「tracking」の検索結果

UUID generation skill - Universally Unique Identifiers v4 and v7 for entity IDs. For ng-events construction site progress tracking system.

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。

@delon/chart skill - G2Plot enterprise charting components with @delon/chart. For ng-events construction site progress tracking system.

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。

@delon/acl skill - Access Control List for role-based permissions and UI element visibility. For ng-events construction site progress tracking system.

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。

@delon/util skill - Utility functions library for array, string, date, number manipulation. For ng-events construction site progress tracking system.

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 the user needs multi-source research with citation tracking, evidence persistence, and structured report generation. Triggers on "deep research", "comprehensive analysis", "research report", "compare X vs Y", "analyze trends", or "state of the art". Not for simple lookups, debugging, or questions answerable with 1-2 searches.

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。

Enhancement-overlay skill — the DECISION + WIRING layer for LM observability that the single-backend skills [[langsmith]], [[phoenix]], [[mlflow]] do NOT cover. Each of those installs one backend; none of them help you DECIDE which backend fits your stack/scale/budget, nor give you a one-line autolog that turns it on fast. Use when starting any LM project, before the first deploy, or the moment someone asks "why did it do that?" and there are no traces to answer with. The skill picks a backend by stack (LangSmith for LangChain/LangGraph; Phoenix for OSS/local OpenTelemetry; MLflow for ML-shops already on MLflow; Langfuse for self-host), wires one-line autolog, verifies traces land, and adds eval hooks — instrumenting BEFORE you need it. Cross-links the first-debug-move skill [[agentsop-prompt-history-inspect]]. Do NOT activate to re-teach a backend you already chose (defer to its own skill), or for non-LM ML experiment tracking with no LLM calls (that is plain MLflow).

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。

Web page change detection, availability tracking, and RSS feed generation. Use to monitor changes, downtime, or make a feed.

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。

FOIA and public records workflows. Use when drafting requests, tracking submissions, checking exemptions, or appealing denials.

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。

Email newsletter workflows. Use when creating newsletters, building subscriber lists, designing templates, or tracking engagement.

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。

Manages newsroom editorial workflows. Use when tracking assignments, managing deadlines, or coordinating editorial calendars.

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。

Wash sale detection under 2025 US crypto rules with 61-day window monitoring, disallowed loss tracking, and safe re-entry countdown

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。

Large wallet monitoring, accumulation and distribution detection, and smart money signal generation for Solana tokens

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。

Real-time tax liability analysis for active crypto traders with proportional cost basis, gain classification, and tax-aware trading signals

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。

Tax-loss harvesting opportunity identification, scoring, and planning with wash sale compliance and annual carryforward tracking

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。

Market sentiment extraction from social media, news, and on-chain data including mention velocity, fear and greed indices, and influencer tracking

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 and analyze scholarly literature using the OpenAlex database. This skill should be used when searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, or conducting bibliometric analysis across 240M+ scholarly works. Use for literature searches, research output analysis, citation analysis, and academic database queries.

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。

Track progress across work sessions using SESSION.md with git checkpoints and concrete next actions. Converts IMPLEMENTATION_PHASES.md into trackable session state with phase status, progress markers, and recovery points. Use when: starting projects after planning phase, resuming work after context clears, managing multi-phase implementations, or troubleshooting lost context, missing progress tracking, or unclear next steps.

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。

This skill should be used when managing the file-based todo tracking system in the todos/ directory. It provides workflows for creating todos, managing status and dependencies, conducting triage, and integrating with slash commands and code review processes.

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。

Expert guidance for GA4 privacy and compliance including GDPR, CCPA, Consent Mode v2, data deletion, and privacy settings. Use when implementing Consent Mode, ensuring GDPR compliance, handling data deletion requests, configuring consent banners, or implementing privacy-first tracking. Covers consent parameters (ad_user_data, ad_personalization), data retention, IP anonymization, and compliance 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。

Execute structured task plans with status tracking. Use when the user provides a plan file path in the format `plans/{current-date}-{task-name}-{version}.md` or explicitly asks you to execute a plan file.

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。

Tracks LLM token consumption and usage metrics for billing, monitoring, and optimization. Use this to log token usage, calculate costs, generate invoices, and understand which agents or users consume the most resources.

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。

Agile product ownership toolkit for Senior Product Owner including INVEST-compliant user story generation, sprint planning, backlog management, and velocity tracking. Use for story writing, sprint planning, stakeholder communication, and agile ceremonies.

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。

Track complex, multi-session work with dependency graphs using bd (beads) issue tracker. Use when work spans multiple sessions, has complex dependencies, or requires persistent context across compaction cycles. For simple single-session linear tasks, TodoWrite remains appropriate.

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。

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab 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。