「collect」の検索結果

Command-line interface for Obs Studio - A stateful command-line interface for OBS Studio scene collection editing, following the same patter...

日本語の概要は準備中です。原文の説明を表示しています。

Command-line interface for ChromaDB - A stateless CLI for managing vector database collections, documents, and semantic search. Designed for AI agents and automation via the ChromaDB HTTP API v2.

日本語の概要は準備中です。原文の説明を表示しています。

Command-line interface for Obs Studio - A stateful command-line interface for OBS Studio scene collection editing, following the same patter...

日本語の概要は準備中です。原文の説明を表示しています。

Calculates sample sizes and statistical power for study planning. Applies when someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for complex designs — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Also handles requests that only mention an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-analysis.

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Provides access to a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.

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Manages Zotero reference libraries using the pyzotero Python client: retrieves, creates, updates, and deletes items, collections, tags, and attachments via the Zotero Web API v3 or local API. Applies when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.

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Queries and downloads public cancer imaging data from NCI Imaging Data Commons. Supports IDC collection discovery, DICOM access, radiology (CT, MR, PET) and pathology AI datasets, metadata SQL, visualization, licensing, and citations. Uses public metadata and download routes without authentication; optional BigQuery and Google Healthcare routes require Google credentials.

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Manages biological datasets and models with LaminDB, including artifact registration, lineage tracking, schema validation, Bionty ontology annotation, query/search, collections, branches, storage, and workflow integrations. Use for reproducible biological data curation or a LaminDB lakehouse.

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Python observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.

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Debug complex issues using competing hypotheses with parallel investigation, evidence collection, and root cause arbitration. Use this skill when debugging bugs with multiple potential causes, performing root cause analysis, or organizing parallel investigation workflows.

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CommunityToolkit.Mvvm Messenger pub/sub for decoupled communication between ViewModels (or any objects). Covers WeakReferenceMessenger vs StrongReferenceMessenger, IRecipient<TMessage>, RequestMessage<T> / AsyncRequestMessage<T> / CollectionRequestMessage<T>, ValueChangedMessage<T>, channels (tokens), and the ObservableRecipient activation lifecycle. Use across WPF, WinUI 3, .NET MAUI, Uno, and Avalonia.

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Draft a PR body from OMC's paper trail — the smallest visual that proves the change, evidence consumed from the verify protocol (never re-collected), reversibility from the ADR test on the diff, glossary language throughout.

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Debug hanging issues in SGLang distributed inference (TP/PP/DP/EP). Covers identifying hang locations via py-spy/watchdog/cuda coredump, per-rank logging to find state divergence, binary-search methodology for locating the first diverge point, and fix patterns. Use when a multi-GPU SGLang run hangs, freezes, or times out during collective operations.

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Core technical indicator collection (trend EMA/ADX + mean-reversion BB/RSI + volume-price OBV/volume ratio), generates a composite signal via three-dimensional voting. Pure pandas implementation for any OHLCV data.

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Detects container escape at runtime across tooling - namespace manipulation, capability abuse, kernel exploits, sensitive host mounts, and anomalous syscalls - and explains which signals matter regardless of whether Falco, Sysdig, auditd, or an EDR is doing the collection. Use when deciding what breakout behaviour to monitor, investigating a suspected Docker or Kubernetes breakout, or comparing escape coverage across runtime sensors. Keywords: container escape, breakout, namespaces, CAP_SYS_ADMIN, privileged, hostPath, kernel exploit, syscall. Do not use for Falco rule syntax itself - use detecting-container-escape-with-falco-rules; for a static configuration sweep use performing-container-escape-detection.

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Conduct internal Active Directory reconnaissance using BloodHound Community Edition's graph database with the SharpHound (AD) and AzureHound (Entra ID) collectors, mapping ACLs, sessions, and group memberships into attack paths from a low-privileged foothold to Domain Admin. Use after an initial AD foothold to identify privilege escalation chains, or to validate that AD hardening closed known attack paths.

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Conduct external recon using OSINT techniques to map an organization's external attack surface without touching target systems, gathering DNS records, certificate transparency logs, search results, social media, code repositories, and breach databases into a target profile. Use for the passive info-gathering phase of a pentest, external footprinting, or collecting employee/email intel for a social engineering campaign.

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Build automated IOC enrichment pipelines in Splunk Enterprise Security by ingesting threat feeds into KV Store collections and correlating them against security events via lookup tables, modular inputs, and the Threat Intelligence Framework. Use when wiring threat intel into Splunk correlation searches to flag IOC matches and cut SOC triage time.

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Design and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment workflows, STIX/TAXII interoperability, and analyst dashboards. Use when architecting or standing up a centralized CTI platform to collect, analyze, and disseminate threat intelligence across a security team.

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Build threat actor profiles by collecting OSINT from vendor reports, paste sites, dark web forums, social media, and code repos, correlating indicators, mapping adversary infrastructure with tools like Maltego and SpiderFoot, and producing structured dossiers of motivations, capabilities, infrastructure, and TTPs. Use when performing attribution or building an adversary dossier from open-source intelligence.

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Conducts security testing of REST, GraphQL, and gRPC APIs to identify vulnerabilities in authentication, authorization, rate limiting, input validation, and business logic. The tester uses the OWASP API Security Top 10 as the testing framework, combining Burp Suite interception with Postman collections and custom scripts to test endpoint security at every privilege level. Activates for requests involving API security testing, REST API pentest, GraphQL security assessment, or API vulnerability testing.

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Parse Windows LNK shortcut files to extract target paths, MAC timestamps, volume serial numbers, and machine identifiers for forensic timeline reconstruction. Use when investigating recently-accessed files, tracking removable media or network paths referenced by shortcuts, or building a DFIR timeline from LNK artifacts.

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Parse Windows Prefetch files (versions 17, 23, 26, 30) with tools like PECmd, WinPrefetchView, or python-prefetch to determine program execution history, including run counts, execution timestamps, and referenced files/DLLs. Use when building a timeline of program execution on a Windows system, confirming whether a suspicious binary ran, or correlating execution evidence with other forensic artifacts during an investigation.

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Builds an automated malware submission and analysis pipeline that collects suspicious files from endpoints and email gateways, submits them to sandbox environments and multi-engine scanners, and generates verdicts with IOCs for SIEM integration. Use when SOC teams need to scale malware analysis beyond manual sandbox submissions for high-volume alert triage.

日本語の概要は準備中です。原文の説明を表示しています。