Results for “camel”

Test-driven development for Quarkus 3.x LTS using JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo. Use when adding features, fixing bugs, or refactoring event-driven services.

Provides Quarkus 3.x architecture patterns for building cloud-native, event-driven services with Apache Camel, covering REST APIs, CDI services, data access with Panache, async processing, and logging.

Trains, evaluates, exports, and runs inference for person re-identification models using TAO, learning discriminative embeddings for cross-camera matching.

Create and manage Kubernetes workloads with declarative YAML manifests, covering deployments, networking, security, storage, Helm charts, and troubleshooting.

Quarkus 3.x LTS 架构模式——Camel 消息、RESTful API 设计、CDI 服务、数据访问、响应式管道及可观测性

Cancel any active OMX mode (autopilot, ralph, ultrawork, ecomode, ultraqa, swarm, ultrapilot, pipeline, team)

Safety guardrails for autonomous agents. Intercepts destructive actions and vets skills, requires structured approval before irreversible operations, with CLI-backed cryptographic audit trails and policy enforcement.

Cancel any active OMX mode (autopilot, ralph, ultrawork, ecomode, ultraqa, swarm, ultrapilot, pipeline, team)

Trains, evaluates, and runs inference for Mask Auto-Label (MAL) weakly-supervised segmentation models using ViT-MAE backbones with minimal point or box annotations.

Train, evaluate, export, and run inference on TAO action-recognition models for classifying temporal actions in video clips using RGB, optical flow, or joint input.

Chameleon: Mixed-Modal Early-Fusion Foundation Models

Use when planning a COLM submission campaign across the calendar — working backward from the late-March abstract and paper deadlines through the May-June rebuttal, July decisions, August camera-ready, and October conference, coordinating co-authors, compute, and reciprocal-reviewing duties, and slotting COLM into a multi-venue LM-research pipeline.

Embody the voice and methodology of Jim Carrey, using his signature techniques for vivid, committed communication.

Cancel any active OMC mode (autopilot, ralph, ultrawork, ultraqa, swarm, ultrapilot, pipeline, team)

JACKAL — First Jump pyramider. FOX v1.6's exact five-layer entry gauntlet combined with RHINO's pyramiding mechanic. Enter at 30% on a qualifying First Jump, add 40% at +10% ROE and final 30% at +20% ROE — but only after re-validating 4h trend, SM alignment, and volume. Failed scouts cost $15 instead of FOX's $50. Full pyramids capture the same upside. DSL High Water Mode (mandatory).

Drive Palmier Pro, an open source AI-native macOS video editor (Swift, SwiftUI/AppKit, AVFoundation) that exposes its timeline as an MCP server at `http://127.0.0.1:19789/mcp` so Claude Code/Desktop, Cursor, or Codex can read and edit a project's tracks, clips, media, transcript, captions, color/effects, and trigger generative AI (video/image/audio) requests side-by-side with a human editor. Use when the user wants to connect an agent to Palmier Pro's MCP server, call its timeline/clip/media/generation tools (`get_timeline`, `add_clips`, `move_clips`, `generate_video`, ...), build/run/test the Swift app from source, or debug the MCP tool surface in `ToolDefinitions.swift`/`ToolExecutor+*.swift`. Triggers on: "palmier pro", "palmier-pro", "AI video editor MCP", "connect Claude to my video editor", "palmier MCP server", "edit my timeline with an agent", "swift build PalmierPro", "palmier-pro mcpb", "manage_project"/"get_timeline"/"add_clips" tool.

YAML configuration for CI/CD, Docker Compose, and Kubernetes.

Packages and deploys Kubernetes applications with Helm, including charts, templates, and releases.

DeepEval — LLM evaluation framework, RAG metrics, hallucination detection, red-teaming, CI/CD integration

Use when masking columns or coordinate ranges in multiple-sequence alignments before downstream HMMER or alignment-processing steps.

Benchmarks LLM bias by scoring responses to automatically generated open-ended questions across sensitive attributes, producing a composite fitness score from 0 to 5.

Read, search, post, and engage with X/Twitter from the command line using cookie-based authentication.

Per-channel skip-existing checks in Snakemake wrapper scripts for resuming interrupted SLURM jobs. Trigger: Snakemake interrupted job, skip existing channels, resume incomplete cycle, sentinel missing but outputs exist, per-channel completeness check, wrapper script resume logic.

Use when running QA Lab channel message flow evidence.

Imported skill claude from vercel

Computational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.

Run OpenClaw remote validation on Linux, macOS, or Windows via the Crabbox or Testbox wrapper, reporting the actual provider and lease id.

Pitfalls, examples, and edge cases for Hermes Kanban workers. The lifecycle itself is auto-injected into every worker's system prompt as KANBAN_GUIDANCE (from agent/prompt_builder.py); this skill is what you load when you want deeper detail on specific scenarios.

Benchmarks large audio-language models against adversarial audio attacks using the CAA dataset, computing WER, ROUGE-L, cosine similarity, and coherence scores to assess robustness in conversational settings.

BALD EAGLE v3.0 — XYZ Alpha Hunter (Hardened). Focused on 6 high-liquidity XYZ assets: CL, BRENTOIL, GOLD, SILVER, SP500, XYZ100. Conviction-scaled leverage (5-10x based on score). Wider DSL for macro assets. Maker-only execution. Scanner calls create_position internally. v3.0: focused assets, conviction-scaled leverage, XYZ-tuned DSL, no thesis exit.

Computational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.

Provides detailed guidance on Hermes Kanban worker lifecycle, including workspace handling, handoff patterns, retry diagnostics, and edge cases for dispatched workers.