Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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release-check
Pre-release verification checklist. Validates features, tests, docs, security, and quality gates before shipping. Delegates to the Centinela (QA) agent.
majiayu000/claude-skill-registry 163
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evaluation
Systematic evaluation and comparison of technologies, tools, frameworks, and approaches using weighted criteria and scoring matrices. Use when choosing between multiple technologies, vendor/tool selection, framework comparison, library selection, or architecture pattern selection.
majiayu000/claude-skill-registry 163
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aria-compliance
ARIA の商用利用、公開、および法的整合性に関するライセンス・ガイドライン。
majiayu000/claude-skill-registry 163
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rsn-learning-outcomes
Extracts insights and improves performance from experience. Applies single-loop (fix action), double-loop (fix frame), reflection (extract insight), experimentation (test belief), and calibration (adjust confidence) modes. Use when correcting mistakes, learning from outcomes, testing hypotheses, or improving predictions. Triggers on "why did this fail", "what can we learn", "test this", "how accurate are we", "pattern of failures".
majiayu000/claude-skill-registry 163
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better-auth
Add authentication with Better Auth (TypeScript). Use for email/password, OAuth providers (Google, GitHub), 2FA/MFA, passkeys/WebAuthn, sessions, RBAC, rate limiting.
majiayu000/claude-skill-registry 163
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minicoil-training
miniCOIL v1 sparse neural retrieval model training methodology: per-word linear layer training with triplet loss, word vocabulary from frequency-filtered English words, sparse retrieval with jina-embeddings-v2-small-en encoder, sparse embedding training pipelines, OpenWebText sentence extraction for self-supervised training, semi-hard triplet mining, and evaluation on BEIR benchmarks. English-only miniCOIL v1 (jina-embeddings, 30k words, mxbai-embed-large-v1 mining). Reference for building, training, and deploying sparse neural retrieval models compatible with inverted indexes and Qdrant.
majiayu000/claude-skill-registry 163
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vitest
Vitest fast unit testing framework powered by Vite with Jest-compatible API. Use when writing tests, mocking, configuring coverage, or working with test filtering and fixtures.
majiayu000/claude-skill-registry 163
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summarize
Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube).
majiayu000/claude-skill-registry 163
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clay-data-handling
Implement Clay PII handling, data retention, and GDPR/CCPA compliance patterns.
Use when handling sensitive data, implementing data redaction, configuring retention policies,
or ensuring compliance with privacy regulations for Clay integrations.
Trigger with phrases like "clay data", "clay PII",
"clay GDPR", "clay data retention", "clay privacy", "clay CCPA".
majiayu000/claude-skill-registry 163
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eventee-automation
Automate Eventee tasks via Rube MCP (Composio). Always search tools first for current schemas.
majiayu000/claude-skill-registry 163
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Drift Detection
This is an **alias skill** so docs can reference `77-mlops-data-engineering/drift-detection`. In this repo, drift guidance is covered by: - `77-mlops-data-engineering/drift-detection-retraining` (trig
majiayu000/claude-skill-registry 163
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sag
ElevenLabs text-to-speech with mac-style say UX.
majiayu000/claude-skill-registry 163
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security-reactnative
Segurança - Melhores Práticas React Native. Use when reviewing security, implementing auth, or hardening code.
majiayu000/claude-skill-registry 163
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researcher
Generates or refreshes research artifacts and RLM evidence for a ticket. Use when research stage should produce or update canonical RLM outputs.
majiayu000/claude-skill-registry 163
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bats-testing-patterns
Master Bash Automated Testing System (Bats) for comprehensive shell script testing. Use when writing tests for shell scripts, CI/CD pipelines, or requiring test-driven development of shell utilities.
majiayu000/claude-skill-registry 163
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billing-automation
Build automated billing systems for recurring payments, invoicing, subscription lifecycle, and dunning management. Use when implementing subscription billing, automating invoicing, or managing recurring payment systems.
majiayu000/claude-skill-registry 163
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create-blog
Create an SEO-optimized blog post from a topic or keyword.
majiayu000/claude-skill-registry 163
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building-native-ui
Complete guide for building beautiful apps with Expo Router. Covers fundamentals, styling, components, navigation, animations, patterns, and native tabs.
majiayu000/claude-skill-registry 163
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plan-risk
Identify risks before building. Flag third-party dependencies, API limits, and cost traps.
majiayu000/claude-skill-registry 163
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self-optimization
SONA self-optimizing neural architecture with ReasoningBank trajectory learning, EWC++ anti-forgetting, and reinforcement learning feedback loops.
majiayu000/claude-skill-registry 163
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fabric-pyspark-perf-remediate
Diagnose and resolve Apache Spark performance issues in Microsoft Fabric notebooks and Spark Job Definitions. Use when PySpark jobs are slow, notebooks take too long, Spark stages are skewed, shuffles are excessive, out-of-memory errors occur, Delta Lake writes are slow, or Fabric capacity is throttled. Covers data skew, shuffle optimization, broadcast joins, partition tuning, VOrder, Optimized Write, resource profiles, autotune, native execution engine, small file compaction, and Spark UI interpretation. Keywords include slow notebook, OOM, spill, shuffle, skew, broadcast, repartition, coalesce, OPTIMIZE, VACUUM, Z-ORDER, checkpoint, cache, persist, executor memory, driver memory, spark.sql.shuffle.partitions, autoBroadcastJoinThreshold, maxPartitionBytes, Fabric capacity throttling, CU utilization.
majiayu000/claude-skill-registry 163
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i18n-localization
Internationalization and localization patterns. Detecting hardcoded strings, managing translations, locale files, RTL support.
majiayu000/claude-skill-registry 163
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service-implementation
Implement Effect services as fine-grained capabilities avoiding monolithic designs
majiayu000/claude-skill-registry 163
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scvi-tools
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or multi-modal integration (TOTALVI, MultiVI). Best for advanced modeling, batch effects, multimodal data. For standard analysis pipelines use scanpy.
majiayu000/claude-skill-registry 163