kb-literature-review
The kb-literature-review command executes a structured literature synthesis workflow that transforms source paper notes into organized knowledge artifacts and writing drafts. Use it to synthesize research papers into literature overviews, method taxonomies, research gaps, and related-work sections, with conditional outputs based on whether source notes contain sufficient evidence records to support claims.
mkdir -p ~/.claude/commands && curl -fsSL https://raw.githubusercontent.com/Galaxy-Dawn/claude-scholar/HEAD/commands/kb-literature-review.md -o ~/.claude/commands/kb-literature-review.mdkb-literature-review.md
# /kb-literature-review Use `obsidian-literature-workflow`. Conditional outputs: - `Knowledge/Literature Overview.md` only when paper notes contain enough Evidence Records for synthesis - `Knowledge/Method Taxonomy.md` when useful and evidence-backed - `Knowledge/Research Gaps.md` when useful and evidence-backed - `Knowledge/Claim Map.md` or a warning when evidence is weak - `Writing/related-work-draft.md` only when promoted claims pass the evidence gate - `Maps/literature.canvas` Keep source notes in `Sources/Papers/`. Do not turn source notes into synthesis notes. Evidence gate: - refuse polished `Knowledge` or `Writing` synthesis when paper notes lack Evidence Records, - keep abstract-only or webpage-placeholder items in coverage / `To-Read`, - generate a warning or `Knowledge/Claim Map.md` instead of a mature related-work draft when evidence is weak, - preserve claim strength on literature canvas edges.
Expert code review specialist. Proactively reviews code for quality, security, and maintainability. Use immediately after writing or modifying code. MUST BE USED for all code changes.
Use this agent when the user provides a Kaggle competition URL or asks to learn from Kaggle winning solutions. Examples:
Use this agent when the user asks to "conduct literature review", "search for papers", "analyze research papers", "identify research gaps", "review related work", or mentions starting a research project. This agent integrates with Zotero for automated paper collection, organization, and full-text analysis. Examples:
Use this agent when the user provides a research paper (PDF/DOCX/arXiv link) or asks to learn writing patterns from papers, extract venue-specific writing signals, study paper structure, or mine rebuttal strategies. The agent writes extracted knowledge into the active installed paper-miner writing memory for ml-paper-writing. It does not maintain project-specific writing memory.
Use this agent when the user asks to "write rebuttal", "respond to reviewers", "analyze review comments", or needs help with academic paper review response. This agent specializes in systematic rebuttal writing with professional tone and structured responses.
Test-driven development guide for writing tests first, implementing the smallest passing change, and keeping verification tight. Use when the user explicitly wants TDD or when a task should be driven by failing tests before code.
Run a blocker-first post-experiment workflow: validate evidence, produce strict statistical analysis when possible, and generate a decision-oriented results report only when the analysis bundle is sufficient. Uses results-analysis + results-report as a gated two-stage workflow.
Commit changes following Conventional Commits format (local only, no push).