Results for “partitioning”

Guides scaling Qdrant for multi-tenant workloads using payload partitioning, custom sharding, and tiered multitenancy.

`task-agent`: use when document, key-value, wide-column, or graph storage changes access, partitioning, consistency, or evolution; skip vendor-only mentions and unchanged storage.

Design and enforce microsegmentation policies using workload identity and label-based rules to prevent lateral movement in zero trust architectures, with guidance for tools like VMware NSX, Illumio, and Calico.

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Design and implement network segmentation using firewall security zones, VLANs, ACLs, and microsegmentation policies to restrict lateral movement and enforce least-privilege network access.

Splits information-dense Anki cards into atomic units via AnkiConnect, with dry-run preview and apply modes.

Designs and implements VLAN-based network segmentation on managed switches to isolate network zones, enforce access control between segments, and reduce the attack surface by limiting lateral movement paths in enterprise network environments.

Process data partitioner operations. Auto-activating skill for Data Pipelines. Triggers on: data partitioner, data partitioner Part of the Data Pipelines skill category. Use when working with data partitioner functionality. Trigger with phrases like "data partitioner", "data partitioner", "data".

Towards Open-World Segmentation of Parts

Configure and distribute creator fees to multiple shareholders using the PumpFees program with BPS-based share allocation, admin management, and cross-program fee consolidation for graduated tokens.

Split a large pull request into multiple smaller PRs to reduce the number of required CODEOWNERS reviewer groups.

Diagnoses Qdrant capacity needs and guides horizontal scaling decisions, including node count, shard count, replication factor, and resharding trade-offs.

Optimizes Qdrant query performance for large limits across multiple shards by using Poisson-distributed subsampling to reduce inter-shard data transfer.

Diagnose and optimize slow-loading, high-memory, or low-FPS USD scenes using a structured workflow with profiling, validation, and mutation phases.

Harden container images by minimizing attack surface, removing unnecessary packages, implementing multi-stage builds, configuring non-root users, and applying CIS Docker Benchmark recommendations.

阶段③ 任务划分。把 design.md 拆成 tasks/<模块>.md 和 tasks/progress.md。

Scales pandas and NumPy workflows to datasets larger than memory using parallel and distributed computing, with support for dataframes, arrays, bags, and custom task graphs.

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Provides expertise in containerization technology, covering container creation, orchestration integration, security hardening, and operational best practices for production workloads.

BluOS CLI (blu) for discovery, playback, grouping, and volume.

Splits large markdown documents into smaller, organized files based on level 2 (default) sections. Use if the user says perform shard document

Splits large markdown documents into smaller, organized files based on level 2 (default) sections. Use if the user says perform shard document

Server management principles and decision-making. Process management, monitoring strategy, and scaling decisions. Teaches thinking, not commands.

Design and implement network segmentation in Operational Technology environments using VLANs, industrial firewalls, data diodes, and software-defined networking, following the Purdue Model and IEC 62443 standards.

Computação paralela/distribuída. Escale pandas/NumPy além da memória disponível, DataFrames/Arrays paralelos, processamento multi-arquivo, grafos de tarefas, para datasets maiores que RAM e workflows paralelos.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Wilkinson, branchline, ratrace, directional couplers, corporate dividers, Rotman lenses for power splitting and beam-forming. TRIGGER: user asks to design, create, or analyze any coupler, splitter, power divider, combiner, or Rotman lens. Invoke BEFORE writing code — class names and design() availability vary per coupler type. SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), building custom non-catalog geometry (use matlab-assemble-pcb-layout), material/stackup setup only (use matlab-manage-pcb-material), cascading multiple components (use matlab-integrate-pcb-circuit).

Exploit privileged pods, host mounts, runC CVEs, and exposed Docker sockets to break out of a container and reach the underlying host during authorized container-security assessments.

Use this when the team needs to decide how responsibilities should be split across services, modules, workers, APIs, or runtimes. Trigger on requests about service boundaries, ownership, modularity, monolith versus separation, or where logic should live.

Scans macOS or Windows disk usage with read-only commands, categorizes large items into auto-cleanable, manual-review, and cautious tiers, and generates an interactive HTML report with one-click deletion via a local web server.

Ship workflow: detect + merge base branch, run tests, review diff, bump VERSION, update CHANGELOG, commit, push, create PR. Use when asked to "ship", "deploy", "push to main", "create a PR", "merge and push", or "get it deployed". Proactively invoke this skill (do NOT push/PR directly) when the user says code is ready, asks about deploying, wants to push code up, or asks to create a PR. (gstack)