Research & Search

dinhanhthi Bundle

Quick Q&A about the codebase → docs/memory. Use for focused project questions — e.g. "how does X work?", "where is Y defined?", "what's the flow for Z?", "explain this module", "why is this done this way?". Unlike /cf-research, one answer.

dinhanhthi Skill

Catch up after absence — summarize git history for a user. Triggers: "warm up", "catch me up", "what happened while I was away", "summarize recent changes", "what changed since I left".

dinhanhthi Bundle

In-depth research with web search and structured output. Triggers: "research this", "look into this library", "investigate how X works", "compare these options", "best practices for", "deep dive into", "study this technology".

dinhanhthi Skill

Completion gate — demands fresh verification evidence (test run, command output, manual check) before any claim that work is done. TRIGGER — about to say "done", "complete", "fixed", "passing", "ready to commit" or "ready to ship", or to summarize finished work; the end of any cf-tdd, cf-fix, cf-plan, or cf-optimize run; the user asks "is it done?" or "does it work?". SKIP — mid-task progress notes, exploratory or read-only answers, and plans that have not been implemented yet.

wanshuiyin Skill

Draft a structured grant proposal from research ideas and literature. Supports KAKENHI (Japan), NSF (US), NSFC (China, including 面上/青年/优青/杰青/海外优青/重点), ERC (EU), DFG (Germany), SNSF (Switzerland), ARC (Australia), NWO (Netherlands), and generic formats. Use when user says "write grant", "grant proposal", "申請書", "write KAKENHI", "科研費", "基金申请", "写基金", "NSF proposal", or wants to turn research ideas into a funding application.

wanshuiyin Skill

Search published venue papers (IEEE, ACM, Springer, etc.) via Semantic Scholar API. Complements /arxiv (preprints) with citation counts, venue metadata, and TLDR. Use when user says "search semantic scholar", "find IEEE papers", "find journal papers", "venue papers", "citation search", or wants published literature beyond arXiv preprints.

wanshuiyin Skill

Fill in the per-paper TODO sections of research-wiki/papers/<slug>.md pages that literature-ingest skills leave as bare scaffolds. Use when user says 'enrich wiki', 'fill paper TODOs', 'wiki body 補完', '把 paper 摘要寫進 wiki', 'research-wiki 自動填', or after a batch ingest that left papers/ as TODO scaffolds.

wanshuiyin Skill

Generate and rank research ideas given a broad direction. Use when user says "找idea", "brainstorm ideas", "generate research ideas", "what can we work on", or wants to explore a research area for publishable directions.

wanshuiyin Skill

Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.

wanshuiyin Skill

Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.

wanshuiyin Skill

Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-6-Astra review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.

cwinvestments Skill

Use this skill when the user says 'analyze feedback', 'feedback analysis', 'what are customers asking for', or has support tickets, reviews, or survey data to categorize, score, and prioritize into actionable reports. Do NOT use for competitor analysis or market research.

aviskaar Skill

Use this skill when building or operating a continuous, automated benchmarking system that tracks competitor performance, ingests the latest research, generates improvement hypotheses, runs experiments autonomously, and keeps a solution ranked

aviskaar Bundle

Use this skill when a product management team needs a fully automated, AI-powered product intelligence platform — managing multiple product areas or initiatives simultaneously, running continuous competitive monitoring, synthesizing cross-portfolio signals, generating research-backed product bets, and producing PRDs, roadmaps, and proposals at portfolio scale. The top-level PM orchestrator.

aviskaar Skill

Use this skill when drafting, editing, or refining AI/ML research papers, abstracts, related work sections, introductions, or rebuttals. Applies academic writing conventions and improves clarity, flow, and precision.

aviskaar Skill

Use this skill when designing ML/AI experiments, evaluation protocols, or research benchmarks. Guides hypothesis specification, baseline selection, metric choice, and experimental controls to ensure results are valid and reproducible.

aviskaar Skill

Use this skill when you need to survey a research domain, discover and formulate open problems worth solving, prioritize them by impact and feasibility, and commission Principal Scientist agents to execute the research. Activate when the user wants to define a research agenda from scratch, identify the most valuable unsolved problems in a field, or systematically advance knowledge across a domain over multiple research cycles — rather than executing a single already-defined project.

aviskaar Skill

Use this skill when managing a portfolio of research projects that require multiple parallel research tracks, competing hypotheses explored simultaneously, or a combination of autonomous research and continuous benchmarking. Activate when the user needs to coordinate multiple lead-researcher agents in parallel — each pursuing a distinct track or hypothesis — while maintaining a unified strategic direction. Also use this skill when research must be paired with continuous competitive benchmarking via the auto-benchmark skill to validate gains against real leaderboards.

aviskaar Skill

Use this skill when generating a complete, publication-ready IEEE research paper from experiment data, results, or research findings. Applies to conference papers (e.g., ICML, NeurIPS, CVPR, ICCV, EMNLP, ACL) and journal articles following IEEE Transactions formatting conventions. Covers all sections from title through references, adhering to IEEE style, structure, and citation format.

aviskaar Skill

Use this skill when asked to synthesize, survey, or summarize a body of research papers on a topic. Produces a coherent narrative across multiple sources, identifying themes, consensus, contradictions, and open questions.

aviskaar Skill

Use this skill when generating, refining, or stress-testing research hypotheses for AI/ML problems. Produces well-formed, falsifiable hypotheses grounded in existing literature and mechanistic reasoning.

aviskaar Skill

Use this skill when asked to review, critique, or analyze an AI/ML research paper. Provides a structured evaluation covering contributions, methodology, experimental validity, and limitations.

chengyi818 Skill

Use when 多源研究工作流 (论文/文档/网页) - 芯片选型调研、技术方案对比。

vstorm-co Skill

Answer a research question with authority, currency and the counter-argument.

vstorm-co Skill

Summarise an application pack into the facts a credit decision needs, and nothing else.

vstorm-co Skill

Answer staff questions from SOPs and guidelines with a citation, and refuse when the procedure is silent.

mathews-tom Bundle

Orchestrates business idea validation via parallel sub-agents: Lean Canvas, JTBD, market/competitive/feasibility research, SWOT/PESTLE, and a weighted scorecard with verdict. Triggers on: "validate this idea", "evaluate my startup idea", "is this idea worth pursuing", "score this business idea", "validate my pitch".

mathews-tom Bundle

Converts research papers into executable skill packages via document conversion, critical analysis, and co-evolutionary refinement. Triggers on: "convert this paper to a skill", "paper-to-skill", "extract methodology from paper", "make a skill from this paper". NOT for literature review, use research-critique.

mathews-tom Bundle

Extract YouTube transcripts and produce structured concept analysis with multi-level summaries, key concepts, takeaways. Uses youtube-transcript-api with yt-dlp fallback. Triggers on: "analyze youtube video", "youtube transcript", "summarize this video", "extract concepts from video", "video key points", or any youtube.com/youtu.be URL.

mathews-tom Bundle

Systematic literature review workflow: scope, search (arXiv, Semantic Scholar, Google Scholar), screen, extract, synthesize, and identify gaps. Triggers on: "literature review", "survey the literature", "related work", "systematic review", "synthesize the research", "find papers about", "research gap analysis".

mathews-tom Bundle

Critical analysis of research papers evaluating methodology, claims-evidence alignment, and contribution significance. Triggers on: "critique this paper", "review this research", "analyze this study", "evaluate the methodology", "is this paper sound". NOT for formatting or submission readiness, use manuscript-review.

amazon-quick Bundle

Researches and identifies ideal prospects for small business sales. Builds targeted lead lists with company intel, decision-maker contacts, and personalized talking points. Use when user says 'find me leads', 'build a prospect list', 'who should I sell to', 'research companies in [industry]', 'find decision makers', 'identify potential customers', or 'prospect list for [product/service]'.

amazon-quick Bundle

Draft clinical trial protocol sections grounded in ICH guidelines and FDA regulations, starting from a grant document or study synopsis. Generates Objectives, Background & Rationale, Study Design, and assembles them into a cohesive protocol document. Use when asked to 'draft a clinical trial protocol', 'write protocol objectives from this grant', 'generate a study design section', 'create a protocol from my synopsis', 'draft IND protocol sections', or any request to produce ICH/FDA-compliant protocol text from research source documents.

amazon-quick Skill

Extracts, classifies, and risk-scores key clauses from contracts and legal agreements. Identifies standard vs non-standard terms, flags high-risk provisions (unlimited liability, broad indemnification, auto-renewal), and produces structured clause inventories with plain-language summaries. Use when asked to 'review this contract', 'extract key clauses', 'flag risky terms', 'contract risk assessment', 'what are the key provisions', or 'summarize this agreement'.

amazon-quick Skill

Summarize daily standup notes into blockers, progress, and plans. Use when asked to 'summarize standup', 'process standup notes', or 'daily summary'.

amazon-quick Skill

Read and condense academic research papers into layered, audience-adaptive summaries. Handles local PDFs, preprint repository URLs, and DOIs. Produces structured output calibrated to reader expertise (expert, adjacent, executive) at configurable depth (tldr, executive, full). Use when asked to 'read this paper', 'summarize this paper', 'condense this paper', 'digest this paper', 'what does this paper say', 'break down this paper', 'explain this paper', 'paper summary', 'TLDR this paper', 'analyze this paper', 'review this paper', or 'parse this paper'.