Dr. Steve J. Bickley
Community@stevejbickley · Brisbane, Australia
Research Fellow at the ARC BITA Centre, Queensland University of Technology (Brisbane, Australia) | CEO & Co-Founder of Panalogy Lab
Agent Skills by Dr. Steve J. Bickley
Showing 15 vetted skills indexed across 1 GitHub repositories.
review-writing
Reviews academic prose for argument, structure, clarity, and consistency without rewriting.
devils-advocate
Generates adversarial pedagogical challenges against slide deck design and ordering.
coauthor-brief
Generates a Markdown handoff brief summarizing git deltas, artifact states, and reproduction steps for collaborators.
stata-replication
Scaffolds and executes numbered Stata .do file pipelines for reproducible replication packages.
handoff
Generates a conversation summary document for continuing work in a new agent session.
code-review
Reviews a git diff against coding standards and the originating spec using parallel sub-agents.
review-paper
Reviews academic manuscripts via single-pass, adversarial, or simulated peer-review pipelines.
end-session
Writes session logs and updates TASKS.md, MEMORY.md, CHANGELOG.md, and README.md at session close.
validate-bib
Validate bibliography entries against citations in LaTeX and Quarto lecture files.
proofread
Reviews LaTeX and Quarto lecture files for grammar, typos, and formatting issues without editing sources.
data-analysis
Runs end-to-end R data analysis producing regression results and publication-ready tables and figures.
humanize
Audit academic prose for AI-voice tells and generate a structured detection report.
grill-me
Interviews the user question-by-question to stress-test plans and decisions.
respond-to-referees
Generate a structured response-to-referees document mapping referee comments to manuscript revisions.
review-r
Reviews R scripts for code quality, reproducibility, and tidyverse conventions without editing source files.
Frequently Asked Questions About Dr. Steve J. Bickley
FAQPage SchemaWhat tasks can I accomplish with Dr. Steve J. Bickley's skills?▼
You can run end-to-end R or Stata empirical analysis pipelines, simulate journal peer review with referee dispositions, draft response-to-referees documents, proofread LaTeX/Quarto lectures, validate bibliographies against citations, audit prose for AI-voice tells, and generate co-author handoff briefs with git deltas.
Who are these skills designed for?▼
Academic economists and quantitative social scientists — matching the author's research fellow profile at QUT's ARC BITA Centre — who write empirical papers in R or Stata, prepare journal submissions and R&R responses, and maintain lecture materials in .tex or .qmd formats.
How do the data analysis and replication skills execute code?▼
The data-analysis skill writes numbered R scripts into scripts/R/ and outputs to scripts/R/_outputs/, while stata-replication scaffolds .do files and executes them through the stata-mcp MCP server, capturing logs and producing esttab tables and exported figures.
What are the prerequisites and dependencies?▼
Stata replication requires the stata-mcp MCP server for execution; R analysis expects .csv, .rds, or .dta inputs. Bibliography validation optionally uses WebFetch for DOI verification, and several skills rely on git for delta-based co-author briefs and code reviews.
Do these skills edit my manuscripts or code directly?▼
Most review skills are read-only: proofread, humanize, review-r, review-writing, and devils-advocate produce reports without editing. Only pipeline and drafting skills like data-analysis, stata-replication, respond-to-referees, and coauthor-brief write files to your project.