Loading...
Loading...
Found 202 Skills
Implement Gale-Shapley stable matching algorithm for two-sided matching problems. Use this skill when the user needs to match candidates to positions, assign students to schools, or solve any two-sided preference matching — even if they say 'optimal job matching', 'stable assignment', or 'candidate-position pairing'.
Must be used when users explicitly request "recommend submission journals", "help me choose SCI journals for my paper", "which journals is this manuscript suitable for", "journal matching/journal selection/submission suggestions". Applicable to scenarios where users provide full text, abstracts, Markdown, LaTeX, PDF, Word, or mixed materials; This skill will first use the built-in `2023IF.xlsx` to perform minimum hard filtering to generate a candidate pool based on the manuscript and user preferences, then the host model will independently plan Set1/Set2/Set3, verify the scope / quality / PubMed papers of the last 3 months via the internet, and finally output a Markdown journal selection report sorted by recommendation level. ⚠️ Not applicable: Users only want to polish papers, only want to translate abstracts, or only ask about the official website information of a single journal without needing systematic journal selection.
End-to-end automated operation for publishing Zoom recordings as lectures on PORSEO LMS / AI PLAY GUILD, then automatically handing off to note membership article creation. It also supports a branch where Zoom recordings are not uploaded as lectures, but only converted into note articles with eye-catching images and screenshots. Responsible for searching unpublished Zoom recordings, matching with lecture candidates, retrieving VTT transcripts and chat logs, creating summaries/lecture data, generating YouTube-style thumbnails and applying Convex Storage, importing to Mux, publishing to production Convex, notifying Discord forums, handing off to note articles, and deleting incorrectly published videos. Used when requested with commands like "Turn this Zoom video into a lecture", "Find and publish unpublished videos", "Create and link lecture thumbnails", "Notify Discord about the video", "Create a note article after publishing", "Turn this Zoom recording into only a note article", "Don't upload it as a lecture", "Include note thumbnails and screenshots", "Delete this lecture video".
Prioritize drug targets from a ranked gene list (e.g., scRNA-seq DE output) by orchestrating parallel API queries against UniProt, OpenTargets (with integrated DepMap CRISPR essentiality + gnomAD constraint), PubMed, the Human Protein Atlas (HPA), and ChEMBL tool compounds, then re-ranking by a composite score combining protein localization, druggability, disease genetics, tissue specificity (safety), focus-cell-type expression, CRISPR essentiality, LoF safety constraint, and research maturity. Use whenever the user wants to filter, triage, prioritize, or "do due diligence" on a list of candidate genes for drug discovery, especially after a DE / DEG analysis when they say things like "which of these should I follow up on", "filter for druggable targets", "make a target dossier", "rank these for tractability", "annotate these genes for druggability", or "build a target report". Trigger even when the user says just "filter these candidate genes" or hands over a CSV from a DE pipeline.
Builds site selection and cannibalization analysis workflows in CARTO. Triggers when the user mentions site selection, cannibalization, cannibalizing, new store location, where to open, optimal location, facility placement, network impact, overlapping catchments, twin areas, similar locations, look-alike areas, find locations like my best, store overlap, revenue impact of new store, commercial hotspots, demand hotspots, location scoring, location ranking, expand network, new branch, franchise placement, EV charging siting, or wants to evaluate candidate sites, quantify overlap between trade areas, or find areas that resemble top-performing locations.
Inspeccionar un proyecto existente para descubrir decisiones arquitectónicas implícitas y proponer ADRs candidatos. Usar cuando el usuario quiera auditar un repositorio en busca de decisiones no documentadas, pida "descubrir ADRs", "qué decisiones arquitectónicas tiene este proyecto", "busca ADRs en el repo", "analiza la arquitectura del proyecto" o cualquier variante que implique explorar el código/estructura para inferir decisiones relevantes que merezcan un ADR. Activar también cuando el usuario llegue a un proyecto nuevo y quiera entender qué decisiones ya se tomaron, aunque no mencione explícitamente "ADR".
Generate headline candidates from a story's raw facts: news-style headlines, press-release headlines, and pitch subject lines. A pure generation skill — it finds the charge in the facts, then runs ten proven moves (consequence, picture, number-as-hero, two-beat turn, naming, reader's-own-story, open question, voice, sound, sized claim), each calibrated by real, verified headlines that made history.
Cheap, high-recall first-pass filter that removes obvious junk from a detector candidate pool before expensive story-origin research and PR judgment. Decides keep, monitor_only, or reject — never ranks, writes angles, verifies dates, or decides whether to pitch.
Provide differential diagnosis for patients with suspected rare diseases based on phenotype and genetic data. Matches symptoms to HPO terms, identifies candidate diseases from Orphanet/OMIM, prioritizes genes for testing, interprets variants of uncertain significance. Use when clinician asks about rare disease diagnosis, unexplained phenotypes, or genetic testing interpretation.
Identify drug repurposing candidates using ToolUniverse for target-based, compound-based, and disease-driven strategies. Searches existing drugs for new therapeutic indications by analyzing targets, bioactivity, safety profiles, and literature evidence. Use when exploring drug repurposing opportunities, finding new indications for approved drugs, or when users mention drug repositioning, off-label uses, or therapeutic alternatives.
Use this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. **Trigger when user asks to:** - Migrate or convert PostgreSQL tables to hypertables - Execute hypertable migration with minimal downtime - Plan blue-green migration for large tables - Validate hypertable migration success - Configure compression after migration **Prerequisites:** Tables already identified as candidates (use find-hypertable-candidates first if needed) **Keywords:** migrate to hypertable, convert table, Timescale, TimescaleDB, blue-green migration, in-place conversion, create_hypertable, migration validation, compression setup Step-by-step migration planning including: partition column selection, chunk interval calculation, PK/constraint handling, migration execution (in-place vs blue-green), and performance validation queries.
Write outcome-based, high-signal job descriptions and role scorecards that attract the right candidates and filter the wrong ones. Use for job description, job posting, job ad, role scorecard, hiring brief. Category: Hiring & Teams.