Results for “asplos”

Comprehensive guide for writing systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. Provides paragraph-level structural blueprints, writing patterns, venue-specific checklists, reviewer guidelines, LaTeX templates, and conference deadlines. Use this skill for all systems conference paper writing.

Identify AWS IAM privilege escalation paths by analyzing policies for dangerous permission combinations and least-privilege violations using boto3 and Cloudsplaining-style analysis.

Perform CRUD operations, run queries, and manage containers on Azure Cosmos DB NoSQL API using the Python SDK.

Walks users from a bare AKS cluster to a running AI model deployment, covering cluster verification, controller install, GPU assessment, provider setup, and first deployment.

Access USPTO APIs for patent and trademark searches, examination history (PEDS), assignments, citations, office actions, and trademark status (TSDR). Use when searching patents or trademarks, conducting prior art searches, retrieving patent examination or assignment records, or doing intellectual property (IP) analysis. Part of the AlterLab Academic Skills suite.

Audit Azure Blob and ADLS storage accounts for public access exposure, weak or long-lived SAS tokens, missing encryption at rest, disabled HTTPS-only traffic, and outdated TLS versions using the azure-mgmt-storage Python SDK.

Manages and analyzes Azure Kubernetes Service clusters via Azure CLI, covering node pools, addons, upgrades, and health diagnostics.

Build forensic super timelines from disk images using Plaso (log2timeline) and triage them in Timesketch.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Process tabular data with Polars' expression API, lazy evaluation, and parallel execution for fast in-memory analysis and pandas migration.

Automate Apollo.io lead generation: search organizations, discover contacts, enrich prospect data, manage contact stages, and build targeted outreach lists using natural language commands.

Process data with high-performance DataFrames using Polars' expression-based API, lazy evaluation, and parallel execution for ETL, analytics, and pandas migration.

Configures memory protection mechanisms including DEP, ASLR, CFG, and Windows Exploit Protection to harden endpoints against buffer overflows, ROP chains, and code injection.

Perform high-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames, including overlap, nearest, merge, coverage, complement, subtract, and reading/writing BED, VCF, BAM, GFF, FASTA, and FASTQ formats with streaming and cloud-native support.

Use when planning an IPSN-lineage project timeline from track/venue selection through the CPS-IoT Week deadline, double-blind submission, deployment and hardware logistics, rebuttal, the Best Research Artifact Award, and the dual ACM/IEEE camera-ready — with honest handling of the fact that IPSN merged into SenSys.

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

Provides expert guidance for fast fine-tuning with Unsloth, including LoRA/QLoRA optimization, with 2-5x faster training and 50-80% less memory usage.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls, and potential data exfiltration using statistical baselines.

Plan, create, and configure production-ready Azure Kubernetes Service (AKS) clusters. Covers Day-0 checklist, SKU selection (Automatic vs Standard), networking options (private API server, Azure CNI Overlay, egress configuration), security, and operations (autoscaling, upgrade strategy, cost anal...

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

Identify and remediate Amazon S3 bucket misconfigurations that expose sensitive data, including enabling Block Public Access, auditing policies and ACLs, enforcing encryption, configuring access logging, and deploying automated remediation with AWS Config and Lambda.

Provides expert guidance for fine-tuning LLMs with Axolotl, covering YAML configs, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, and multimodal support.

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

Post-process AI-generated text through the unslop CLI to strip AI writing patterns before publishing

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Bulk-create or update display names and descriptions for subscriptions, subscription groups, and in-app purchases across all App Store Connect locales using the asc CLI, eliminating manual per-language entry.

rustls — modern, safe TLS implementation in pure Rust. Drop-in replacement for OpenSSL/native-tls in Rust apps. No C dependencies — perfect for mobile cross- compile and embedded targets. Covers ClientConfig + ServerConfig, certificate verification with webpki-roots, mTLS, custom verifier (cert pinning), ALPN negotiation (HTTP/2, HTTP/3), session resumption, integration with hyper + reqwest + tokio. USE WHEN: user mentions "rustls", "ClientConfig", "ServerConfig", "webpki-roots", "rustls-pemfile", "rustls cert pinning", "rustls mTLS", "rustls Tokio", "rustls hyper" DO NOT USE FOR: OpenSSL specifics - use OpenSSL skill (or platform TLS) DO NOT USE FOR: Apple/Windows native TLS - use platform-specific skills DO NOT USE FOR: Tor anonymous transport - use `network/arti` DO NOT USE FOR: TLS protocol theory - use OWASP / RFC docs

Fast in-memory DataFrame analytics with Polars — lazy evaluation, parallel execution, and an Apache Arrow backend for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory, for 1-100GB datasets, ETL pipelines, or a faster pandas replacement. For larger-than-RAM data prefer dask or vaex. Part of the AlterLab Academic Skills suite.

High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.