yogsoth-ai/literature-survey

gap-identification

Identify what the literature has NOT addressed — missing methods, untested combinations, unexplored applications, contradictions without resolution. Used by all strategies.

thematic-coding

Identify recurring themes across papers using qualitative coding methodology. Produces a codebook with theme definitions, supporting evidence, and frequency counts. Used by narrative-review.

prisma-flowchart

Generate PRISMA-compliant flow data documenting the screening funnel — counts at each stage (identification, screening, eligibility, inclusion) with exclusion reasons. Used by systematic-survey via prisma-screening tactic.

taxonomy-mapping

Construct a hierarchical field map from paper collection — multi-level taxonomy with parent/child relationships, paper counts per node, and maturity indicators. Used by scoping-survey.

saturation-detection

Determine when additional searching yields diminishing returns. Analyzes the latest expansion batch against existing corpus to judge continue/near-saturation/saturated. Used by snowball and systematic-survey.

seed-selection

Validate and prioritize starting papers for snowball surveys. Evaluates which seeds will yield the richest citation traces based on citation count, recency, and network position.

extract-data

Structured data extraction from deep-read papers — produces comparison tables (method, dataset, metrics, results, limitations). Used by systematic-survey and deep-survey.

quality-assessment

Methodological rigor scoring for papers — evaluates bias risk, reproducibility, sample adequacy using established frameworks. Used by systematic-survey.

categorize-papers

Cluster papers by theme, method, or timeline. Produces natural groupings from a paper collection. Used by scoping-survey and narrative-review.

define-search-protocol

Formalize search queries and inclusion/exclusion criteria for systematic surveys. Produces a reproducible search protocol document. Used by systematic-survey.

survey-synthesis

Final synthesis step — weave all gathered evidence (reading notes, extracted data, categorizations) into a coherent structured output appropriate to the strategy type. Used by all 5 strategies as the final step.

paper-research

Full-depth paper reading with raw text extraction. Import of literature-engine/literature-research skill. Must read fullText (true) — equations, hyperparameters, specific claims extracted.

paper-search

AI-summarized paper reading for intermediate depth. Import of literature-engine/literature-search skill. Must call get_paper_content for every analyzed paper.

web-research

Full-page web reading for non-academic perspectives — blogs, tech reports, product pages, industry analysis. Import of web-browsing/web-research skill. Must fetch full page via apify for every analyzed page.

intake

Lightweight intent clarification dialogue — only invoked when the entry point cannot determine the correct strategy from context alone. Maximum 3 questions. Pure routing, not profiling.

citation-chaining

Forward and backward citation tracing tactic — expand paper coverage by tracing citation networks in both directions from seed/key papers. Alternates forward (who cited this) and backward (what this cited) passes until saturation.

narrative-framing

Theory-driven reading tactic — define a theoretical framework first, then guide reading to fill it with evidence. Five stages (theme identification, argument construction, evidence collection, counter-evidence, synthesis). The most intellectually demanding…

prisma-screening

Multi-stage PRISMA screening tactic — progressively filter papers from a large candidate pool to a focused set for deep reading. Four stages (identification, title/abstract screening, full-text screening, inclusion) with documented counts at each stage.

deep-survey

Precise, targeted investigation of a specific sub-problem — few papers, all read in full depth. High paper-research ratio (50% deep-read rate). Use when the user knows exactly what they need to understand and requires detailed technical analysis with…

literature-survey

Autonomous Literature Survey Engine with 5 research paradigms (scoping, systematic, deep, narrative, snowball). Use this skill whenever a user needs to survey academic literature, conduct a literature review, map a research field, trace citation lineages, or…

narrative-review

Theory-driven literature review for building arguments and frameworks. Flexible, subjective, and narrative-focused — selects evidence strategically to support a thesis. High web-research budget for blogs, opinion pieces, and industry perspectives. Use when…

scoping-survey

Broad landscape mapping strategy — quickly understand what exists in a field. Prioritizes breadth over depth with high paper-overview volume and minimal deep reading. Use when entering a new field or needing orientation before committing to deeper…

snowball

Citation-chain-driven literature survey starting from seed papers. Traces research lineage in both forward (who cited this) and backward (what this cited) directions until saturation. High deep-read ratio (67%). Use when the user already has key papers and…

systematic-survey

Exhaustive PRISMA-style literature survey — comprehensive coverage of all related work on a specific question. Multi-stage screening, citation chaining, quality assessment, and structured data extraction. Use when the user needs to demonstrate complete…