「tar」の検索結果

Analyze live crypto K-line, price-volume, market-structure, and derivatives evidence, then turn it into a conditional trading plan with exact entry, invalidation, targets, position sizing, leverage, and three risk tiers. Use when a user wants both market analysis and an actionable risk-managed plan, asks whether or how to trade a coin, or requests entry/stop/target/size levels. Do not use for placing orders, managing an existing account, or guaranteeing returns.

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Coordinates private placement execution with investor targeting, NAIC designation analysis, and shelf registration requirements. Use when managing PP offerings, targeting insurance company investors, or structuring private notes.

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。

Structures investor day content with long-term strategy presentation, financial targets, and capital allocation framework communication. Use when preparing investor days, designing strategy presentations, or building financial target frameworks.

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。

Constructs proprietary factor definitions with signal specification, universe application, and orthogonalization methodology. Use when defining custom factors, creating proprietary signals, or building factor libraries.

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。

Maps institutional investor targeting with AUM analysis, sector allocation preferences, and historical participation patterns. Use when targeting investors, analyzing demand profiles, or building investor marketing lists.

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。

After /start-task: park the current clean, pushed feature branch in its own issue-numbered nested worktree (.worktrees/<issue#>) and return the primary checkout to current main, so the next parallel lane can start. Use when the user says to move the branch or task to a worktree or open a parallel lane.

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。

Bootstrap a task into a synced feature branch — one shot, zero confirmations. Detects the source from the args: GitHub issue ('#100', 'issue 100', 'gh issue 100', or bare '100'), Jira key ('PROJ-42'), or a local spec file path; ad-hoc conversation otherwise. Fetches the task, derives {type}/{number}/{slug}, syncs the default branch, creates and pushes the branch, and writes specs/context/<id>.md. Use only when the user explicitly asks to start a task or create a work branch — never trigger 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。

Scaffold a new Android app with SDLC and Play-safe defaults — Kotlin/Compose Gradle project with version catalog, convention plugins, module layout, a targetSdk that meets the Play mandate, R8 on release, and git-ignored signing so it passes the pre-flight checker from day one. Use when starting a new Android project.

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。

Prevents premature execution on ambiguous requests. Analyzes request clarity using 5W1H decomposition, surfaces hidden assumptions, and generates structured clarifying questions before work begins. Use at the start of any non-trivial task, or when a request could be interpreted multiple ways. Triggers on "뭘 원하는건지", "요구사항 정리", "clarify", "what exactly", "scope", "requirements", "정확히 뭘", "before we start".

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。

Generate cinematic case study pages for films, documentaries, photography portfolios, and creative projects — film-frame hero images, structured crew credit grids, dark footage galleries, festival award sections, scroll-choreographed reveals via data-attribute animation orchestration. Warm cream palette with analog typography. Single-file HTML, zero build step. Triggers on film case study, documentary showcase, filmmaker portfolio, production company website, film credits page, creative project case study, director portfolio, photography case study.

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。

Generate physically-based atmospheric scattering shaders — sky domes, planetary atmospheres, LUT-optimized pipelines, depth-aware post-processing. Four modes — sky-dome, atmosphere-post, planet, lut. Triggers on atmospheric scattering, sky shader, sunset rendering, planet atmosphere, Rayleigh scattering, Mie scattering, volumetric sky, sky dome, atmosphere post-processing, aerial perspective, transmittance LUT, sky rendering, realistic sky, planetary rendering.

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。

Find and score legitimate external authority and backlink opportunities as a dry-run register, using relevance, platform rules, risk, target-page fit, and explicit user approval gates. Use this skill when the user asks where links to a target site could be placed effectively, but never post, submit, DM, email, open PRs, or edit external accounts without separate explicit approval.

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。

Run a read-only parallel Kimi review fan-out across many independent targets. Use only for explicit broad fan-out requests where one subagent per target is the point.

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。

Decide whether a protein has a pocket worth targeting, and where it is, before committing to a docking or design campaign. Use this skill to run fpocket cavity detection, rank cavities by druggability and volume, compare apo and holo conformations to spot induced fit, identify allosteric and cryptic cavities that only open in simulation, and convert a chosen cavity into the search box coordinates a docking run needs. Also trigger on fpocket, cavity detection, druggability score, alpha sphere, cryptic pocket, allosteric site, pocket volume, hotspot mapping, or undruggable target assessment.

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Query the ChEMBL database web services for measured bioactivity data, compound records and calculated properties, targets, assays, mechanisms of action, drug indications and warnings. Use this skill to build curated SAR or QSAR datasets for a target, look compounds up by SMILES, InChIKey, name, or ChEMBL id, run similarity and substructure searches, and check what chemistry is already known against a protein. Also trigger when a query mentions ChEMBL ids (CHEMBL...), pChEMBL values, IC50/Ki/Kd/EC50 retrieval, assay confidence scores, or ebi.ac.uk/chembl.

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。

Generalised autonomous optimisation loop — soft RLVR for any artifact a user can measure. Web runtime package: uses memory in this order: connector-backed, project-pack, none. Never assumes subprocess access or unrestricted local files. Use this skill whenever a user wants to iteratively improve an artifact — code, prompts, documents, configs, designs, content — by running structured experiments, evaluating results against a multi-dimensional rubric, and learning from each attempt. Triggers include: "optimise this", "keep improving until it's good", "run experiments on", "autoresearch", "iterate on this overnight", "try different approaches and pick the best", or any request implying repeated evaluate-and-improve cycles.

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。

Generalised autonomous optimisation loop — soft RLVR for any artifact a user can measure. Use this skill whenever a user wants to iteratively improve an artifact — code, prompts, documents, configs, designs, content — by running structured experiments, evaluating results against a multi-dimensional rubric, and learning from each attempt. Triggers include: "optimise this", "keep improving until it's good", "run experiments on", "autoresearch", "iterate on this overnight", "try different approaches and pick the best", or any request implying repeated evaluate-and-improve cycles. Also use when the user wants to improve a system prompt, a data pipeline, a writing style, or any artifact where quality can be decomposed into measurable tracks. For inference optimisation tasks (model latency, throughput, quantization, GPU deployment), a* delegates the low-level tuning to AITune while maintaining quality tracking and learning.

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。

UX/マーケティング向けのユーザーペルソナを、5つの専門エージェントチームで作成するスキル。 ペルソナ設計、ユーザーリサーチ、ナラティブ執筆、バイアスレビュー、データ検証の 5観点からペルソナをディスカッション型で議論・作成し、Markdownドキュメントとして出力する。 data-critic がライブモデレーターとして矛盾を検出・収束を判定する。 コンテキストファイルで過去のセッションを引き継げる。 Use when: ユーザーペルソナを作りたい、ターゲットユーザーを定義したい、 ペルソナシートを作成したい、UXリサーチ用のペルソナが必要、 マーケティング用のターゲット分析をしたい。 Triggers: "ペルソナ", "persona", "ターゲットユーザー", "target user", "ユーザー像", "ユーザー定義", "user profile", "ペルソナシート", "ターゲット分析", "ユーザーセグメント", "customer profile"

PlantUML Salt 記法でワイヤーフレームを正確に生成するためのベストプラクティスガイド。 Salt 特有のハマりポイント（横並び `} | {` の1行ルール、列数統一、ネスト閉じ括弧）を防ぎ、 モバイルアプリやWebアプリのワイヤーフレームを高精度で生成する。 Use when: PlantUML Salt でワイヤーフレームを生成するとき。 画面設計をテキストベースで行うとき。Salt 図が壊れたとき。 機能から画面構成に落とすとき。ワイヤーフレームを Markdown に埋め込むとき。 Triggers: "Salt", "salt", "PlantUML", "plantuml", "ワイヤーフレーム", "wireframe", "画面設計", "画面構成", "@startsalt", "Salt図"

Guide a person through a Coordinate Remote Viewing (CRV) session following the Stargate/SRI protocol. AI acts as the monitor/tasker role, managing protocol progression, catching Analytical Overlay (AOL), and redirecting the viewer through stages I-VI. Use when a person wants to practice CRV and needs a monitor to manage the session protocol, when training a viewer through the staged CRV process, facilitating a structured intuitive perception exercise, or developing non-local awareness skills that complement healing 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。

Run the memex session-init ritual at the start of a fresh session: load the bias-log, read the persistent-self trail in order, run the verification scoreboard, and surface the next slice from the docs. Use at the very start of any session that operates on the memex repo, when reconstructing context before doing work, or when an interrupted session needs to re-orient. NOT the `memex init` CLI command (which initializes the store/db) — this is the reconstruct-context ritual.

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 insects using body plan analysis, dichotomous keys to order, wing venation, mouthpart type, antennae form, leg and tarsal structure, and confidence levels. Covers the fundamental hexapod body plan verification, a simplified dichotomous key to major orders, wing venation and type analysis, mouthpart classification, antennae morphology, leg specialization and tarsal formula, and a structured confidence assessment framework. Use when you need to identify an unknown insect beyond preliminary order placement, are working through a specimen for taxonomic study, want to distinguish between similar orders or families, or need to assign a confidence level to a field identification.

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。

Systematically interpret Raman spectra to identify molecular vibrations, assess polarizability-driven selection rules, compare with complementary IR data, and evaluate depolarization ratios for symmetry assignment. Covers Raman-active mode identification, fluorescence interference mitigation, and reference spectrum matching.

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。

Conduct temperament-based health assessment from Hildegard von Bingen's Causae et Curae. Evaluates the four temperaments (sanguine, choleric, melancholic, phlegmatic), elemental correspondences (air, fire, earth, water), and provides dietary and lifestyle recommendations for rebalancing. Use when understanding constitutional type in Hildegardian terms, experiencing imbalance (fatigue, digestive issues, mental fog) needing holistic guidance, seeking dietary recommendations by temperament, or researching medieval humoral medicine.

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。