dark-research-lab

Reference for configuring, launching, and monitoring research iteration loops and analysis polish loops

Verifies the analysis pipeline runs end-to-end, outputs match expectations, and LaTeX compiles

Hands-on QA of the research analysis pipeline. Use whenever the user asks to verify the pipeline end-to-end, check output file integrity, validate table and figure generation, test data processing, or verify LaTeX compilation. Triggers on phrases like "test the pipeline", "QA the analysis", "check the outputs", "verify the tables", "run end-to-end", "does the paper compile", or any request to validate a research pipeline.

Define research question, hypotheses, methodology outline, and literature gap

Decompose a research question into cook-it-ready epic beads with methodology specifications

Comprehensive playbook for building rigorous, publication-quality research papers. Covers the full research output sequence from paper structure and statistical reporting through table formatting, figure design, LaTeX conventions, academic writing quality, and pre-submission review.

Multi-agent review with dual-mode detection for code and paper changes

Reviews argument structure for complete claim-evidence chains and counterargument handling

Reviews logical coherence of hypothesis conclusions, limitations handling, and contribution-evidence alignment

Reviews contribution specificity, gap statement support, evidence-claim alignment, and practical implications

Reviews data transformation documentation, sample adequacy, missing data reporting, and selection bias

Detects drift between the approved research plan and the actual analysis implementation

Reviews academic prose quality at the paragraph level for tone, hedging, and logical flow

Reviews section completeness, output references, and LaTeX cross-reference correctness

Comprehensive security review covering credentials, data privacy, dependencies, injection risks, and access controls

Reviews statistical assumption testing, significance reporting, robustness checks, and variable operationalization

Reviews theoretical framework justification, hypothesis derivation, operationalization alignment, and literature support

Orchestrate the full DRL research workflow from specification through paper synthesis

Interactive interview that customizes DRL skill files for field-specific research conventions

Execute statistical analysis pipeline, generate tables and figures

TDD-based code implementation for analysis pipeline and infrastructure

Route work tasks to the appropriate sub-skill based on task context

Draft and revise paper sections with proper citations and cross-references

Reviews research design structure, hypothesis-method alignment, and analysis pipeline architecture

Deep semantic analysis of research outputs against methodology decisions and statistical standards

Injects research-derived test requirements ensuring each methodology decision has a corresponding test

Extracts and stores research methodology insights, statistical technique discoveries, and field-specific patterns

Analyzes research context including literature positioning, methodology rationale, and contribution clarity

Reviews paper formatting, LaTeX quality, table/figure presentation, and academic writing conventions

Audits research documentation for decision log completeness, literature index freshness, and paper section coverage

Implements analysis code following the research plan including data loading, statistical models, and robustness checks

Extracts methodological lessons from completed research cycles for future projects

Searches and retrieves relevant research memory items including prior decisions, methodology patterns, and field conventions

Identifies recurring methodology patterns, statistical approach similarities, and cross-project research insights

Reviews analysis code for efficient data processing, memory usage, and execution time on large datasets

Analyzes the research repository structure, conventions, and patterns for paper organization, data pipeline layout, and test structure

Ensures all stated hypotheses have corresponding analyses, robustness checks, and paper sections

Reviews research methodology and code for unnecessary complexity, over-engineered analysis, and needless abstraction

Writes research analysis code including statistical models, data transformations, and table/figure generation

Reviews test coverage for reproducibility of all analysis steps, seed fixation, and result determinism