Results for “base”

Builds and maintains a persistent, interlinked Obsidian knowledge base by incrementally ingesting sources, updating entity/concept pages, and keeping cross-references current.

Inspect B20 token contract addresses on Base to verify factory recognition, initialization, policies, pause state, and risk flags via the public B20 Console API.

Audits a research knowledge base for stale profiles, thesis drift, and orphan pages, returning a 0-100 health score with actionable recommendations.

Access real-time X/Twitter attention intelligence for Base chain tokens via the checkr API, including trending tokens, social spikes, attention/price divergence signals, and narrative summaries.

Analyze diverse user feedback to identify at least 3 distinct behavioral and needs-based user segments based on jobs-to-be-done, behaviors, and motivations.

Retrieves and answers questions from a local knowledge base directory by navigating hierarchical index files, then progressively searching Markdown, PDF, and Excel files using grep, Read, pdfplumber, and pandas.

Compare Itô prediction-market baskets against a user's knowledge base, portfolio notes, financial context, watchlist, or research thesis for read-only gap analysis.

Use the Python-based ddgs CLI (via `uvx ddgs`) for ad-hoc, unlimited web searches across multiple search engines. Trigger this skill when the user asks you to look something up online, compare sources, or gather search-based research.

Evaluates Base ERC-20 tokens by contract address, returning a 0-100 score across five criteria, launch protocol classification, security flags, and a narrative interpretation.

Investigate tokens, wallets, and on-chain entities with natural-language answers backed by on-chain data. Detect insiders, whales, pump-and-dump, wash trading, and wallet networks on Base.

Use this skill to measure performance baselines, detect regressions before/after PRs, and compare stack alternatives.

Transform research findings into actionable implementation plans with stakes-based rigor, test-first strategy, and granular task decomposition.

Conducts thorough landscape research, competitive analysis, best practices evaluation, and evidence-based recommendations. Expert in market research and trend analysis.

Especialista em CrewAI - o principal framework multi-agente baseado em papéis utilizado por 60% das empresas da Fortune 500. Abrange design de agentes com papéis e objetivos, definição de tarefas, orquestração de crew, tipos de processo (sequencial, hierárquico, paralelo), sistemas de memória e flows para workflows complexos. Essencial para construir equipes colaborativas de agentes IA. Use quando: crewai, equipe multi-agente, papéis de agentes, crew de agentes, agentes baseados em papéis.

Search your references and context knowledge base for patterns relevant to a current task. Use before implementing anything non-trivial to surface prior art from your analyzed repos.

Query Google NotebookLM notebooks using Gemini's source-grounded answers. Automates browser-based authentication, notebook management, and question-answering workflows.

Distill learnings from a completed repo analysis into reusable knowledge base entries in ~/.copilot/context/. Use after finishing a repo-analysis to make the learnings persistent and searchable.

Evidence-based health research using tiered trusted sources with GRADE-inspired evidence ratings. Integrates Apple Health data for personalized context. Use when user asks health, nutrition, exercise, sleep, or wellness questions.

Personal knowledge base powered by Ensue for capturing and retrieving understanding. Use when user wants to save knowledge, recall what they know, manage their toolbox, or build on past learnings. Triggers on "save this", "remember", "what do I know about", "add to toolbox", "my notes on", "store this concept".

Routes quality reviews to specialized critic agents based on file type or flags, covering peer review, code review, and manuscript polish.

Runs evidence-first research workflows by combining search, synthesis, and recommendation skills for current facts, comparisons, or enrichment.

Runs evidence-first research workflows, choosing the lightest useful path from search to deep synthesis, and labels facts, inference, and recommendations.

Identifies, qualifies, and tiers investors for a funding round based on stage, sector, geography, check size, and portfolio fit, delivering a prioritized target list.

Benchmarks medical AI agents on synthetic EHR tasks, measuring success rates for data retrieval, temporal aggregation, and threshold-based conditional logic with exact-match scoring.

Evaluate scientific manuscripts and grant proposals with structured, checklist-based peer review covering methodology, statistics, reproducibility, ethics, and reporting standards.

Transforms chaotic notes, voice dumps, and meeting transcripts into a structured, interlinked knowledge base inside Obsidian by extracting entities, generating wikilinks, and surfacing forgotten context.

Builds systematic factor-based investment strategies following AQR Capital Management's methodology, covering factor construction, portfolio optimization, and risk management.

Perform constraint-based metabolic modeling with COBRApy: run FBA, FVA, gene knockouts, flux sampling, and manage SBML models for systems biology and metabolic engineering.

Apply plugin knowledge base updates to an existing generated system. Consults the Ars Contexta research graph for methodology improvements, proposes skill upgrades with research justification. Never auto-implements. Triggers on "/upgrade", "upgrade skills", "check for improvements", "update methodology".

Predict 3D binding poses of small molecule ligands to protein targets using diffusion-based molecular docking, supporting single complexes, batch processing, and virtual screening.