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Found 2,123 Skills
Bitcoin bottom-timing judgment model. By tracking 6 core indicators (RSI technical oversold, volume dry-up, MVRV ratio, social media fear index, miner shutdown price, long-term holder behavior), it comprehensively evaluates whether Bitcoin has entered a bottom-fishing zone and outputs a bottom-fishing rating and position-building recommendations. When users mention topics such as Bitcoin bottom-fishing, whether BTC has bottomed out, Bitcoin oversold, MVRV, miner shutdown price, long-term holder LTH, Bitcoin fear index, whether to buy Bitcoin, BTC position entry timing, crypto market bottom signals, Bitcoin cycle bottom, etc., be sure to use this skill. Even if the user simply asks "Can I buy the dip on Bitcoin now?" or "Has BTC finished dropping?", this skill should be triggered to provide a structured analysis framework.
Decision-first data analysis with statistical rigor gates. Use when analyzing CSV, JSON, database exports, API responses, logs, or any structured data to support a business decision. Handles: trend analysis, cohort comparison, A/B test evaluation, distribution profiling, anomaly detection. Do NOT use for codebase analysis (use codebase-analyzer), codebase exploration (use explore-pipeline), or ML model training.
Resolve PR review feedback by evaluating validity and fixing issues in parallel. Use when addressing PR review comments, resolving review threads, or fixing code review feedback.
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
Design and operate reconciliation processes that ensure data accuracy across portfolio management custodian and clearing systems. Use when building or evaluating a daily position cash or transaction reconciliation process, investigating discrepancies between internal systems and custodian records, diagnosing recurring break patterns especially from corporate actions or pricing differences, setting tolerance thresholds for position cash or market value matching, implementing three-way reconciliation across advisor system custodian and clearing firm, designing break investigation workflows with aging and escalation, normalizing data across multi-custodian feeds from Schwab Fidelity or Pershing, reconciling cost basis tax lots or accrued income across systems, evaluating reconciliation platforms like Arcesium Duco or Advent Geneva, or preparing for regulatory examinations on books and records accuracy.
Time-boxed technical investigation with structured output. Use for feasibility studies, architecture exploration, integration assessment, performance analysis, or risk evaluation. Creates spike tasks in ohno, enforces time-boxing, generates spike reports, and creates actionable follow-up tasks.
Guide for creating agent skills that follow the Agent Skills specification. Use when user wants to create, write, draft, or improve a skill. Covers structure, description optimization, progressive disclosure, scripts, and evaluation.
Apply pragmatist philosophy (Peirce, James, Dewey) to frame knowledge as instrumental for action, evaluate ideas by their practical consequences, and conduct inquiry as problem-solving. Use this skill when the user needs to bridge theory and practice, evaluate competing theories by their usefulness, employ abductive reasoning to generate hypotheses, or when they ask 'which theory is more useful here', 'how do I move from abstract ideas to actionable knowledge', or 'what practical difference does this distinction make'.
Apply public choice theory to analyze political decision-making as rational self-interested behavior. Use this skill when the user needs to evaluate government policy failures, rent-seeking costs, voting outcomes, or bureaucratic incentives, especially when the assumption of benevolent government is questionable.
Respond to review comments on a PR after evaluation and fixes
Grill the diff. Specialists evaluate every finding internally — only high-value findings reach the user for discussion until reaching shared understanding.
Use this skill whenever users want to build, inspect, debug, automate, or publish workflows in Agentforce Grid (AI Workbench) using Salesforce plus the Grid MCP or direct Grid REST calls. Trigger it for Grid workbook creation, worksheet setup, Object/Reference/AI/Agent/AgentTest/Evaluation/PromptTemplate/InvocableAction column design, prompt drafting inside Grid, worksheet execution troubleshooting, Grid YAML `apply_grid` specs, and Windows-specific Grid setup issues. Also use it when users mention AI Workbench, Grid Studio, workbook IDs, worksheet IDs, Grid Connect, or ask for recipes like "top opportunities with AI email drafts", "agent test suite in Grid", or "build this worksheet from YAML". Do not use it for generic Salesforce work unrelated to Agentforce Grid.