Results for “radixattention”

Reclaim DRAM on NVIDIA Jetson devices by disabling unused display, camera, and DMA subsystems across MB1 BCT, MB2 BCT, kernel reserved-memory, and SWIOTLB layers for headless or no-camera deployments.

Econometrics skill for Regression Discontinuity Design (RDD). Activates when the user asks about: "regression discontinuity", "RDD", "RD design", "sharp RDD", "fuzzy RDD", "running variable", "forcing variable", "cutoff", "bandwidth selection", "local linear regression", "McCrary test", "density test", "RDROBUST", "continuity assumption", "donut hole RDD", "geographic RDD", "断点回归", "回归不连续", "运行变量", "截断值", "带宽选择", "精确断点", "模糊断点", "密度检验", "局部线性回归"

Redis caching patterns, pub/sub, sessions, rate limiting, and data structures.

Systematically investigate all persistence mechanisms on Windows and Linux systems to identify how malware survives reboots and maintains access.

Quick reference for Redis best practices across common backend use cases, including caching strategies, rate limiting, distributed locks, pub/sub, streams, and connection management.

Save information to persistent memory for cross-session recall. Stores preferences, conventions, decisions, and context.

Redis in-memory data store. Covers data structures, caching, and pub/sub. Use for caching and real-time features. USE WHEN: user mentions "redis", "caching", "session storage", "rate limiting", "pub/sub", "sorted sets", "in-memory database", "cache invalidation" DO NOT USE FOR: relational data - use `postgresql` or `mysql` instead, document storage - use `mongodb` instead, full-text search - use `elasticsearch` instead

Designs and implements data retention schedules compliant with GDPR Article 5(1)(e) storage limitation principle. Maps data categories to retention periods with legal basis justification, regulatory minimum holding periods, and automated review triggers for schedule maintenance. Activate for retention policy, storage limitation, data lifecycle, retention period queries.

Implements financial records retention requirements across EU directives (5-7 years), SOX Section 802 (7 years), MiFID II (5-7 years), tax records, payment data, and AML obligations under AMLD. Maps financial data categories to statutory retention periods with cross-jurisdictional reconciliation. Activate for financial retention, SOX records, MiFID retention, AML retention, tax record keeping queries.

Store and inspect source-indexed proof material extracted from papers, notes, PDFs, or LaTeX sources. Use when Codex needs stable material IDs, source locations, reusable abstractions, proof skeletons, tags, and public attribution before any proof ideas are cooked into proof-usage.

Recommends careful DDAVP and fluid intake titration including frequent weighing and serum sodium level monitoring for adipsic diabetes insipidus. Use when managing adipsic DI requiring fluid balance management.

Capture durable project memory from work, debates, debugging discoveries, learned conventions, deferred options, and session outcomes. Load when the user says remember this, save this learning, record what happened, update project memory, or preserve context for future agents.

Investigate retention patterns, cohorts, drivers, warning signs, and intervention options.

Redis data structure patterns, caching strategies, distributed locks, rate limiting, pub/sub, and connection management for production applications.

Save the current diagnosis state to disk for cross-session recall, including conclusions, rejected directions, and next steps.

Use when converting completed work into durable knowledge. This skill provides a systematic process for extracting lessons learned, patterns, and insights from completed work and storing them in memory systems (PARA, Gigabrain, OpenStinger) for future reuse.

Manage Convex table retention policies, TTL fields, cleanup crons, and schema classification for ClawHub.

Scaffold, install, and compose shadcn-vue components built on Reka UI v2, including Vue variants, form patterns with vee-validate/Zod, and adaptation of existing components.

Use to review how call recordings are notified, stored, accessed, redacted and deleted, including the parts that differ from text conversations. Trigger for "review our call recording practices", "do we need to tell customers we're recording", "who can listen to our calls", recording retention, card details spoken on a call, or a request for a customer's own recording.

Train reinforcement learning agents using PPO, SAC, DQN, TD3, DDPG, and A2C algorithms with a scikit-learn-like API. Supports custom Gymnasium environments, vectorized environments, callbacks, and model persistence.

Check post-launch traction for a shipped VARD app and recommend iterate, graduate, or archive

Enforces identity-based network access with 802.1X, RADIUS authentication, dynamic VLAN assignment, and endpoint posture assessment using PacketFence.

Operate and extend NanoClaw v2, a zero-dependency session-aware REPL built on Claude's -p mode.

REJESTR KONFIGURACJI (ConfigReg) platformy Soneta (enova365, Triva) od strony kodu C#: drzewo węzłów, providery `IConfigRegProvider` (Root/Module/Table/Row/SubRow/SubTable/Storage/Addins), atrybut `[ConfigReg(Hide/Ignore/Include/ChildrenType)]`, format `*.reg.json`, potok Loader → Differ/Merger → SessionUpdater. Używaj ZAWSZE gdy użytkownik: (1) pyta o rejestr konfiguracji, ConfigReg, `Soneta.Config.Reg`, tabelę `ConfigRegistry` lub menu „Zarządzanie konfiguracją"; (2) chce włączyć/wyłączyć tabelę, kolumnę lub węzeł z rejestru (`Ignore`, `Hide`, `Include`, `ChildrenType`); (3) pisze provider rejestru, obsługę zapisu (`SaveChild`, `delayed`), porównywanie (`ConfigRegDiffer`), scalanie (`ConfigRegMerger`), serializację (`RegConfigJsonConverter`); (4) buduje lub debuguje `*.reg.json` — sigile `$strict`, `$v`, `#klucz`, `@atrybut`, `$blob`, ścieżki `Business/FeatureDefs/Name=CECHA`; (5) przenosi ustawienia między bazami przez rejestr. Import/eksport przez XML (`dbinit.xml`) to INNY mechanizm → /soneta-config.

Python resilience patterns including automatic retries, exponential backoff, timeouts, and fault-tolerant decorators. Use when adding retry logic, implementing timeouts, building fault-tolerant services, or handling transient failures.

Use when tuning RL reward function weights, fixing reward hacking, or addressing P&L gradient issues

Keep sessions focused and efficient — prune stale outputs, preserve active state, recommend compaction

Stores verified cross-session facts, decisions, preferences, and open questions without secrets, speculation, or monitoring.

Renders videos and still images from Remotion compositions using the CLI, with guidance on transparent output.