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Prepare reproducible setup and removal instructions for software environments on Open-Science SSH hosts, including Slurm clusters. Check available tools, define named activation settings, and validate the environment where jobs run after the user installs it.
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Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.
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When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.
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NEB-IRC activation energy pipeline for reaction barriers using GFN2-xTB and pysisyphus. Optimize reactant and product geometries, run CI-NEB path search, optimize the transition state with a Hessian, verify with IRC (one imaginary mode, endpoints matching reactant/product, single NEB maximum), and report the electronic and Gibbs barriers. Use when you need a transition state, reaction barrier, activation energy, minimum energy path, or intrinsic reaction coordinate. Covers reactant/product atom-ordering pitfalls, feasibility sizing for single-core runs, and thermochemistry corrections. Renders an IRC energy-profile plot and an animated TS imaginary-mode HTML viewer. For 2D reaction scheme drawing use rdkit-chemdraw-cdxml.
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When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.
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Design activation metrics. TRIGGERS - Use when user needs help with activation-metric-design related tasks.
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Use when enabling Data Cloud (Data 360) in an org, creating data spaces, assigning permission sets, registering ingestion API sources, or configuring activation targets. Triggers: 'enable data cloud', 'data spaces setup', 'data cloud permission sets', 'ingestion API connected app', 'activation target setup', 'data cloud licensing', 'dedicated home org vs existing org'. NOT for data streams or DLO-to-DMO mapping — use data/data-cloud-data-streams. NOT for identity resolution rulesets — use admin/data-cloud-identity-resolution.
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Use when defining or auditing the activation event — aha-moment selection, retention correlation, falsifiable definition. Triggers on 'what is our aha moment', 'redefine activation'.
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Behavioral activation for depression: Breaking the vicious cycle, activity monitoring, weekly planning, and values-based activities.
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When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.
中文简介正在准备中。当前显示原文说明。
Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.
中文简介正在准备中。当前显示原文说明。
When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.
中文简介正在准备中。当前显示原文说明。
Design activation metrics. TRIGGERS - Use when user needs help with activation-metric-design related tasks.
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通过一张参考卡查阅ponytail的三个运行级别、相关技能及调用命令，并了解如何启用、停用、设置默认模式和更新。
将收藏数、安装量和激活等每周指标整理为HTML幻灯片，关联变化原因与后续建议，供增长和产品团队在评审会议中讨论并作出决策。
Review existing DeerFlow skill packages for publication readiness, activation rules, safety boundaries, supporting files, and evaluation evidence. Receive concrete findings and suggested replacement text, with a clear distinction between inspection results and verified runtime behavior.
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Plan the conversion of existing Claude Flow commands into specialized agents. Map each command to responsibilities, permitted tools, and activation rules, then outline interaction testing and a gradual rollout that keeps existing commands available during the transition.
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Design and test rules for activating skills through human requests, AI selection, applications, or other skills. Check eligibility before matching descriptions, then return a JSON decision showing the selected channel, score, and policy reason.
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Evaluate an Agent Skill bundle before release by checking structure, activation conditions, output quality, scripts, safety, file integrity, and host compatibility. Receive a detailed JSON report that distinguishes local evidence checks from production readiness backed by external attestation.
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Use a reference template to understand and create Claude Code plugin skills. It explains required metadata, activation descriptions, supporting file layouts, and writing practices so you can organize instructions and specify when the skill should apply.
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Check training data and machine learning models for malicious changes, including backdoors that cause unexpected behavior on specific inputs. Combine data quality checks, model analysis, and file integrity verification, then document findings and retest after remediation.
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Compress large language models to 4-bit weights to reduce GPU memory use and accelerate inference. Covers loading compressed models, configuring quantization, and using Transformers or vLLM, with guidance on hardware requirements and backend choices.
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Turn documentation, code, and specifications into reusable Agent Skills. Define when each skill should activate, organize supporting references, add reproducible examples, and check new or existing skills with templates, a checklist, and a validator.
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Investigate Google Cloud access denials and choose a resolution path based on the caller’s permissions. Supports temporary access activation, structured escalation tickets, policy analysis, and administrator selection of roles that grant only the permissions needed.
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