数据处理

denario

jimmc414

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.

anndata

jimmc414

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

lamindb

jimmc414

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

hmdb-database

jimmc414

"Access Human Metabolome Database (220K+ metabolites). Search by name/ID/structure, retrieve chemical properties, biomarker data, NMR/MS spectra, pathways, for metabolomics and identification."

social-push

jihe520

使用 agent-browser 帮用户将内容发到社交媒体上。当用户需要发布内容、推送文章、上传文章、发帖到社交平台时使用此 skill。

speckit-specify

dceoy

Create or update a feature specification from a natural language feature description.

speckit-clarify

dceoy

Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.

approval-tests

lexler

Writes approval tests (snapshot/golden master testing) for Python, JavaScript/TypeScript, or Java. Use when verifying complex output, characterization testing legacy code, testing combinations, or working with .approved/.received files.

playwright-best-practices

NeverSight

Provides Playwright test patterns for resilient locators, Page Object Models, fixtures, web-first assertions, and network mocking. Must use when writing or modifying Playwright tests (.spec.ts, .test.ts files with @playwright/test imports).

python-best-practices

NeverSight

Provides Python patterns for type-first development with dataclasses, discriminated unions, NewType, and Protocol. Must use when reading or writing Python files.

Jira Agile Skill

NeverSight

A crawler script to fetch skill data from network, automatically executed daily via GitHub Actions.

event-modeling

lexler

Designs systems using Event Modeling.

op-cli

NeverSight

Secure 1Password CLI patterns for reading secrets, discovering vaults/items, and piping credentials to other tools. Use when reading from 1Password, rotating secrets, or piping credentials to wrangler/kubectl/etc. Triggers on op CLI, 1Password, secret rotation, or credential piping tasks.

collaborative-design

lexler

Designs software features collaboratively through visual scenarios and iterative refinement. Use when designing features, tools, UIs, workflows, or any system before implementation.

odoo-19

unclecatvn

Odoo 19 development knowledge base with 18 specialized guides covering Actions (ir.actions.*, cron jobs, server actions), Controllers (HTTP routing, endpoints, auth types), Data files (XML/CSV records, shortcuts, noupdate), API Decorators (@api.depends, @api.constrains, @api.ondelete, @api.onchange, @api.model), Module development (manifest, wizards, reports), Field types (Char, Text, Monetary, relational fields), Manifest configuration (manifest.py, dependencies, asset bundles), Mixins (mail.thread, mail.activity.mixin, mail.alias.mixin, utm.mixin), ORM Model methods (search, CRUD, domain filters, recordsets, prefetch), Migration scripts (pre/post/end hooks, data migration), OWL frontend components (hooks, services, lifecycle), Performance optimization (N+1 prevention, batch ops, read_group), QWeb Reports (PDF/HTML, paper formats, barcodes), Security/ACL (record rules, field permissions, multi-company), Testing (TransactionCase, HttpCase, mocking, query count assertions), Transactions (savepoints, UniqueViolation, serialization failures), Translations (i18n, PO files, translatable fields), XML Views (list/form/search, xpath inheritance, QWeb templates). Use when writing, reviewing, or debugging any Odoo 19 Python or XML code, creating or modifying modules, fixing performance issues, or looking up Odoo 19 API patterns and best practices.

react-frontend

iliaal

React, TypeScript, and Next.js patterns for frontend development. Use when building React components, managing state, fetching data, optimizing performance, or working with Next.js App Router. Covers React 18-19, hooks, Server Components, and type-safe patterns.

meta-prompting

iliaal

Enhanced reasoning patterns via slash commands (/think, /verify, /adversarial, /edge, /compare, /confidence, /budget, /constrain, /json, /flip, /assumptions, /tensions, /analyze, /trade) or natural language ("argue against", "what could break", "show reasoning", "deep review", "meta-prompts", "thinking modes", "second-best approach", "list assumptions", "opposing perspectives").

analyzing-time-series

https-deeplearning-ai

Comprehensive diagnostic analysis of time series data. Use when users provide CSV time series data and want to understand its characteristics before forecasting - stationarity, seasonality, trend, forecastability, and transform recommendations.

laravel-pdf

spatie

Generate PDFs from Blade views or HTML using spatie/laravel-pdf. Covers creating, formatting, saving, downloading, and testing PDFs with the Browsershot, Cloudflare, or DOMPDF driver.

analyzing-time-series

https-deeplearning-ai

Comprehensive diagnostic analysis of time series data. Use when users provide CSV time series data and want to understand its characteristics before forecasting - stationarity, seasonality, trend, forecastability, and transform recommendations.

Practice Question Generator

https-deeplearning-ai

grace-ask

osovv

"Answer a question about a GRACE project using full project context. Use when the user has a question about the codebase, architecture, modules, or implementation — loads all GRACE artifacts, navigates the knowledge graph, and provides a grounded answer with citations."

Practice Question Generator

https-deeplearning-ai

analyzing-marketing-campaign

https-deeplearning-ai

Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.