Expert assistant for creating Deckset presentations with markdown. Helps with slide formatting, headings, lists, images, videos, presenter notes, build steps, themes, and configuration. Use when working with .md presentation files, or when user mentions Deckset, creating slides, presentations, or decks.
Find, trial, compare, and govern AI agents before hiring
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Use this type-filtered index for broad candidate discovery. Filter by protocol, source, trust, and review status before opening a profile.
Complete development kit for building Microsoft 365 Copilot declarative agents with TypeSpec and Agents Toolkit integration. Three specialized workflows cover basic agent creation, advanced enterprise design, and validation/optimization for existing agents Supports up to 5 capabilities from 11 options including WebSearch, OneDrive/SharePoint, Graph Connecto...
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This skill helps you build hierarchical AI agents with planning, memory, and subagent delegation to manage complex tasks.
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This skill conducts deep, evidence-based reverse engineering analysis to answer focused questions and iteratively improve the Ghidra database.
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This skill performs exhaustive research with full citations and structured findings to support critical decisions.
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This skill helps you conduct structured multi-step research, orchestrating subagents and long-context analysis to deliver synthesized, actionable insights.
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Build agents specialized in conducting thorough research, gathering information from multiple sources, and synthesizing findings. Covers research planning, source evaluation, and report generation. Use when automating market research, competitive analysis, literature reviews, or intelligence gathering.
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This skill guides you through complex, multi-step research, planning tasks, coordinating subagents, and delivering synthesized data-driven insights.
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This skill performs structured, multi-step research by planning, decomposing, and coordinating subagents to deliver data-driven insights.
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This skill enables deep research by planning multi-step projects, coordinating subagents, and synthesizing large-context analysis into actionable reports.
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This skill enhances an existing plan by assigning parallel research agents to each section, delivering depth, best practices, and concrete implementation
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This skill helps you evaluate LLM applications using Deepeval's pytest-based metrics and tracing to ensure quality and safety.
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Inventory cards stay compact; complete index records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
- 01Site contextShared review rules
- 02Agent inventoryBrowse the matching inventory
- 03Profile pageOpen the candidate page
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for type-filtered inventory records, candidate discovery context, and finalist profile resources before action.