Proves
Proves unitàries, d’integració i automatitzades
life-meaning
kangarooking
当用户问「活着的意义是什么/找不到方向/虚无感/该为什么努力」时调用。 核心理念: 生命没有外在赋予的意义(宇宙尺度一切会消失); 意义=个人创造+愿意为之受苦; 拥抱死亡是意义的入口。 不适用于: 急性自杀风险(先紧急求助)。 Triggers: 生命的意义/虚无/找不到意义/为什么活着/meaning/purpose/nihilism
V3 Swarm Coordination
ruvnet
"15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline."
swarm-advanced
ruvnet
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
V3 Core Implementation
ruvnet
"Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing."
consult-outside-expert
basecamp
Get a second opinion via Codex MCP. Use for stress-testing ideas, getting fresh perspective, steelmanning arguments, or iteratively refining work through expert back-and-forth. Invoke for ANY request involving external review, feedback, or consultation.
statistical-analysis
ynulihao
"Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research."
python-expert
tao12345666333
Python development best practices and advanced patterns
godot-genre-rts
thedivergentai
"Expert blueprint for real-time strategy games including unit selection (drag box, shift-add), command systems (move, attack, gather), pathfinding (NavigationAgent2D with RVO avoidance), fog of war (SubViewport mask shader), resource economy (gather/build loop), and AI opponents (behavior trees, utility AI). Use for base-building RTS or tactical combat games. Trigger keywords: RTS, unit_selection, command_system, fog_of_war, pathfinding_RVO, resource_economy, command_queue."
godot-economy-system
thedivergentai
"Expert patterns for game economies including currency management (multi-currency, wallet system), shop systems (buy/sell prices, stock limits), dynamic pricing (supply/demand), loot tables (weighted drops, rarity tiers), and economic balance (inflation control, currency sinks). Use for RPGs, trading games, or resource management systems. Trigger keywords: EconomyManager, currency, shop_item, loot_table, dynamic_pricing, buy_sell_spread, currency_sink, inflation, item_rarity."
nextjs-tanstack-form
fusengine
TanStack Form v1 for Next.js 16 with Server Actions, Zod validation, and shadcn/ui integration. Use when building forms, validation, multi-step wizards, or dynamic field arrays.
harden
pbakaus
Improve interface resilience through better error handling, i18n support, text overflow handling, and edge case management. Makes interfaces robust and production-ready.
geniml
K-Dense-AI
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
gtars
K-Dense-AI
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
deepchem
K-Dense-AI
Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.
Shape output for an ADHD reader
melodic-software
"Shape the assistant's output for a reader with ADHD, and anyone who wants action-first, low-friction responses. Lead with the concrete next action, number multi-step work, restate state across turns, cap and rank lists, give concrete time estimates, make wins visible, and cut preamble, recap, and closers. Use when: 'ADHD-friendly', 'action-first', 'give me the structured version', 'lead with what to do', 'cut the preamble', or when the user invokes it to set that output shape for the session. Once invoked, applies to every response for the rest of the session. This is a STANDING posture over future responses; to reshape one dense message already on screen (chunk it one-decision-at-a-time, define its jargon, surface the decisions) without changing the session style, that is the one-shot sibling adhd:clarify. Skip when the user wants a full narrative explanation (it stays long) or a destructive action needs confirmation (safety wins over brevity)."
security-research-guardrail
Sekolah76
Independent control layer for security-research agents — prevent unsafe actions, unsupported claims, scope violations, evidence contamination, target impact, and premature reporting.
security-finding-triage
Sekolah76
Adversarial security finding triage — decide whether a candidate finding is real, reachable, exploitable, and in-scope by actively trying to falsify it before it reaches report-ready status.
agent-evaluation
benjaminasterA
"Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring\u2014where even top agents achieve less than 50% on re..."
e2e
vellum-ai
Run end-to-end tests via the CI workflow.
typescript-eval
vellum-ai
Test TypeScript code snippets before persisting as skills
web-renderer-test
remotion-dev
Add a test case to the web renderer
Edge Cases
product-on-purpose
A curated collection of 24 best-practice, plug-and-play product management “agent skills” plus templates and workflow bundles for consistent, professional PM outputs.
Experiment Results
product-on-purpose
A curated collection of 24 best-practice, plug-and-play product management “agent skills” plus templates and workflow bundles for consistent, professional PM outputs.
cellxgene-census
K-Dense-AI
Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.