Guides clinical and health science research through PICOT question formulation, evidence hierarchy assessment, bias evaluation (Cochrane RoB 2, ROBINS-I), outcome prioritization, and GRADE certainty rating. Use when formulating clinical research questions, evaluating health evidence quality, prioritizing patient-important outcomes, conducting systematic reviews or meta-analyses, creating evidence summaries for guidelines, or assessing regulatory evidence.
Fetches arXiv papers submitted within a given date window matching a keyword set, with optional restriction to one or more arXiv categories (e.g. cs.LG, cs.CL, cs.CV, stat.ML, math.ST, q-bio.QM). Wraps the public `export.arxiv.org/api/query` endpoint, parses Atom XML, handles pagination, and normalizes records to the same canonical shape as `fetch-preprint-recent` and `fetch-pubmed-recent` so a calling agent can dedupe across sources. Domain-neutral — usable for any literature scan that crosses CS, ML, statistics, math, physics, or quantitative biology. Use when user mentions arXiv, cs.LG, ML papers, NeurIPS-adjacent preprints, weekly arXiv scan, or when a literature-scan agent needs arXiv records alongside bioRxiv / medRxiv / PubMed.
Fetches preprints posted to bioRxiv or medRxiv within a given date window, then keyword-filters the results client-side. Wraps the public `api.biorxiv.org/details/{server}/{from}/{to}/{cursor}` endpoint, handles cursor pagination, normalizes records to a stable shape (doi, title, authors, abstract, date, server, version, url), and applies a keyword-OR match against title + abstract. Domain-neutral — usable for any biology / clinical preprint scan, not just one project. Use when user mentions bioRxiv, medRxiv, weekly preprint scan, fetch preprints, last-N-days preprints, or when a literature-scan agent needs structured preprint records.
Fetches PubMed articles posted in a given date window matching a keyword set, returning normalized records (PMID, title, authors, abstract, journal, date, DOI, URL). Uses NCBI E-utilities (`esearch` + `esummary` + `efetch`) via WebFetch for portability, but prefers a PubMed MCP server's `search_articles` + `get_article_metadata` tools when one is connected (faster, paginated, parsed). Builds date-bounded queries with optional MeSH expansion. Domain-neutral - usable for any PubMed scan, not just one project. Use when user mentions PubMed, NCBI, last-N-days PubMed, weekly PubMed scan, MeSH search, or when a literature-scan agent needs structured PubMed records.
Presents a math or ML concept simultaneously in geometric form (picture, transformation, region, surface) and algebraic form (formula, matrix, derivation), then writes the explicit one-sentence bridge that says "these are the same thing because…". The signature 3Blue1Brown move applied to any vector/matrix concept. Use when a learner has one view but not the other ("I understand the formula but not what it means" or "I see the picture but can't write it down"), when introducing a concept that genuinely needs both views to land (eigendecomposition, SVD, dot product, attention, gradient, covariance), or when the user mentions "geometric meaning", "intuition behind", "picture for", or "why does the formula look like that".
Diagnoses where a learner's 3D geometric intuition is misleading them in a high-dimensional context (concentration of measure, Gaussian shells, distance-metric breakdown, manifold hypothesis, volume-in-corners, random-projection preservation), then surgically replaces the false picture with the correct one. Use when the user is reasoning about high-dim spaces (embeddings, latent vectors, neural net activations, large-scale data clouds, optimization landscapes) and either makes a claim that's true in 3D but false in 1000D, or expresses confusion at a high-dim phenomenon that "shouldn't" happen.
Memory hierarchy skill for caches, coherence, and locality. Use when explaining cache levels, associativity, false sharing, prefetching, or MESI coherence. Activates on queries about cache hierarchy, L1 L2 L3, false sharing, cache line, prefetch, or cache coherence.
Decomposes any ML construct (attention, layer norm, softmax, convolution, dropout, contrastive loss, diffusion step, gradient descent update, cross-entropy) into the small set of linear-algebra primitives it's built from, then explains why those primitives produce the observed behavior. Includes an ablation thought experiment that asks "what would break if you removed this piece?". Use when the user asks "why does X work?", "explain attention/conv/norm intuitively", "what's actually happening in this layer", or when reading an architecture paper and a particular block doesn't make sense yet.
Weekly refresh of per-opponent archetype + behavioral profiles for the 11 opposing teams in the user's Yahoo Fantasy Baseball league (ID 23756). Thin baseball-specific wrapper around the domain-neutral `opponent-archetype-classifier` -- provides the 10-archetype MLB taxonomy (balanced, stars_and_scrubs, punt_sv, punt_sb, punt_wins_qs, hitter_heavy, pitcher_heavy, inactive, frustrated_active, unknown), extracts MLB features from Yahoo pages (draft distribution, FAAB spend, waiver pattern, roster composition, lineup consistency, trade activity, recent record, activity recency), invokes the classifier, and writes/updates `context/opponents/<team-slug>.md` files per `opponent-profile-schema.md`. Read-modify-write preserves manual notes. Emits a weekly summary signal at `signals/wkNN-opponent-profiles.md`. Use when user says "opponent profiling", "classify opposing manager", "update opponent profiles", "refresh opponents", "weekly opponent scout", or "MLB fantasy opponent archetype".
Deep-dive analysis of a single MLB player (hitter or pitcher) for the Yahoo Fantasy Baseball 2K25 league. Web-searches FanGraphs (ATC projections), Baseball Savant (xwOBA/xBA/xERA), MLB.com (lineups, probables), RotoWire (weather, injuries), and RotoBaller (closer depth) to produce the full set of structured player signals defined in the signal framework. Emits form_score, matchup_score, opportunity_score, daily_quality, regression_index, obp_contribution, sb_opportunity, role_certainty for hitters and qs_probability, k_ceiling, era_whip_risk, streamability_score, two_start_bonus, save_role_certainty for pitchers. Use when you need to analyze player, compute daily_quality, compute regression index, produce player signals, run a hitter analysis, run a pitcher analysis, or prep start/sit inputs for the lineup optimizer.