration in iOS, Android, or Unity projects. Check test IDs, ad units, SKAdNetwork IDs, adapter compatibility, and ad preloading, then report findings and next steps in a table.
Review AI agent instructions for unnecessary rules, contradictions, repetition, and vague wording. Get recommendations on what to remove, merge, clarify, or load only when needed, plus an estimate of savings in tokens, the units models process.
Find the Wren CLI workflow for answering data questions, connecting databases or SaaS sources, generating model definitions, adding business metrics, or building a shareable analytics app. Guides are retrieved from the installed CLI version.
Supports analysis of tables already in the workspace through data inspection, Python calculations, and charts chosen for the question. It also explains how to ask users for clarification and label results with meaningful units and names.
Research new models and API capabilities offered by providers behind Pipecat services. Produce dated reports for each service and local committed branches for clear updates, with review commands and separate publishing steps.
Build text tokenizers, which split text into units for AI models, directly from raw multilingual text. Learn custom vocabularies with BPE or Unigram, convert text to pieces or numeric IDs, and decode the results.
Organize medical guidelines into structured learning tracks, preview upcoming units, and manage delivery using recorded progress. It also supports investigating duplicate or missed deliveries and planning transitions to new guideline versions using authoritative sources.
Design and evaluate paid-ad experiments with clear hypotheses, comparison groups, sample requirements, and stopping rules. Check data quality before estimating effects, then deliver structured results and a plain-language decision that reflects uncertainty and the population tested.
Explore and query measurements stored in Axiom MetricsDB. The skill discovers metrics and tags, checks measurement types and units, and builds MPL queries, Axiom’s metrics query language, to retrieve values and aggregate them over a chosen period.
Coordinate temporary agents for code exploration, independent implementation tasks, verification, reviews, or complex debugging. Define self-contained assignments, run independent work in parallel, and check returned evidence before combining the results.
Prepare public-company financial data for analysis models by standardizing periods, units, currencies, and account labels. Produce structured tables with source references, validation results, and clear flags for missing data, conflicts, or disclosure changes.
Run an initial quality review of public equity investment decks and reports. Identify inconsistent figures, unclear units, missing sources, and conflicting conclusions, then prioritize fixes and document evidence limits in a review report.
Choose, build, and review charts that answer a clear analytical question. The skill checks chart types, labels, units, colors, and data sufficiency, then refines the visual in its intended report, dashboard, notebook, or other output.
Design and review how a system is divided into modules, cohesive parts with clear responsibilities. Evaluate data ownership, communication rules, dependencies, and failure handling, and decide when to split or merge parts without assuming a particular technology.
Analyze a monolithic codebase before splitting it into modules or services. The skill inventories components, examines duplication, hierarchy, and dependencies, then proposes groupings aligned with business domains, with optional checks against business terminology and boundaries.
Create green isometric illustrations, using angled views without perspective, of developer and design workspaces as SVG files. A bundled drawing kit helps arrange equipment on one platform, with consistent shading, fine details, shadows, and validation checks.
Build JavaScript or TypeScript apps that interact with NEAR. This skill guides token transfers, smart contract calls, account and key management, transaction signing, and message authentication through near-api-js v7 examples.
Extract key metrics from spreadsheet data, check whether recorded values match calculations after unit conversion, and rank selected metrics from highest to lowest. Export the ranking or validation results to an Excel file for download.
Process astronomical data in Python with Astropy. This skill covers celestial coordinate, unit, and time conversions; reading and editing FITS astronomy files; matching object catalogs; and calculating cosmic distances using cosmological models.