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Found 1,954 Skills
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.
Run the Ouroboros specification-first development loop: reduce ambiguity with a Socratic interview, freeze an immutable seed/spec, execute against that contract, verify before claiming success, and keep looping until completion is actually verified. Use when the user wants spec-first clarification, immutable requirements, drift-aware implementation, or a persistent completion loop that should keep going until tests / checks / acceptance criteria pass. Triggers on: ooo, ouroboros, interview, seed, run workflow, evaluate, evolve, ooo ralph, specification first, socratic interview, ambiguity reduction, persistent completion.
Evaluate test coverage and fill real gaps with high-value tests.
Reviews Forge apps for security vulnerabilities, architecture issues, cost inefficiencies, performance problems, and trigger/scheduling waste before deployment. Use when the user says "review my Forge app", "check my app", "pre-deploy check", "is my app ready to deploy", "audit my Forge app", "check for security issues", "check performance", "review manifest", "check my Forge app for problems", "app review", "optimize my Forge app costs", "reduce invocations", "why is my app expensive", "check my triggers", or any request to evaluate a Forge app's quality, safety, cost efficiency, or readiness. Also triggers when users ask about Forge best practices, permission scopes, resolver optimization, storage efficiency, cold start reduction, frontend offloading, trigger filtering, scheduled trigger frequency, N+1 API calls, bulk API usage, verbose logging, or Forge platform pricing.