「ada」の検索結果

Custom training plans by goal (strength, cardio, flexibility). Progressive overload programming, rest day optimization, home vs gym adaptations, deload weeks.

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。

Optimize content for search engines with keyword analysis, readability scoring, meta descriptions, and competitor comparison. Use this when users want to improve SEO, optimize blog posts, or analyze content for search performance.

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。

Convert content between platforms (blog to Twitter thread, article to LinkedIn post, etc.). Optimize for each platform's format, tone, and best practices. Use when user wants to adapt content for different social media platforms.

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。

Generates customized client onboarding checklists with phased tasks, ownership assignments, dependencies, acceptance criteria, and email templates. Adapts to consulting, SaaS, or agency engagement models.

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。

Sweep a contracts folder and extract every renewal date, auto-renew clause, notice window, and price-escalation term into a renewal calendar -- then create calendar reminders ahead of each notice deadline via Cowork's calendar write tools. The skill that stops auto-renewals from ambushing you.

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 the current local Codex conversation and coding task in an AgentKit Studio cloud Codex Sandbox using a Studio URL and short one-time pairing code. Use when the user asks to hand off, migrate, or continue a local repository in Studio, especially when a prompt contains a Studio address and pairing code. Export the complete user-visible user and assistant message history from every prior turn, including interrupted turns and progress commentary, create a temporary Studio Sandbox, restore tracked and non-ignored working-tree files plus Git metadata, inject that visible history into the cloud Thread, transfer GitHub CLI authentication separately when needed, and send one final continuation message; never copy system or developer prompts, reasoning, tool logs, SQLite state, global configuration, local skills, or SSH private keys.

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。

Provides error classification, recovery, and graceful-degradation patterns. Use when implementing error handling or debugging resilience failures in any skill.

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。

Presents adaptive codebase challenge questions with multiple-choice and trace exercises. Use when testing contributor knowledge of the codebase.

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。

Use when running a systematic review and meta-analysis, DTA or intervention. Covers PROSPERO protocol, search, screening, extraction, risk of bias (QUADAS-3, RoB 2, ROBINS-I), bivariate/HSROC or random-effects pooling, forest plots, heterogeneity and PRISMA reporting. Topic scouting is /ma-scout.

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。

Use when sending local changes back to the project (an added journal profile, a fixed checklist item, an adapted skill) or reporting a false positive or bug. Finds what changed, scans it for patient data, shows every line and sends nothing until you confirm.

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。

Use when turning a personal agent skill into an open-source, distributable one. Runs a PII audit, generalizes personal details, checks licence compatibility, reviews cross-platform adapters and walks through packaging.

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。

Use when analyzing a researcher's publication record from PubMed. Fetches an author's papers, classifies study types and author position, charts the patterns and writes a strategy report, with an optional trajectory-archetype classification. Works from PubMed metadata only.

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。

Use when auditing a manuscript item by item against a reporting guideline or risk-of-bias tool. Covers 49 reporting guidelines and risk-of-bias tools (STROBE, CONSORT, STARD, TRIPOD+AI, PRISMA, QUADAS and more), marking each item PRESENT, PARTIAL or MISSING. Not a reviewer critique (/self-review).

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。

Use when preparing an academic talk such as a journal club, grand rounds, seminar, conference presentation, or lecture/teaching deck. Analyzes the source, drafts audience-adapted speaker scripts, builds or augments the PPTX with speaker notes and prepares Q&A.

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。

Maintain an online covariance over named series whose set changes over time (e.g. assets entering and leaving). Use when observations arrive as dicts keyed by name rather than fixed-length vectors. Wraps precise's keyed / FixedUniverse / DynamicUniverse adapters.

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。

Operate and extend GeoNode geospatial content-management deployments, resource APIs, uploads, metadata/catalogues, GeoServer security, harvesting, and administration with explicit service and safety 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。

Create, polish, and troubleshoot figures4papers-style publication-ready matplotlib figures, including grouped bars, trends, radar charts, heatmaps, concept diagrams, manifolds, and high-DPI/vector export 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。

Use the GeoParquet specification and bundled inspection helpers to author, validate, distribute, or safely review geospatial Parquet data, including GeoParquet 2.0 vector metadata, external writer choices, and the alpha Parquet Raster proposal.

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。

Use this skill for Hugging Face Diffusers tasks: pipeline inference, schedulers, adapters/loaders, training recipes, modular pipelines, conversion helpers, CLI checks, and repo maintenance.

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。

Use the einops Python package for readable tensor rearrangement, reductions, repetition, named-axis einsum, packing, framework layers, and repository maintenance 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。

Use when you need to design DataDesigner configs, run preview/create/validate workflows, inspect the CLI or agent context, work with plugins or MCP tools, or adapt documented recipes and integrations for synthetic dataset generation.

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。

Use Atomic Agents to build schema-driven agents, integrate tools and MCP connectors, adapt example applications, and maintain the monorepo safely.

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。

Route auto-sklearn AutoML estimator, data validation, search, custom component, and metadata-maintenance 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。

Routes agents working with Axolotl config-driven LLM fine-tuning, datasets, SFT, preference tuning, GRPO/EBFT, model adapters, distributed training, CLI operations, and troubleshooting.

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。