Dados e Análise
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systems-programming
Systems programming from memory management through networking. Covers memory models (stack vs heap, manual allocation, garbage collection, ownership/borrowing), concurrency (threads, mutexes, channels, async/await, actor model, data races vs race conditions), operating system concepts (processes, virtual memory, page tables, system calls, file descriptors, signals), compilation (lexing, parsing, c
stakeholder-communication
Stakeholder identification, communication planning, and facilitation for project teams. Covers power/interest grid mapping, communication plans (audience, frequency, channel), status reporting (RAG, earned value, burn charts), RACI matrices, meeting facilitation, conflict resolution, change management (Kotter's 8 steps), psychological safety (Edmondson), managing up, and remote/distributed team co
cortex-navigate-knowledge
Navigate the knowledge graph — trace entity relationships, explore causal chains, drill into memory clusters, and traverse co-access paths. Use when the user asks 'how are these related', 'what connects X to Y', 'show me the knowledge graph', 'trace the relationship', 'what caused X', 'drill down into', 'explore connections', or when you need to understand the web of relationships between concepts
openstack-glance
OpenStack Glance image service skill for deploying, configuring, operating, and troubleshooting the VM image registry. Covers image upload/download, format management (qcow2, raw, vmdk, vhd, iso), backend storage selection (file, swift, ceph), image import methods (web-download, glance-direct, copy-image), metadata management, property protections, image sharing between projects, snapshot lifecycl
cortex-recall
Search and retrieve memories from Cortex persistent memory. Use when the user asks 'what did we decide about X', 'do you remember', 'what was the fix for', 'find that thing about', 'search memories', 'what do we know about', 'have we seen this before', or when you need context about past decisions, patterns, bugs, or architecture choices. Also use proactively when working on something that likely
cybersecurity-basics
Foundational cybersecurity literacy covering threat landscape (malware, phishing, social engineering, network attacks), defensive practices (encryption, authentication, access control, patching), privacy fundamentals (data collection, tracking, regulatory frameworks), and security reasoning (threat modeling, risk assessment, defense in depth). Use when explaining security concepts, evaluating syst
data-analysis-sci
Data collection, analysis, and interpretation for scientific inquiry. Covers measurement and units, data recording and organization, descriptive and inferential statistics, graphical representation, error analysis, drawing valid conclusions from evidence, and recognizing the limits of data. Use when collecting, analyzing, visualizing, or interpreting scientific data at any level.
security-hygiene
Security hygiene for GSD's self-modifying skill and agent system. Use this skill whenever: creating, editing, or deleting skill files (.claude/skills/, .claude/commands/), modifying agent definitions (.claude/agents/), working with YAML configuration or chipset files, handling JSONL observation data (.planning/patterns/), processing community-contributed skills or chipsets, any file path operation
ethics-governance
Bias detection and mitigation, fairness metrics, privacy frameworks, consent models, transparency requirements, and accountability structures for data science practice. Covers algorithmic bias sources, disparate impact testing, differential privacy, GDPR principles, model cards, datasheets for datasets, responsible AI frameworks, and the organizational governance needed to make ethics actionable.
aminet-index
Manages Aminet INDEX infrastructure: fetch, parse, cache, and incremental update of ~84,000-entry package database. Use when managing INDEX data, checking freshness, or parsing .readme files.
bayesian-methods
Bayesian approach to statistical inference and decision-making. Covers prior specification, likelihood functions, posterior computation, conjugate priors, Markov chain Monte Carlo (MCMC), credible intervals, Bayesian hypothesis comparison (Bayes factors), hierarchical models, and the philosophical contrast with frequentist methods. Use when updating beliefs with data, specifying priors, computing
cortex-setup-project
Bootstrap Cortex for a new project or import existing session history. Use when the user says 'set up Cortex', 'seed this project', 'import my history', 'backfill memories', 'bootstrap memory', 'initialize Cortex for this project', or when starting to use Cortex on an existing codebase that already has Claude Code conversation history.