Results for “crt-effects”

Generates synthetic CT volumes and masks using NVIDIA's rectified-flow pipeline for medical imaging research.

Calculates CRAP (Change Risk Anti-Patterns) scores for .NET methods by combining cyclomatic complexity with code coverage data from Cobertura XML reports.

Trains, evaluates, exports, prunes, quantizes, retrains, and runs inference for TAO OCRNet models for scene text recognition from cropped text-region images, supporting CTC and attention-based decoders.

Generate a complete Rust Model Context Protocol server project with tools, prompts, resources, and tests using the official rmcp SDK.

Creates structured Jira tickets from incident root cause analysis findings, including severity classification and remediation steps.

Audits nonprofit operations across impact measurement, fundraising, grant management, and donor retention, producing a prioritized fix plan.

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

Write React hooks with clean effect boundaries and measured memoization. Use when working with `useEffect`, custom hooks, refs, transitions, or hook dependency problems in React.

Detect and exploit Cross-Site Request Forgery vulnerabilities by testing for missing or predictable CSRF tokens, absent SameSite cookie attributes, and JSON endpoints accepting text/plain Content-Type, with payloads and bypass techniques for security testing.

Work with Effect v4 / effect-smol TypeScript code in this repo

Traces software supply chain provenance from source to runtime, identifying divergence points in dependency resolution, build, packaging, and release pipelines.

Multi-tiered memory management (HOT/WARM/COLD) for context compaction. Invoke ONLY for explicit compaction events: post-`/compact` cleanup, MEMORY.md tier promotion, archive batch, or "trim my context". NOT for general recall (use deep-recall) or routine memory writes (use storage-router). Triggers: "compact memory", "promote to durable", "archive old context", "tier this".

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.

Practical patterns for using fp-ts with React - hooks, state, forms, data fetching. Works with React 18/19, Next.js 14/15.

Instaura/atua em IRDR — Incidente de Resolucao de Demandas Repetitivas (CPC 976, requisitos simultaneos: I efetiva repeticao sobre questao unicamente de direito + II risco a isonomia/seguranca; legitimados 977; admissibilidade 981; suspensao no Estado/regiao 982 I; tese aplicada a todos e aos casos futuros 985; revisao 986; REsp/RE 987) ou IAC — Incidente de Assuncao de Competencia (CPC 947, questao relevante de grande repercussao social SEM repeticao; acordao vinculante §3), com efeito vinculante da tese (CPC 927 III). Use quando o operador disser IRDR, incidente de resolucao de demandas repetitivas, IAC, assuncao de competencia, tese vinculante regional, muitos processos iguais, suspensao por IRDR.

Provides practical patterns for using fp-ts with React, including hooks, state management, form validation, and data fetching.

Provides idiomatic React 18/19 patterns for hooks, server/client components, Suspense, error boundaries, forms, data fetching, state management, and accessibility-first composition.

Audits colour decisions on a screen for contrast ratios, palette coherence, semantic meaning, and accessibility, flagging deviations and recommending specific corrections.

Identify render hotspots, isolate expensive updates, and apply targeted React optimizations without changing UI behavior.

React 18/19 patterns including hooks discipline, server/client component boundaries, Suspense + error boundaries, form actions, data fetching, state management decision trees, and accessibility-first composition. Use when writing or reviewing React components.

Practical patterns for using fp-ts with React, covering hooks, state, forms, and data fetching for React 18/19 and Next.js 14/15.

Use when for crm audit.

Analisa os efeitos da revelia (CPC 344-346) e suas excecoes (345), tanto quando o cliente e o revel quanto quando a parte contraria e revel. Cobre a presuncao de veracidade dos fatos (344), as quatro hipoteses em que ela NAO opera (345 — litisconsorte contestante, direito indisponivel, falta de instrumento que a lei repute indispensavel, fatos inverossimeis/contraditorios com a prova), a fluencia de prazos sem intimacao (346) e a possibilidade de o revel ingressar e produzir prova. Use quando o operador disser revelia, reu revel, parte nao contestou, efeitos da revelia, presuncao de veracidade, ou meu cliente perdeu o prazo de defesa.

Practical patterns for using fp-ts with React - hooks, state, forms, data fetching. Works with React 18/19, Next.js 14/15.

Patterns for Bayesian inference in R using brms, including multilevel models, DAG validation, and marginal effects. Use when performing Bayesian analysis.

`task-agent`/`review-agent`: use when image layers, build context, runtime user, secrets, health checks, shutdown, or provenance change; skip when container behavior is unaffected.

Practical patterns for using fp-ts with React - hooks, state, forms, data fetching. Works with React 18/19, Next.js 14/15.

Use when support or CS is being asked to claim a share of net revenue retention, expansion or churn reduction, to work out what can honestly be attributed and what cannot. Trigger for "how much NRR can support claim", "prove support's revenue impact", "attribute retention to CS", support ROI for a board deck, or two teams claiming the same expansion.

Econometrics skill for panel data models. Activates when the user asks about: "panel data", "fixed effects", "random effects", "Hausman test", "within estimator", "between estimator", "two-way fixed effects", "clustered standard errors panel", "FE model", "RE model", "pooled OLS", "unobserved heterogeneity", "panel regression", "first difference estimator", "entity fixed effects", "time fixed effects", "面板数据", "固定效应", "随机效应", "豪斯曼检验", "双向固定效应", "面板回归", "个体效应", "时间效应", "一阶差分"

Recruit a channel or tech partner and actually activate them, not just sign them. It scores who fits, writes the mutual-value pitch in their terms, builds the enablement that makes them productive, and plans the first co-marketing or co-sell motion so the partnership produces something in the first quarter instead of going dark after the kickoff. Built for B2B partnerships teams, customizable to your CRM and your partner program. Trigger on "recruit a partner", "does this partner fit", "pitch a partnership", "activate a new partner", "partner enablement plan", "first co-marketing motion", or any partner recruiting or activation request.

Conversion Rate Optimization auditing for landing pages, signup flows, checkout funnels, forms, and CTAs. Identifies friction points, runs heuristic evaluations, produces prioritized recommendations using ICE/PIE frameworks. Use when the user asks about conversion optimization, funnel analysis, landing page audits, form optimization, CTA testing, or checkout improvement.

Provides idiomatic React 18/19 patterns for hooks, server/client components, Suspense, error boundaries, forms, data fetching, state management, and accessibility-first composition.

Practical patterns for using fp-ts with React: Option for optional state, Either for form validation, TaskEither for data fetching, and RemoteData for async state management.

Weekly churn risk detection across active client accounts. Scans for signals like decreased engagement, missed meetings, delayed payments, and competitor mentions. Scores risk 1-10 and outputs prioritized alert list.

Practical patterns for using fp-ts with React - hooks, state, forms, data fetching. Works with React 18/19, Next.js 14/15.