eval
Evaluate Deca agent prompts and behavioral consistency through automated test runners, manual LLM judgment, and structured reporting.
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529 skills found
Evaluate Deca agent prompts and behavioral consistency through automated test runners, manual LLM judgment, and structured reporting.
Update text within fillable PDF forms programmatically. Efficiently modify names, dates, addresses, and reference numbers in form fields while preserving document structure.
Systematically evaluate scholarly work using the ScholarEval framework, providing structured, quantitative, and qualitative assessment across research quality dimensions with actionable feedback.
Generate high-quality, minimalistic, and geometric SVG logos using Python scripts. Ideal for icons, branding, and visual assets built with geometric primitives.
Optimize agent context windows through KV-caching, observation masking, summarization-based compaction, and context partitioning to reduce costs and latency.
A comprehensive guide and reference for building, orchestrating, and deploying AI agents using the Google Agent Development Kit (ADK).
Analyze markdown documentation files to ensure compliance with predefined AI token budgets and optimize content for efficient AI ingestion.
Universal MCP client for connecting to any MCP server with progressive disclosure. Wraps MCP servers as skills to prevent context window bloat from tool definitions. Use for Zapier, GitHub, sequential thinking, and file operations.
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
Audit Packmind documentation by cross-referencing MDX files against the codebase to detect broken links, outdated CLI references, and missing coverage.
Expert skill for implementing the Gemini Interactions API. Use for stateful multi-turn chat, background Deep Research agent tasks, function calling, structured outputs, and modern Python/TypeScript SDK integration.
A testing skill designed to verify the functionality of the Skillet CLI by performing basic tasks and confirming completion.