Results for “salmon”

Optimizes Qdrant query performance for large limits across multiple shards by using Poisson-distributed subsampling to reduce inter-shard data transfer.

Generate XML configuration files and execute SSMA Console commands for Oracle to SQL Server database migration, including schema conversion and data migration.

Serve LLMs and VLMs on NVIDIA Jetson devices using vLLM or SGLang with optimized Docker containers and quantization presets.

SHARK v3.0 — SM Conviction + Liquidation Cascade Hunter. Consolidated from v1.0's 8-cron pipeline into a single scanner. 4-gate entry: SM concentration (30+ traders, 5%+) → top 5 trader alignment → price momentum → funding structure. Score 8+ to enter. DSL manages all exits. No thesis exit. DSL exit managed by plugin runtime via runtime.yaml.

Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats for market sizing.

GSAP Skill

Automates Slack team communication with bots, notifiers, and slash commands for alerts and workflow automation.

Use when SWMM integration, API development, or data synchronization is needed. This agent specializes in SWMM connectivity within the IntegrateForge AI ecosystem.

索隆（少年漫）认知与表达框架（压缩蒸馏）：路痴反差、三刀流执念、副船长担当 触发：海贼王 等。虚构；非暴力教唆

Run STORM phase 4 — article polishing. This skill should be used when the user asks to "polish the storm article", "finalize the article", or invokes /storm:polish. Adds a summary section, removes duplicate content, and verifies citation integrity.

Applies the TAM/SAM/SOM market sizing framework to guide decision-making, structure analysis, and produce actionable recommendations for product research.

Automates alert triage, IOC enrichment, containment actions, and incident response playbooks using Splunk SOAR (Phantom) to reduce manual analyst work and standardize response procedures.

Screen US equities for parabolic exhaustion patterns, generate conditional pre-market short plans, and monitor intraday trigger signals using 5-min bars.

Compute TAM/SAM/SOM with top-down and bottoms-up methods, plan survey sample sizes with per-segment minimums, and score candidate segments against Kotler's five criteria.

Integrate new data sources into SIEM platforms by configuring collectors, parsers, normalization, and validation for security monitoring.

Search SAM.gov for live notices matching a pursuit row (agency, incumbent, NAICS keywords) and save results to sam_scan.md. Use for admin monitor setup, presolicitation watch, or when user asks what is live on SAM for an expiring contract.

Explains MariaDB-specific SHOW statement syntax, including replication terminology, filtering rules, and diagnostic commands like SHOW EXPLAIN and SHOW ANALYZE.

LEMON v2.0 — The Degen Fader. Identifies historically reckless traders (DEGEN activity + CHOPPY consistency) on Hyperliquid, monitors their live positions, and counter-trades them when they're bleeding at high leverage. If a cluster of degens goes max-leverage long on a coin and starts losing, LEMON shorts it — betting on their inevitable liquidation cascade. DSL exit managed by plugin runtime via runtime.yaml.

Ableton Live Object Model (LOM) API reference for Python Remote Scripts and control surface development.

SQLAlchemy Python SQL toolkit and ORM with powerful query builder, relationship mapping, and database migrations via Alembic

Onboard a new small-business owner — connect their first two tools, run one recipe, interview them, store context, and set a weekly check-in.

Runs Stanford's STORM pipeline to produce Wikipedia-quality research articles with citations, using Claude models and a search engine API.

Post-train LLMs with reinforcement learning using the slime framework, which integrates Megatron-LM for training and SGLang for rollout generation.

SA-1B: Segment Anything 1 Billion Masks Dataset

SCORPION v2.0 — Altcoin Swarm Hunter. Detects coordinated risk-off events where 5+ altcoins simultaneously attract SM concentration, then trades the highest-conviction target within the swarm.

Embody Seth Godin's marketing and business philosophy to reframe challenges, define audiences, and overcome resistance to shipping.

Drive Soup (`soup-cli`), a CLI-first tool for fine-tuning and post-training LLMs with one YAML config and one command — SFT, DPO/GRPO/ORPO/SimPO/KTO, QLoRA/DoRA/LoRA+, layer streaming for 4-8 GB GPUs, eval-gated training, and serving. Use when the user wants to `soup init`/`soup train` a model, pick a training method or quantization scheme, estimate cost/memory before training, fine-tune on a small local GPU, migrate a config from Axolotl/LLaMA-Factory/Unsloth, or serve/merge/push a trained adapter. Triggers on: "soup-cli", "soup train", "soup init", "fine-tune an LLM locally", "QLoRA on a laptop GPU", "layer streaming", "soup advise", "soup autopilot", "DPO/GRPO/ORPO training", "merge LoRA adapter".

Unified search API across Google, Amazon, Yelp, OpenTable, Walmart, and more. Use when searching for products, local businesses, restaurants, shopping, images, news, or any web search. One API key, many engines.

Context compression for YAMTAM — nén JSON/structured tool output trước khi vào LLM. Hiệu quả với JSON (50-72% tiết kiệm); text thuần cần bản [all].

Provides a structured framework for making shipping and logistics decisions, covering carrier selection, international customs, fulfillment strategy, and claims handling.

Amazon Ads deep analysis covering Sponsored Products, Sponsored Brands (incl. Sponsored Brands Video), Sponsored Display (audiences + contextual), and basic Amazon DSP. Evaluates campaign structure, ACOS/TACOS targets, search-term harvesting, negative keyword discipline, Brand Analytics signals, day-parting, bid management, auto vs manual campaign mix, ASIN targeting, and DSP retargeting. Use when user says Amazon Ads, Amazon advertising, Amazon PPC, Amazon search ads, Sponsored Products, Sponsored Brands, Sponsored Display, Amazon DSP, ACOS, TACOS, retail media audit, Amazon Marketing Services, AMS, or Amazon seller advertising.

Evaluates how well internal model representations (hidden states) predict token-level information importance in summarization tasks, using NDCG@10 and Spearman's rank correlation.

Adds, fixes, and optimizes schema.org structured data (JSON-LD) for rich results, including validation and implementation guidance.

Covers MariaDB-specific SELECT syntax and behavior, including optimizer hints, LIMIT extensions, row locking, temporal queries, and file output.

Build Simulink models that co-simulate with Eclipse SUMO traffic simulator. Use when creating SUMO-Simulink co-simulation, traffic simulation, TraCI connection, vehicle-in-the-loop testing, or ADAS scenario validation with SUMO. Covers Server/Client setup, Reader/Writer/Actor block configuration, random traffic generation, ego vehicle control, and SUMO file creation. Also use when the user mentions SumoInterfaceLibrary, .sumocfg files, or wants to connect Simulink to an external traffic simulator.