Results for “omero”

Manages microscopy image data on an OMERO server via the OMERO Python API (BlitzGateway) — access images, retrieve datasets, read pixel data, manage ROIs and annotations, and batch-process. Use when connecting to an OMERO server, pulling microscopy images or datasets, analyzing pixels, managing ROIs/annotations, or running high-content screening and microscopy workflows. Part of the AlterLab Academic Skills suite.

Train, evaluate, export, quantize, and run inference for a TAO OneFormer model that performs panoptic, instance, and semantic segmentation using task-conditioned queries.

Detects and triages explicitly-unbounded AEM queries (p.limit=-1 or setLimit(-1)) that cause OOMs, safely capping only where provably safe and escalating others for human pagination.

Enforce Kubernetes admission policies using OPA Gatekeeper with ConstraintTemplates, Rego rules, and the Gatekeeper policy library.

Manage and inspect OPA policies, Gatekeeper constraints, and Rego rules, including discovery, testing, and audit analysis.

Expert app store marketing specialist focused on App Store Optimization (ASO), conversion rate optimization, and app discoverability

Enforce organizational security policies across Kubernetes clusters and CI/CD pipelines using Open Policy Agent (OPA) and Gatekeeper, including writing Rego policies, deploying admission controllers, and testing policies locally.

Generate three alternative OKR sets for a team, aligned with company strategy, to spark strategic discussion and planning.

Framework core engineer skill for ORM conventions, schema annotations, query patterns, and cross-module data access contracts.

Apply the OKRs framework to structure analysis, guide decision-making, and improve outcomes in product research and strategic planning contexts.

Data pipeline specialist for ML experiments. Use when the user asks to talk to Gekko, requests the data engineer, or needs DataLoader optimization.

Enumerating failure modes via pre-mortem analysis. Systematically identifies failure scenarios for plans, designs, and features, scoring them with RPN/AP. Does not write code.

Orchestrate altering an existing, working feature to new desired behavior by updating tests first, then changing implementation, reviewing, and committing with gated approval.

Tracks team OKRs with quarter banner, objective columns, key result progress bars, owner avatars, and status pills.

Analisa a estrutura de páginas de marketing para melhorar a conversão, avaliando hierarquia, ordem das seções, posicionamento de CTA, sinais de confiança e pontos de atrito.

Governs unattended automation workflows with mandatory budgets, dry-run defaults, and a separate verification gate before any side effect.

Imported skill dmmono_ofl from anthropic

Solves single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including constraint handling, Pareto front analysis, and benchmark problems.

Provides a framework for solo entrepreneurs to run a one-person company using 14 integrated skills.

Correlates OT asset inventory with ICS-CERT advisories and CVE data to identify, prioritize, and track vulnerabilities in operational technology environments using Claroty xDome.

When to use ALO (fee-optimized) vs MARKET orders on Hyperliquid via Senpi, and standard order params for entry/exit/TP. Use when configuring execution.

基于流行 OKR 体系管理智能体目标（O）与关键结果（KR）。当用户提到目标管理、季度计划、OKR、关键结果、复盘、评分、经验沉淀时使用，并将信息维护到 memory/okr.md。

Observability and reliability engineer — SLOs, alerting, instrumentation, and incident response.

Multi-objective optimization with pymoo — NSGA-II, NSGA-III, MOEA/D, Pareto-front computation, constraint handling, and standard benchmarks (ZDT, DTLZ). Use when solving multi-objective or constrained optimization problems, computing Pareto-optimal trade-offs, or tackling engineering design problems with competing objectives. Part of the AlterLab Academic Skills suite.

Create OKRs (Objectives and Key Results) for teams and companies. TRIGGERS - Use when user wants OKRs, goal setting frameworks, or quarterly objectives.

Run the Ouroboros specification-first development loop: reduce ambiguity with a Socratic interview grounded in live git data (commits, churn, contributors), freeze an immutable seed/spec, render the execution plan through spec-kit (/speckit.plan → /speckit.tasks), execute against that contract through cli-anything agent-native CLI harnesses (cli-hub, --json evidence), verify before claiming success, and keep looping until completion is actually verified. Use when the user wants spec-first clarification, git-aware interviews, immutable requirements, drift-aware implementation, harness-driven execution, or a persistent completion loop that should keep going until tests / checks / acceptance criteria pass. Triggers on: ooo, ouroboros, interview, seed, run workflow, evaluate, evolve, ooo ralph, specification first, socratic interview, git-aware interview, ambiguity reduction, execution plan, cli harness execute, persistent completion.

Brainstorm team-level OKRs aligned with company objectives — qualitative objectives with measurable key results. Use when setting quarterly OKRs, aligning team goals with company strategy, drafting objectives, or learning how to write effective OKRs.

Framework de otimização multi-objetivo. NSGA-II, NSGA-III, MOEA/D, frentes de Pareto, tratamento de restrições, benchmarks (ZDT, DTLZ), para problemas de design e otimização em engenharia.

Expert guidance for OPA (Open Policy Agent), the CNCF policy engine for unified authorization across the stack. Helps developers write Rego policies for Kubernetes admission control, API authorization, infrastructure-as-code validation, and data filtering — enforcing security policies as code.

Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) specialist. Optimize content and websites to appear in AI-generated answers from ChatGPT, Perplexity, Claude, Google AI Overviews, and other LLM-powered search experiences. Use when the user asks about AI search optimization, AEO, GEO, AI Overviews, appearing in AI answers, LLM citations, or optimizing for generative search.

Create OKRs (Objectives and Key Results) for teams and companies. TRIGGERS - Use when user wants OKRs, goal setting frameworks, or quarterly objectives.

Mem0 Platform SDK for adding persistent memory to AI applications. TRIGGER when: user mentions "mem0", "MemoryClient", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python SDK (mem0ai), TypeScript SDK (mem0ai), and framework integrations (LangChain, CrewAI, OpenAI Agents SDK, Pipecat, LlamaIndex, AutoGen, LangGraph). Also covers the open-source self-hosted Memory class. This is the DEFAULT mem0 skill for ambiguous queries. DO NOT TRIGGER when: user asks about CLI commands, terminal usage, or shell scripts (use mem0-cli), or Vercel AI SDK / @mem0/vercel-ai-provider / createMem0 (use mem0-vercel-ai-sdk).

Socratic deep interview with mathematical ambiguity gating before explicit execution approval

Implement and debug network requests, API calls, and data fetching in Expo apps using fetch, React Query, SWR, Expo Router loaders, caching, and offline support.

Federal Organizational Conflict of Interest (OCI) sweeper backed by FAR Subpart 9.5 (9.501-9.508) and the active Theseus workspace knowledge graph. USE WHEN the user asks about OCI risk on a bid, organizational conflicts, incumbent conflicts, biased ground rules, unequal access to information, impaired objectivity, or any pre-bid OCI due diligence. Pulls `company`, `incumbent`, `subcontractor`, `customer`, `program_office`, and prior-contract relationships from the workspace KG, classifies each potential conflict into one of the three FAR 9.505 classes (biased ground rules, unequal access, impaired objectivity), and emits a structured findings envelope with mitigation recommendations (firewall, NDA, recusal, novation). DO NOT USE FOR FAR clause coverage audit (use `compliance-auditor`), proposal prose (use `proposal-generator`), competitor research (use `competitive-intel`), or pricing (use `price-to-win`).