Results for “spa”

Prüft Fristen, Form, Zuständigkeit, Rechtsweg und Sofortmaßnahmen bei Energie-Transaktionen und Due Diligence; liefert eine Fristen- und Risikoampel mit Sofortschritten.

Store, query, and export genomic variant data (VCF/BCF) using TileDB's sparse array technology for scalable population genomics workflows.

Spawns a researcher agent to investigate how to implement a project phase, gathering context on architecture patterns, standard libraries, and common pitfalls.

Runs chest X-ray reasoning smoke tests using the NV-Reason-CXR-3B model via local inference or a public Hugging Face Space API.

Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page.

Search X/Twitter profiles, tweets, trends, lists, communities, and Spaces through the AIsa relay, then support approved posting workflows with OAuth. Use when the user asks for Twitter research, monitoring, or posting without sharing passwords.

Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.

Search X/Twitter profiles, tweets, trends, lists, communities, and Spaces through the AISA relay, then publish approved posts with OAuth. Use when: the user asks for Twitter/X research, monitoring, or posting without sharing passwords. Supports read APIs, authorization links, and media-aware posting.

Searches and reads X (Twitter): profiles, timelines, mentions, followers, tweet search, trends, lists, communities, and Spaces. Publishes posts, likes/unlikes tweets, and follows/unfollows users after the user completes OAuth in the browser. Use when the user asks for Twitter/X research, social listening, posting, or account interactions without sharing account passwords.

Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

Use to reconstruct what actually happened to one customer across every conversation, channel and handoff, for an escalation, complaint, post-mortem or goodwill decision. Trigger for "build a timeline for this customer", "what happened on this case", "summarize the back-and-forth before I decide", "when were they first told", escalation summaries, complaint investigations, or a case spanning several tickets.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.