「db」の検索結果

Turning research artifacts into actionable PM insight. Customer interviews, user research notes, support ticket reviews, sales call transcripts, survey data, in-app feedback, all synthesized into the decisions they are meant to inform. The discipline of moving from raw discovery data to clear product direction without losing signal in the synthesis or fabricating insight that was not actually there. Triggers on research synthesis, customer interview synthesis, user research analysis, discovery readout, research insights, sales call analysis, support ticket analysis, qualitative data analysis. Also triggers when a team has done research but cannot turn it into decisions, when synthesis is producing pretty decks but no roadmap movement, or when an upcoming PM decision needs to be grounded in research already conducted.

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。

Attach/install/use clawhip as a daemon-first notification gateway runtime for OpenClaw / Clawdbot

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。

Data engineering for batch and streaming pipelines with Airflow, dbt, Spark, and Kafka. Use when designing data architectures, building pipelines, adding data-quality checks, optimizing ETL/ELT, or troubleshooting pipeline failures.

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。

Audit data quality across pipelines, warehouses, and stores. Use when designing a DQ program, defining DQ dimensions, building rule-based checks, detecting schema drift, monitoring freshness SLAs, or responding to a DQ incident.

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。

Design AWS serverless architectures for startups with IaC. Use when designing serverless architecture, writing CloudFormation, optimizing AWS costs, setting up CI/CD, or migrating to AWS across Lambda, API Gateway, and DynamoDB.

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。

Structured peer review analysis and feedback 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。

Query Protein Data Bank for 3D macromolecular structure 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。

Query Human Metabolome Database for metabolite information

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。

Playtest feedback analysis and documentation

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。

Analyzes code diffs and files to identify bugs, security vulnerabilities, code smells, and architectural concerns, then produces a structured review report with prioritized, actionable feedback.

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 and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync/DynamoDB including schema modeling, enum types, relationships, authorization rules), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue, Angular, React Native, Flutter, Swift, and Android. Always use this skill for Amplify Gen2 topics — even for questions you think you know — it contains validated, version-specific patterns that prevent common mistakes. TRIGGER when: user mentions Amplify Gen2; project has amplify/ directory or amplify_outputs; code imports @aws-amplify packages; user asks about defineBackend, defineAuth, defineData, defineStorage, or npx ampx. SKIP: Amplify Gen1 (amplify CLI v6), standalone SAM/CDK without Amplify (use aws-serverless), direct Bedrock without Amplify AI Kit (use bedrock).

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。

Give an AI agent persistent, cross-session long-term memory through MindMemOS. Covers installing and authenticating the mindmemos CLI, the full command interface (add / search / get / update / delete / feedback / dreaming) with parameters and examples, guidance on which capability to use when, plus a Python SDK example. To wire memory into a specific agent host (OpenClaw, DeepSeek Harness, Codex, Claude, etc.), see references/.

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。

Set up DMP for team use in Cowork: sandbox check, Drive folders, saved routing. "set up DMP for my team in Cowork"

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。

数据库迁移助手 - Schema 对比、迁移脚本生成

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 writing agent-relay workflows that must fully validate features end-to-end before merging. Covers the 80-to-100 pattern - going beyond "code compiles" to "feature works, tested E2E locally." Includes repair-before-failure validation gates, review-depth fresh-eyes review/fix loops with test hardening, PGlite for in-memory Postgres testing, mock sandbox patterns, test-fix-rerun loops, verify gates after every edit, and the full lifecycle from implementation through passing tests to commit.

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。

Verify a BibTeX file for hallucinated or fabricated references by cross-checking every entry against CrossRef, arXiv, and DBLP. Reports each reference as verified, suspect, or not found, with field-level mismatch details (title, authors, year, DOI). Use when the user wants to check a .bib file for fake citations, validate references in a paper, or audit bibliography entries for accuracy.

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。

Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate, per-field accuracy (title/author/year/DOI), discipline breakdown, and year constraint compliance. Supports tool-augmented (ReAct + web search) mode. Use when the user asks to evaluate, benchmark, or compare models on academic reference hallucination, literature recommendation quality, or citation accuracy.

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。

Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate, per-field accuracy (title/author/year/DOI), discipline breakdown, and year constraint compliance. Supports tool-augmented (ReAct + web search) mode. Use when the user asks to evaluate, benchmark, or compare models on academic reference hallucination, literature recommendation quality, or citation accuracy.

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。

Acknowledge a tap/click with a ripple that blooms from the exact press point. Fast and low-opacity so it reads as feedback, not decoration. No ripple under prefers-reduced-motion (native :active covers it). Avoid on destructive actions and text links.

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。

Add a celebratory particle burst to a like / favorite / reaction button. A delight micro-interaction that fires on user tap only (never on load), bursts on the "like" transition (not un-like), and ships a prefers-reduced-motion fallback. Use when a small, earned moment of positive feedback will feel good — and only one such moment per screen.

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。

A Material-style ripple spreads from the point of contact. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.

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。

A bottom sheet slides up over a dimmed backdrop, then dismisses. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.

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。

A toast slides up from the bottom, holds, then fades away. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.

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。

A bottom tab bar whose active pill slides between tabs. An App-UI micro-interaction (mobile component feedback). Honors prefers-reduced-motion. Keep it short and snappy; only on controls that actually change state.

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。