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概要と使いどころ
Manage PostHog subscriptions — scheduled email, Slack, or webhook deliveries of insight or dashboard snapshots, optionally with an AI-written summary attached to each delivery. Use when the user wants to subscribe to an insight or dashboard, get an AI summary attached to those deliveries, check existing subscriptions, change delivery frequency, add or remove recipients, or stop receiving updates.
日本語の概要は準備中です。原文の説明を表示しています。
Recall project-first and global-supplement ChatCrystal memories before substantive implementation, refactoring, migration, configuration, investigation, or optimization work. Use when the task is non-trivial, has repository or project context, and prior fixes, decisions, pitfalls, or reusable patterns may change the approach.
日本語の概要は準備中です。原文の説明を表示しています。
Write reusable ChatCrystal task memories after substantive work completes. Use when implementation or debugging produced a durable fix, pitfall, pattern, or decision worth preserving, and when the environment can either persist it through `write_task_memory` or emit a structured memory candidate for later save.
日本語の概要は準備中です。原文の説明を表示しています。
Identify and clean up stale feature flags in a PostHog project. Use when the user wants to find unused, fully rolled out, or abandoned feature flags, review them for safety, and then disable or delete them. Covers staleness detection, dependency checking, and safe removal workflows.
日本語の概要は準備中です。原文の説明を表示しています。
ALWAYS use this skill when committing code changes — never commit directly without it. Creates commits following Sentry conventions with proper conventional commit format and issue references. Trigger on any commit, git commit, save changes, or commit message task.
日本語の概要は準備中です。原文の説明を表示しています。
When the same multi-step workflow repeats in Cursor (user corrections or agent redos), capture it as a new SKILL.md under .cursor/skills/ so future sessions load it automatically.
日本語の概要は準備中です。原文の説明を表示しています。
Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.
日本語の概要は準備中です。原文の説明を表示しています。
Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), ligand preparation (meeko, OpenBabel), and ultralarge-library screening (ZINC22, Enamine REAL). Use when screening chemical libraries against a protein target to find candidate binders, ranking docking poses, or selecting a docking workflow for a specific scenario.
日本語の概要は準備中です。原文の説明を表示しています。
Builds and applies 3D pharmacophore models using RDKit Pharm3D, the apo2ph4 receptor-based workflow (Heider et al 2022/2023 J Chem Inf Model 63:147-158), Pharmer / Pharmit (search), and PharmacoForge (diffusion-based generation, Flynn et al 2025 Front Bioinform), covering ligand-based pharmacophore (from active set alignment) and receptor-based pharmacophore (from binding pocket geometry). Explicit handling of feature types, geometric tolerances, partial matching, and pharmacophore-based virtual screening. Use when identifying scaffold-hopping candidates, building shape-and-feature search queries, or transferring SAR across chemotypes.
日本語の概要は準備中です。原文の説明を表示しています。
Continue working on an OpenSpec change by creating the next artifact. Use when the user wants to progress their change, create the next artifact, or continue their workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
日本語の概要は準備中です。原文の説明を表示しています。
Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Start a new OpenSpec change using the experimental artifact workflow. Use when the user wants to create a new feature, fix, or modification with a structured step-by-step approach.
日本語の概要は準備中です。原文の説明を表示しています。
Guided onboarding for OpenSpec - walk through a complete workflow cycle with narration and real codebase work.
日本語の概要は準備中です。原文の説明を表示しています。
Author and diagnose YAML, prototype schemas, workflows, manifests, and structured configuration with exact validation.
日本語の概要は準備中です。原文の説明を表示しています。
Preserve user work, scope, metadata, history, and verifiable delivery.
日本語の概要は準備中です。原文の説明を表示しています。
Modify NPC behavior, HTN tasks, navigation, steering, prototypes, and AI debugging.
日本語の概要は準備中です。原文の説明を表示しています。
Plan, verify, implement, and deliver repository work through evidence-backed ownership and quality gates.
日本語の概要は準備中です。原文の説明を表示しています。
Turn product requirements into scoped tasks with dependencies and acceptance criteria. Use for implementation planning and prioritization.
日本語の概要は準備中です。原文の説明を表示しています。
Ultrawork - high-quality 5-phase development workflow with 11 review steps out of 17
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Configure development tasks, git hooks, CI/CD, or release automation. Use when creating or fixing a repository development workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Build AI pricing optimization. TRIGGERS - Use when user needs help with ai-pricing-optimizer related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Build AI dynamic pricing systems. TRIGGERS - Use when user needs help with ai-price-optimizer related tasks.
日本語の概要は準備中です。原文の説明を表示しています。