Research & Search Agent Skills

Analyzes local SEO signals including Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, and location page quality, with business type and industry vertical detection.

Analyzes target markets, ICP segments, demand patterns, competitive terrain, and strategic whitespace to support founder decisions on positioning, fundraising, and go-to-market.

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

Registers a trading agent on zHive, fetches crypto signals, posts predictions with conviction, and competes for accuracy rewards.

Monitors websites, RSS feeds, and e-commerce pages for content changes and price drops, with social listening and custom scraping for competitive intelligence and market research.

Monitors trending topics across 35+ platforms, aggregates trends, analyzes sentiment, and provides real-time notifications via MCP tools.

Fetches and summarizes the latest ORF news in German, focusing on Austrian and international politics, and generates a themed studio image.

Plans and decomposes complex, multi-step research tasks into manageable steps.

Answers questions about the Sui blockchain ecosystem, covering concepts, tokenomics, validators, staking, and comparisons with other chains.

Answers questions about the Sui blockchain ecosystem, including concepts, tokenomics, validators, staking, and comparisons with other chains.

Calculates TAM, SAM, and SOM using three methodologies (top-down, bottom-up, value theory) and cross-validates results for investor-ready market analysis.

Provides domain knowledge of Korean government and private funding program announcement systems, evaluation criteria, and key program characteristics, including TIPS, Early-Stage Startup Package, Startup Growth Technology Development, and AI Voucher.

Optimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems. Use when improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.

Formalizes narrative technical documents into structured mathematical problem specifications with variables, constraints, objectives, and uncertainty, citing evidence and flagging missing information.

Analyze and optimize content for visibility in AI Overviews, ChatGPT, Perplexity, and other AI search systems by evaluating citability, structure, authority, and technical accessibility.

Turns any folder of files into a navigable knowledge graph with community detection, producing interactive HTML, GraphRAG-ready JSON, and a plain-language report.

Query the Cancer Dependency Map (DepMap) for CRISPR gene dependency scores, drug sensitivity data, and gene effect profiles to identify cancer-specific vulnerabilities, synthetic lethal interactions, and validate oncology drug targets.

Delegates scientific literature searches to the Edison API, which autonomously searches hundreds of papers and returns a cited answer. Handles query submission, polling, and reporting results.

Profiles a competitor's vehicles, teaming posture, and recent award patterns, producing a markdown note for vault capture.

Perform intermediate-level optics design tasks including wave equation solving, behavior prediction, and physical modeling for research, industry, or education.

Literature survey and SOTA tracking specialist. Use when the user asks to talk to Sova, requests the research tracker, or needs literature review, citation mapping, and paper analysis.

Run an AI Lab division meeting with research and build agents (no AI Startup agents). Use when the user requests to "start a lab meeting", "convene the lab", or "run a sprint retrospective for the lab".

Search and summarize papers from ArXiv. Use when the user asks for the latest research, specific topics on ArXiv, or a daily summary of AI papers.

AI 论文速读 Skill：三档深度（裸读 / 引导 / 精读）+ 页码级 Provenance 防幻觉 + 多篇对比。 触发词：论文速读、读这篇论文、抓核心观点、论文对比、多篇对比、与我研究方向的关联、 第几页提到 X、这篇论文的数据集怎么构造的、论文精读、 paper summary、summarize this paper、compare these papers、literature skim、extract methodology。 不做：论文检索、文献管理、论文翻译、扫描件 OCR、论文写作 / 降重。

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".

Manage and compress conversation context in long sessions. Detect when context is growing large, summarize completed work phases, archive old findings while preserving key decisions. Prevents context degradation.

Use to convert references to NEJM's Vancouver / ICMJE numbered style — numbered in order of appearance, limited author lists then et al., NLM journal abbreviations, and a capped reference count. Late-stage style pass.

Spawns a researcher agent to investigate how to implement a project phase, gathering context on architecture patterns, standard libraries, and common pitfalls.

Gracefully retire a skill that is redundant, superseded, or no longer earning its place in the context window. Load when improve-skills finds a skill scoring 0-5/14 AND research confirms the domain is now handled natively by current models, when two skills have overlapping triggers and one subsumes the other, when the user asks to remove a skill, retire a skill, delete a skill, or clean up redundant skills, or when validate-skills flags a skill as a duplicate trigger risk. Handles removal cleanly: updates all callers, removes from AGENTS.md, updates README, and archives rather than deletes so the skill can be recovered if needed.

Creates research-backed user personas with JTBD, pain points, gains, and unexpected behavioral insights. Use when building personas from survey or interview data, or segmenting users to inform product decisions. Triggers on: user persona, user profile, customer segment, jobs-to-be-done, JTBD, persona creation, user segmentation, target user, who are our users.

Use to CREATE or REVIEW a Job to be Done (JTBD) in Alan Klement's demand-side, progress-based sense — a job is the progress a customer is trying to make, never a task or feature. Trigger whenever someone wants to write or draft a JTBD, job statement, or job story; figure out the real motivation, struggle, or progress behind a feature, request, or product; understand why customers switch, adopt, or churn; turn interview notes or research into jobs; or pressure-test, sharpen, or rewrite existing JTBDs into proper jobs. Also trigger on "grill my JTBD", "is this a real job or just a task/feature", "what's the actual job here", "why would they switch". In an A-Team target repo, jobs are durable artifacts — this skill writes docs/product/jtbd/NN-<slug>.md per CONTRACT.md and never deletes or silently rewrites a job. Do NOT use for writing PRDs, roadmaps, tickets, or acceptance criteria (those consume a finished JTBD), or for implementation user stories.

Quantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing—use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.

Provides astronomical data analysis capabilities including coordinate transformations, unit conversions, FITS file handling, cosmological calculations, time systems, and table operations.

Stays current on UI design patterns, tools, and frameworks by monitoring release notes and running targeted search queries.

Summarize Microsoft Teams conversations, triage unread or recent activity, draft follow-ups, and manage Planner tasks through connected Teams data. Use when the user wants to review chats or channels, identify owners and next steps, prepare a safe reply or post, or turn Teams follow-ups into Microsoft Planner tasks.

Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.