Atiko
Community@AppleCG
Atiko provides a distilled cognitive scaffolding system for social science and humanities research, covering topic diagnosis, execution, and contribution convergence.
Agent Skills by Atiko
Showing 6 vetted skills indexed across 1 GitHub repositories.
AppleCGacademic-research-workflow
Diagnose social science research topics, designs, and contributions using distilled methodological frameworks.
AppleCGresearch-distiller
Extract research frameworks and argumentation structures from academic papers and scholarly materials.
AppleCGtopic-problematization
Diagnose research topic quality through a four-step problematization framework for social sciences.
AppleCGresearch-execution
Diagnoses theory derivation and method justification chains in social science research designs.
AppleCGresearch-architecture
Diagnoses research stage and provides source-traced methodology guidance for social science and humanities projects.
AppleCGresearch-contribution
Diagnoses research contribution type, construction quality, discussion framing, and limitation honesty in academic papers.
Frequently Asked Questions About Atiko
FAQPage SchemaWhat tasks can I accomplish with Atiko's academic-research-workflow skills?▼
You can distill research frameworks from academic materials, diagnose topic selection via problematization, validate execution from research question to design with theory derivation and method justification, and assess contribution convergence across Discussion, Conclusion, and limitations sections.
Who is the target user for these research skills?▼
Social science and humanities researchers, graduate students, and academic writers who need structured cognitive scaffolding for topic selection, research design, methodology justification, and contribution framing—not an automated paper-production pipeline.
How do the six skills relate to each other in practice?▼
Academic-research-workflow is the parent three-layer, four-step architecture. Research-distiller extracts frameworks from source materials; topic-problematization, research-execution, and research-contribution are child diagnostic engines covering topic, execution, and contribution layers respectively.
Do the skills generate content without source materials?▼
No. Every recommendation is traceable to distilled authoritative source materials (8-9 documents per engine). The skills explicitly avoid unsourced presets, templates, and topic selection on the user's behalf, functioning purely as diagnostic scaffolding.
What are the prerequisites for using these skills?▼
You need academic materials to feed the distiller—papers, talks, or journal guidelines—and an existing research idea or question. The skills assume a social science or humanities research context; no other dependencies are specified in the manifest.