Use when a researcher asks where to start, which project skill fits the current stage of a study, or in what order literature scoping, source access, vault upkeep, drafting, citation verification, disclosure, and review response should run.
The English summary is being prepared. Showing the original description.
Use when sources must stay traceable across sessions and years, when each reference needs a passport recording where it was found, how it was verified, and where it is cited, or when a draft needs a cited-but-unverified sweep before submission.
The English summary is being prepared. Showing the original description.
Use when selecting a statistical test with AI consultation, when assumptions need checking against the actual data, when an analysis plan or decision log must be written before running anything, or when results need APA-style reporting with effect sizes.
The English summary is being prepared. Showing the original description.
Use when designing a course, assessment, or student-feedback workflow and deciding where AI assistance is acceptable, when grading or feedback must stay within academic-integrity and FERPA/KVKK boundaries, or when AI-use rules for students need stating.
The English summary is being prepared. Showing the original description.
Use when a source must be reached through DergiPark, ULAKBIM TR Dizin, HEAL-Link, YOK Thesis Center, or an institutional library route, when off-campus access fails, or when a lawful retrieval plan is needed for Turkish, Greek, or European materials.
The English summary is being prepared. Showing the original description.
Use for the search-planning stage of a literature review, when database lanes and language layers must be chosen, when DOI coverage policy is unclear, or when inclusion and exclusion criteria need drafting before any source is read; not for running the screening and PRISMA pipeline of a formal review, which is prisma-scoping-review-pipeline.
The English summary is being prepared. Showing the original description.
Use before sensitive, clinical, identifying, or raw interview data is placed in front of an AI tool, when transcripts or student materials need de-identification, or when a data-minimization gate must run before any analysis or drafting.
The English summary is being prepared. Showing the original description.
Use when automating research session rituals in Claude Code with hooks, such as session-start context injection, daily research logging, session-end persistence, or pre-commit guards that block secrets and unverified citations.
The English summary is being prepared. Showing the original description.
Is this your account? Link GitHub to bring it onto your creator page (Japanese)