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Clarify responsibilities in a TeamHarness team, including planning, task execution, result acceptance, and runtime administration. Use the role boundaries to identify who owns each action and how participants should handle sensitive information.
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Manage an assigned Worker task from acceptance through delivery using taskflow. Keep work and optional progress notes in the task directory, submit structured results with deliverable paths, and report completion or blockers to the coordinator.
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Turn ready project tasks into clear instructions for AI workers, with defined ownership, deliverables, acceptance criteria, and reporting rules. Handle assignment notifications and check submitted results before passing them to the project management workflow for acceptance.
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Organize research reports around what readers need to understand or decide. Choose structures for overviews, comparisons, background investigations, or event tracking, with specialized formats for academic, medical, legal, and policy reports that make evidence and uncertainty explicit.
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Add an animation that makes a finished interface look as though an AI agent is building it. It traces the element’s actual layout with dots, then reveals the interface, optionally alongside generation logs and CSS text.
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Compare choices using weighted scores, pros and cons, possible failure scenarios, and what each option means giving up. Make preferences and uncertainty explicit, rank alternatives, and identify information that could change the decision.
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Assess internet-exposed VMware management services by identifying versions, matching known vulnerabilities, and checking authentication settings and information exposure. Use the findings to document affected services, supporting evidence, and the potential impact on virtual infrastructure.
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Investigate SSRF, where supplied URLs cause unintended server requests, in previews, imports, proxies, and PDF generation. Confirm outbound connections, identify the responsible input, and establish whether internal services or sensitive responses are accessible.
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Investigate authentication gaps across single sign-on, APIs, and legacy login endpoints. The skill helps map entry points, compare their protections, test token trust between portals, and document whether a flaw grants access to protected accounts or functions.
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Use SymPy in Python to solve equations, simplify formulas, calculate derivatives and integrals, and work with matrices. Keep exact results such as fractions and square roots, then turn expressions into executable code or LaTeX.
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Create summary tables, treatment and control comparisons, and correlation matrices using Python, R, or Stata. Summarize averages, variation, sample sizes, and missing data to understand a dataset before regression or prepare tables for a research paper.
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Build reproducible empirical analyses in R, from data cleaning to statistical modeling and publication tables and figures. Covers economics, epidemiology, and machine learning approaches to causal inference, which estimates effects of interventions.
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Build a Python workflow for empirical research, from data cleaning and statistical checks to estimation, robustness checks, and paper-ready tables and figures. Economics is the default, with additional modes for epidemiology, public health, and machine learning for causal inference.
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Compare a recreated app with its reference using weighted feature coverage, screenshot layout differences that ignore color, and workflow reviews. Generate a report showing missing functionality, release readiness, and the next five implementation priorities.
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Map an existing app’s screens, user journeys, reusable interface parts, and likely data structure using public sources and your own account. Produce a research document and prioritized feature table to guide development of your own version.
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Evaluate a content idea before production using seven criteria, including audience fit, traffic potential, cost, and risk. Receive scores with reasons, a recommendation to proceed, revise, or skip, and improvements or alternative ideas.
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Handle equations, calculus, matrices, unit conversions, and mathematical explanations through one entry point. The skill selects a suitable calculation tool or topic guide, including symbolic math tools that work directly with expressions.
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Investigate runtime behavior that code review and normal tests cannot resolve. Plan controlled cases, disclose commands and effects for approval, then use temporary scripts to report observed results, comparison conditions, and supporting evidence.
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Organize paper or report submissions with stage-specific checklists and templates. Link checks to actual files, prepare cover letters, and track each reviewer comment alongside the response, revision, and location of the change.
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Work with mathematical formulas in Python to solve equations, calculate derivatives and integrals, and manipulate matrices. Keep exact results using symbols, then turn expressions into executable code or formatted LaTeX equations.
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Study and apply statistics, probability, and linear algebra through Python examples. Calculate summary statistics, compare groups, analyze A/B tests, and build regression models while checking assumptions and considering the size of observed differences.
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Explore research ideas through conversation, question existing assumptions, and connect methods across disciplines. The skill helps identify research gaps, compare ways to combine papers, and summarize promising directions with practical next steps.
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Handle equations, calculus, matrices, unit conversions, and mathematical explanations through one entry point. The skill selects a suitable calculation tool or topic guide, including symbolic math tools that work directly with expressions.
中文简介正在准备中。当前显示英语简介。
Implement and troubleshoot storage recovery with DOCA Erasure Coding. The skill guides parity generation, lost-block recovery, and incremental parity updates using Reed-Solomon coding, while checking device capabilities, block limits, and memory permissions.
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