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literature-review
Find, verify, and synthesize scientific literature — from "what's the seminal paper for X" through full multi-source reviews. Covers grounding claims in real retrieved sources, avoiding fabricated citations, handling retractions, and calibrating confidence to evidence strength.
reimagine-it-audit
Design Health — runs 19 deterministic quality checks on HTML output. Use when the user says /reimagine-it audit, "audit this page", "check design quality", or wants to verify craft-floor compliance before shipping. Catches blank plates, missing focus rings, non-compositor motion, off-palette accents, dead motion, fabricated content. No LLM, no API key. CI-r…
blog-rewrite
Rewrite and optimize existing blog posts for Google rankings (December 2025 Core Update, E-E-A-T) and AI citations (GEO/AEO). Full rewrite for both Google rankings AND AI citations. For AI-citation-only audit (no Google work), use blog-geo instead. Replaces fabricated statistics with sourced data, applies answer-first formatting, adds Pixabay/Unsplash image…
testimonial-capture-interview
Runs customer interviews engineered to produce usable testimonials and case-study raw material - a question sequence that elicits before/after specifics and real numbers, a permission and approval workflow, quote-editing ethics (tighten but never fabricate), and a soundbite extraction procedure. Use when a user says "get a testimonial from this customer", "…
dataviz-precision
Choose how many significant digits to show for chart and table numbers - keyed to the spread (max-min), not individual values, one uniform place per column. Never fabricate precision.
bib-verify
Verify a BibTeX file for hallucinated or fabricated references by cross-checking every entry against CrossRef, arXiv, and DBLP. Reports each reference as verified, suspect, or not found, with field-level mismatch details (title, authors, year, DOI). Use when the user wants to check a .bib file for fake citations, validate references in a paper, or audit bib…
citation-audit
Zero-context verification that every bibliographic entry in the paper is real, correctly attributed, and used in a context the cited paper actually supports. Uses a fresh cross-model reviewer with web/DBLP/arXiv lookup to catch hallucinated authors, wrong years, fabricated venues, version mismatches, and wrong-context citations (cite present but the cited p…
figure-first-paper-reader
Reads a paper figure by figure before re-integrating the full narrative, so the user can identify the core findings quickly and check whether each visual actually supports the authors' main claims. Always separate figure content, figure-linked claim, evidentiary strength, and unsupported interpretation. Never fabricate references, PMIDs, DOIs, figure conten…
aaag-rebuttal
Use when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and 1-3 referees across the journal's four areas. Structures the response and revisions; it does not fabricate results.
aerj-rebuttal
Use when writing the response to an American Educational Research Journal (AERJ) revise-and-resubmit. AERJ R&Rs come back through the handling editor and multiple masked reviewers, so the response must convert each reviewer while keeping the editor confident the revision is convergent. Structures the response letter; it does not fabricate new results.
agsy-data-and-model-evaluation
Use when evaluating the model and analyzing results for an Agricultural Systems (AgSy) manuscript so it survives expert systems review — independent model evaluation (observed vs. simulated, fit statistics), sensitivity and uncertainty analysis, and trade-off / scenario analysis across the system. Guides evaluation norms; it does not fabricate results or ru…
ahr-argument-development
Use when turning archival findings into a sustained historical argument for The American Historical Review (AHR). The AHR rewards a clear thesis that earns its claims from evidence while remaining alert to contingency and complexity. Builds the argument and its stakes; it does not gather new sources or fabricate evidence.
ahr-revision-and-response
Use when responding to an American Historical Review (AHR) decision — a revise-and-resubmit or rejection. AHR articles are read by at least six demanding specialists, so the response must address expert reports while protecting the argument and keeping the manuscript anonymized. Structures the revision and response letter; it does not fabricate new evidence.
ajps-data-analysis
Use when executing and reporting the analysis for an American Journal of Political Science (AJPS) manuscript. AJPS will have a third-party verifier re-run your exact code against the numerical results in the main text before publication, so analyze reproducibly from the first line. Guides analysis and reporting norms; it does not fabricate results.
ajps-rebuttal
Use when writing the response to an American Journal of Political Science (AJPS) revise-and-resubmit. The revised manuscript stays double-blind, the response memorandum is submitted anonymized, and any new analyses must keep the replication package re-runnable for the third-party verifier at acceptance. Structures the response; it does not fabricate new res…
ajs-data-analysis
Use when planning or auditing the analysis of an American Journal of Sociology (AJS) manuscript so the evidence credibly supports the theoretical claim. Covers analysis norms, uncertainty, robustness, and triangulation across quantitative, comparative-historical, and ethnographic work. Improves the analysis chain; it does not fabricate results.
ajs-rebuttal
Use when responding to an American Journal of Sociology (AJS) decision — an R&R response letter to multiple double-blind reviewers and the editor, or an author Reply to a published Comment in AJS's Comment-and-Reply tradition. Structures a persuasive, evidence-based response; it does not fabricate results or contact editors.
algo-risk-benford
Apply Benford's Law to detect anomalies in numerical datasets by analyzing first-digit frequency distributions. Use this skill when the user needs to audit financial data for fraud indicators, validate data integrity, or detect fabricated numbers — even if they say 'data manipulation detection', 'first digit test', or 'accounting fraud screening'.
An independently imported catalog with original authors, licenses and source links. Classification is not a security audit.
Sources and import coverage