「serve」の検索結果

科学計算の単位と測定の不確かさを扱い、換算、誤差の伝わり方、有効数字を確認します。Pythonコードの点検や、計算結果の桁が物理的に妥当かの確認にも使えます。

• 不確かさを保って単位換算したいとき
• 校正データから不確かさの内訳を作りたいとき
• Pythonの単位・不確かさの扱いの点検

観察終了までに出来事が起きなかったデータを含む生存時間分析で、情報漏れを防ぐ前処理、モデル選択、確率予測、打ち切りを考慮した評価を進めるスキル。

• CSVのイベント列と観察時間の検証
• 評価データの情報漏れを防いだモデル学習
• 打ち切りを考慮した生存確率の評価

保存済みのPrimeKGデータから、遺伝子・薬剤・疾患・症状の関係を調べます。直接の関連や中間要素を一つ挟む経路を、関係の種類とデータの出所を保って取得します。

• 遺伝子・薬剤・疾患の関連を調べたいとき
• 疾患に関連する遺伝子・薬剤・症状の整理
• 二つの要素を結ぶ短い経路の探索

Builds with and operates Pi, the minimal terminal coding harness. Use for installing Pi, configuring providers/models/settings/environment variables, creating Pi skills/extensions/packages/themes/prompt templates, embedding Pi through the SDK, integrating over RPC or JSON event streams, parsing sessions, running local models through the llama.cpp router, developing custom Pi providers and TUI components, or using ecosystem packages such as pi-subagents (delegation/orchestration), pi-mcp-adapter (MCP servers), pi-interview (interactive forms), and pi-web-access (web search, fetching, video understanding).

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。

Zoteroの文献をPythonから検索・登録・更新し、コレクションやタグの整理、PDF添付、引用データの書き出しなど研究資料の管理を支援するスキル。

• Zotero内の文献を検索したいとき
• 文献をコレクションやタグで整理したいとき
• 文献にPDFを添付したいとき

ペアエンド16S配列をQIIME 2で処理し、配列の種類と分類情報をまとめます。入力ファイルやプライマー、読み取り配列の残存率を確認し、処理履歴も保存します。

• FASTQペアとサンプル情報を検証したいとき
• プライマー除去とDADA2処理をしたいとき
• 互換性のある分類器で分類したいとき

Converts neuroscience acquisition data to Neurodata Without Borders files with NeuroConv and PyNWB, preserves metadata and timebases, checks evidence-based clock alignment, and produces schema validation, NWB Inspector findings and round-trip checks. Use for NWB conversion and synchronization of planar single-channel two-photon TIFF imaging plus timestamped behavioral position CSV; this skill does not perform spike sorting or claim tested support for arbitrary acquisition formats.

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。

Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs. Use when deploying or serving AI/ML models, running GPU-accelerated workloads (training, fine-tuning, inference), serving web endpoints, scheduling batch jobs, or scaling Python code to cloud containers with the Modal SDK.

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。

Inspects and automates microscopy data workflows against OMERO.server with omero-py, BlitzGateway, OMERO CLI, tables, annotations, ROIs, rendering, and documented OMERO.web APIs. Use this skill for scoped OMERO inventory, metadata export, import/export planning, or reviewed write 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。

PDF・Office文書・画像から、文字とページ内の位置情報をローカルで抽出します。スキャンの文字認識、JSON・Markdown出力、ページ画像化、一括処理に対応します。

• スキャンPDFや画像の文字を抽出したいとき
• RAG用に文書と位置情報を整えたいとき
• 論文フォルダの一括取り込み

Predicts regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene symbol, a genomic region, or a DNA/FASTA sequence and wants any of these predictions, mentions Genomic Intelligence, genomicintelligence.ai, api.genomicintelligence.ai, or mcp.genomicintelligence.ai.

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。

Retrieves ClinGen gene-disease validity assertions for a public gene or disease, and reviews source-linked public evidence and literature for one supported GRCh38 germline nuclear SNV or simple indel through Folklore Clinical Variant Interpretation MCP. Used when a scientific agent must branch deterministically on resolved, ambiguous, not-found, invalid, unsupported, or unavailable variant outcomes; chain a resolved public variant into related literature or publication details; or preserve evidence provenance without accepting patient, phenotype, family, segregation, or private case data.

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。

Store team knowledge, project conventions, and learnings from tasks. Use to remember what works and recall context before new tasks. Connects to a self-hosted Hindsight server. (user)

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。

How to use the PSL syntax tree layers (green tree, red tree, strongly-typed AST classes) correctly. Use for any PSL-related work: PSL interpreters (contract-psl), helpers inside the psl-parser package, the language server, formatters, or anything else that consumes `parse()` output from @internal/psl-parser.

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 server-side call automation workflows including IVR systems, call routing, recording, and AI-powered interactions.

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。

⚠️ DEPRECATED: This SDK has been renamed to Call Automation. For new projects, use azure-communication-callautomation instead. This skill is for maintaining legacy code 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。

Goal-integrity skill. Use for backend/API/persistence, preserve/do-not-change, tests/validation, mocks, rework, multi-part requests. Emits Goal Contracts, Deviation Notices, Phase Checks, Final Audits. Skip for Q&A or trivial edits.

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。

Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.

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。

Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.

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。

Compiled CLI covering all 52 endpoints of the Anytype local API — objects, properties, tags, search, chat, files — one binary, no MCP server needed.

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 the coding agent's explicit AAS skill selection as a validated stack and optional evidence.

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。

Decides what information belongs on a resume or CV, what to leave off and in what order, and audits an existing resume against those norms. Covers every section (contact details, photo, summary, experience, education and GPA, skills, languages, references), candidate situations (new grad, career change, gaps, layoffs, veterans, academic, visa and more) and country and industry norms. Use when the user asks "what should I put on my resume", "what should I leave off", "should I include my photo / GPA / date of birth", "how do I show a gap", "summary or objective?", "how long should my CV be", "CV for a job in Dubai / Germany", "I'm moving to another country, what should I change", "what to put on my resume as a veteran" or "audit / review my resume". Works with pasted text or the Reactive Resume MCP server. For rewriting bullets use resume-bullet-writer; for fitting a resume to one job posting use resume-tailor; for building a new resume as JSON use resume-builder.

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。

Turns resume duties into truthful impact bullets. Questions the user role by role to dig out achievements, asks for real numbers or honest ranges (never invents them), and writes concise bullets in XYZ, CAR, scope or qualitative form. Use when the user says "rewrite my bullets", "make this bullet stronger", "quantify my resume", "turn my duties into achievements", "improve my experience section", "my resume sounds boring", "I don't have any numbers", pastes resume lines for feedback, or works in a low-number job (nursing, teaching, care, trades, admin, creative). With the Reactive Resume MCP server connected, it edits experience, project, volunteer and education descriptions with apply_resume_patch after the user approves. Use resume-content-guide instead for which sections or details belong and for summaries or headlines, resume-tailor to fit one job posting, interview-prep or mock-interview for interview stories and practice, and resume-builder to build a resume from scratch.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for malware configuration recovery, staged payload boundaries, beacon parameter extraction, and IOC decoding. Use when the user asks to recover a malware config, decode C2 or beacon fields, unpack staged payloads, extract bot or campaign IDs, or tie recovered config to observed protocol behavior under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。