Results for “edge-research”

Use when designing solutions to identify and test boundary conditions, unusual inputs, and uncommon scenarios that could cause failures. This skill provides a systematic approach to finding edge cases before they become bugs in production.

Convert daily market observations into structured research tickets and export validated candidate specs for a trading strategy pipeline.

Analyze and improve the internal link structure of an AEM Edge Delivery Services site by building a link graph from the query index and page content, identifying orphan pages, hub pages, and content silos, and generating specific linking recommendations with suggested anchor text and placement.

Audit images across AEM Edge Delivery Services pages for SEO and performance, checking alt text quality, dimensions, lazy loading, fetch priority, file naming, and decorative image handling, and generate per-page reports with fix instructions.

Rewrites AEM Edge Delivery Services page content for AI search discoverability (Generative Engine Optimization) by analyzing structure, clarity, and factual density.

Reviews trading strategy drafts for edge plausibility, overfitting risk, sample size adequacy, and execution realism, outputting PASS/REVISE/REJECT verdicts with confidence scores.

Walk every branching path and boundary condition in content, report only unhandled edge cases. Orthogonal to adversarial review - method-driven not attitude-driven. Use when you need exhaustive edge-case analysis of code, specs, or diffs.

Walk every branching path and boundary condition in content, report only unhandled edge cases. Orthogonal to adversarial review - method-driven not attitude-driven. Use when you need exhaustive edge-case analysis of code, specs, or diffs.

Measures the trade-off between computation time and energy consumption in mobile edge computing by computing a weighted sum of the two objectives, given system configuration parameters and per-user task characteristics.

Research the open web for enhancement opportunities (Layer 3 — Opus subagent with WebSearch + WebFetch). Topic-driven. Returns structured findings with hype tags + source URLs. Does NOT auto-implement.

Forge Research — Forge Skill

Walk every branching path and boundary condition in content, report only unhandled edge cases. Orthogonal to adversarial review - method-driven not attitude-driven. Use when you need exhaustive edge-case analysis of code, specs, or diffs.

Produces decision-oriented market research, competitive analysis, investor due diligence, and industry intelligence with source attribution.

Frontier research tracking and trend scouting specialist. Use when the user asks to talk to Fade, requests the scout, or needs arxiv monitoring, paradigm shift detection, and emerging method analysis.

进行市场研究、竞争分析、投资者尽职调查和行业情报，附带来源归属和决策导向的摘要。适用于用户需要市场规模、竞争对手比较、基金研究、技术扫描或为商业决策提供信息的研究时。

Research companies, industries, or competitor sets using web search and seven analytical lenses to produce structured intelligence for downstream product management tasks.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Aggregate and rank signals from multiple edge-finding skills into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.

Route research prompts to evidence, retrieval, scraping, data, market, or scientific research skills. Use when prompts mention deep research, current facts, citations, Exa, iterative retrieval, search-first, scraping, data pipelines, PubMed, USPTO, gget, literature review, or scholar evaluation.

Search external documentation (web pages, API docs, papers) and generate useful summaries for development. Use when investigating new technologies, understanding third-party APIs, researching best practices, or gathering information for technical decisions. Reduces hallucinations and expands agent knowledge.

Clusters raw detection tickets into reusable edge concepts with thesis, invalidation signals, and strategy playbooks before strategy design.

端到端研究编排器：idea 发现 → 实验设计 → 执行 → 判决 → 论文撰写，带人工门控和状态恢复

NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-face...

Skeptical pushback on the research dossier before it feeds the outline. Asks whether claims are cited, whether surprising findings are actually surprising, whether we missed the strongest competitor angle. One revision pass on FAIL (BLOG_AGENT_RESEARCH_REVISION_BUDGET, default 1).

Audit and optimize headings across AEM Edge Delivery Services pages for search intent, hierarchy, and consistency.

Migrate Jetpack Compose apps to support edge-to-edge displays, fix UI components obscured by system bars, and handle IME insets.

Identifies error-prone APIs, dangerous configurations, and footgun designs that enable security mistakes in API designs, configuration schemas, and cryptographic library ergonomics.

Searches the aem.live documentation for information on AEM Edge Delivery Services features, then fetches and reads full page content for detailed guidance.

Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.

Generate structured research briefs from RSS feeds and web sources on any topic. Synthesizes multiple sources into actionable analysis with key findings, data points, expert perspectives, and content angles.

Convert daily market observations and news reactions into structured edge hints, with optional LLM augmentation, outputting a canonical hints.yaml for downstream concept synthesis.

Search the web, extract URL content, enrich datasets with web-sourced fields, and run deep research reports, prioritizing academic and scientific sources.

Structured deep research workflow with human-in-the-loop control. Use /research to generate research outline, /research-deep for parallel web search across items, /research-report to compile markdown reports. Supports academic research, benchmark research, technology selection, market analysis, and due diligence. Triggers: 'deep research', 'research topic', 'benchmark comparison', 'technology survey', 'market analysis'. Requires: WebSearch capability.

Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

金融经济学实证论文计划书生成器。根据用户提供的研究方向，生成包含标题、假说、数据来源、实证策略、 预期结果表格、稳健性检验、异质性分析、机制检验等12个完整模块的研究计划书。 内置中国微观/宏观数据库（皮皮侠1599个数据集、马克数据377个数据集）和WRDS国际数据库索引， 自动匹配可用数据源。融合Edmans (2024) "Learnings From 1000 Rejections"的编辑视角作为质量护栏， 确保选题具有真正的边际贡献而非"just another determinant of Y"。 当用户提到以下任何情境时触发：写研究计划书、research proposal、论文开题、选题+计划、 帮我设计一个实证研究、empirical research design、我想研究X对Y的影响怎么做、 帮我找个能发表的选题、generate proposal、写一个可以投稿的研究方案、 研究设计、identification strategy、DID/RDD/IV研究设计。 即使用户只是描述了一个经济金融现象并想知道"能不能做成论文"，也应考虑使用此技能。