markdown-token-optimizer
Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.
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259 skills found
Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.
Implement LlamaExtract for robust structured data extraction from PDF, DOCX, and PPTX files using Pydantic schemas.
Deep inquiry framework using Socratic questioning to examine beliefs, uncover hidden assumptions, test evidence, and reach nuanced understanding without lecturing.
Comprehensive citation management: search academic databases, extract metadata from DOIs/PMIDs/arXiv, validate references, and generate perfectly formatted BibTeX for scientific manuscripts.
Analyze AppWorld task failures to extract specific API patterns and generate actionable playbook bullets with concrete code examples.
Synthesizes multi-agent research findings into coherent, citation-backed reports, resolving contradictions and identifying consensus.
Query the Pollinations text API with web-search enabled models like Gemini and Perplexity for grounded, real-time research.
Synchronizes and maintains CLAUDE.md and README.md documentation hierarchy across a repository to ensure consistent, just-in-time context for AI agents.
Expert consultant for designing and building high-quality, consistent AI agent skills. Guides you through discovery, architecture, and creation phases to ensure reliable, composable, and efficient skill delivery.
Framework for multi-agent collaboration using the Google A2A protocol. Enables messaging, task delegation, and cross-agent coordination for CLI-based AI tools.
A decision-support tool for Claude Code users to select the optimal extension mechanism—slash commands, skills, subagents, or hooks—based on project requirements.
Automated retrieval of PubMed scientific literature and generation of plain-language biomedical research summaries.