assess-covariance-method
Provides a protocol for implementing, validating, benchmarking, and statistically evaluating new covariance, correlation, precision estimators, and covariance scoring rules.
Analyzes persuasive messages by decomposing claims, tracing them to authoritative evidence, identifying misleading framing, and reporting calibrated verdicts while separating literal truth from implied conclusions.
Use when someone asks what is true, false, misleading, unsupported, unknown, or genuinely complicated in a persuasive message, article, pitch, advertisement, policy claim, or viral post. Analyze propaganda, spin, selective framing, urgency, social proof, deceptive marketing, and AI-generated persuasion by tracing claims to evidence and separating literal truth from implied conclusions. Do not use to read deception from demeanor, adjudicate intent, or replace broad domain research.
Provides a protocol for implementing, validating, benchmarking, and statistically evaluating new covariance, correlation, precision estimators, and covariance scoring rules.
Extracts and organizes Douyin video data, transcripts, comments, metadata, and visual evidence into traceable notes, research briefs, scripts, fact-checks, and reusable knowledge …
Enforces a research workflow requiring source-grounded claims, citations, direct quotations from documents, and explicit acknowledgment when information cannot be verified.
Searches Project Gutenberg via Gutendex, downloads book editions, extracts clean text from TXT or EPUB files, and classifies books as fiction, non-fiction, or ambiguous.
Enables terminal-based browsing of PeerTube instances, including video search, details, comments, channels, accounts, instance statistics, and optional OAuth2 access to the user's…
Guides agents through rigorous research planning, evidence evaluation, analysis, synthesis, reporting, and durable preservation with traceable source-to-claim relationships.
Provides rigorous guidance for statistical analysis, experimental design, causal inference, Bayesian methods, machine learning, reproducibility, and research methodology.
Provides a methodology for formulating, comparing, validating, and auditing constrained optimization decisions using explicit variables, objectives, feasibility rules, tradeoffs, …