「estimation」の検索結果

Analyze an insurance claims processing system for lifecycle completeness, straight-through processing automation, fraud detection coverage, reserve estimation methodology, subrogation recovery workflows, and regulatory compliance with state prompt payment laws..

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。

Analyze defense program budgets and acquisition costs — earned value management (EVM/CPI/SPI), should-cost modeling, PPBE process alignment, cost estimation per GAO guidelines, Nunn-McCurdy breach risk, FYDP profiles, and learning curve analysis. Audit DoD 5000 acquisition software, program cost databases, and budget justification systems.

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。

Analyze consumer modeling systems for purchase prediction, lifetime value estimation, multi-touch attribution, brand affinity, and switching cost analysis. Triggers: 'evaluate CLV model', 'review purchase prediction', 'audit attribution model', 'assess customer lifetime value'.

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。

Analyze catastrophe modeling systems for natural disaster exposure, PML estimation, and reinsurance optimization. Use when: 'assess cat model', 'evaluate disaster exposure', 'review PML calculations', 'audit reinsurance program', 'check exposure data quality', 'analyze hurricane/earthquake risk models', 'evaluate Oasis or RMS setup'.

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 working on the SAM3 plus Sapiens2 pose estimation pipeline, batch GPU processing, or VRAM and throughput issues.

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。

Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs (including cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don't use for generic VM management or non-observability tasks.

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 working on the FIFA Skeletal Tracking Light 2026 pipeline, monocular broadcast pose estimation, or vaila_sam.py FIFA commands.

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。

Show real token usage and estimated savings for the current session. Reads directly from the Claude Code session log — no AI estimation. Triggers on /caveman-stats. Output is injected by the mode-tracker hook; the model itself does not compute the numbers.

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 when prioritizing a Salesforce backlog with the MoSCoW method (Must / Should / Could / Won't) plus an effort + value lens, deciding what fits in the next sprint or release, and using WSJF as a tie-break when MoSCoW alone produces ties. Trigger keywords: MoSCoW prioritization, must should could won't, WSJF salesforce, prioritize salesforce stories, sprint commit, backlog grooming. NOT for story writing or splitting (use admin/user-story-writing-for-salesforce). NOT for release train planning (use agents/release-train-planner). NOT for sizing/estimation method debates — this skill assumes a sizing convention is already in place.

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 scoring a list of business or solution requirements against the *actual* capabilities of a specific Salesforce org so each row can be classified Standard / Configuration / Low-Code / Custom / Unfit, given an effort tier (S/M/L/XL), a risk tag, and an AppExchange suggestion when applicable. Trigger keywords: fit gap salesforce requirements, score requirements against salesforce capabilities, salesforce capability matrix, classify requirement as standard config custom, fit-gap effort tier, AppExchange alternative for requirement. NOT for requirements elicitation (use admin/requirements-gathering-for-sf). NOT for architecture decisions on the GAP rows (use architect/solution-design-patterns and standards/decision-trees/). NOT for license or edition selection (use architect/license-optimization-strategy and architect/org-edition-and-feature-licensing). NOT for OmniStudio-specific fit-gap (use architect/omnistudio-vs-standard-decision).

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Identify, score, and prioritize Salesforce AI use cases before any implementation begins — opportunity identification, Impact-Effort matrix scoring, feasibility evaluation across Technical/Operational/Data/Risk dimensions, and ROI framing. NOT for the license checks and enablement steps once a use case is approved — use agentforce/agentforce-service-ai-setup or agentforce/agentforce-sales-ai-setup. NOT for making the data model AI-ready — use architect/ai-ready-data-architecture.

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。

Prospective failure imagination for a plan, decision, or running system. Operates in two modes — **plan mode** (a plan has not yet been committed to; imagine its catastrophic failure broadly) and **scenario mode** (a specific catastrophic scenario is posed against an existing system; investigate causes against the actual code and architecture). Spawns parallel pre-mortemers in isolation across three categories of lens: standard failure classes (technical, operational, estimation, scope, adoption, dependency, team, incentive, detection, reversibility, adversarial), 0-3 ad-hoc target-specific lenses the orchestrator names when warranted, and a first-principles lens that always runs to catch what the prescribed taxonomy misses. Synthesizes into a prioritized risk register with early-warning signals. Produces feedback only — no code, no tickets, no artifacts.

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 and implement adaptive testing systems using Item Response Theory (IRT). Use when working with computerized adaptive tests (CAT), psychometric assessment, ability estimation, question calibration, test design, or IRT models (1PL/2PL/3PL). Covers test algorithms, stopping rules, item selection strategies, and practical implementation patterns for K-12, certification, placement, and diagnostic assessments.

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Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.

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。

Read-only full Jira ticket analysis incl. media + linked issues via jira-analyst agent; produces comment-ready findings. NOT complexity scoring (mk:jira-evaluator) or estimation (mk:jira-estimator).

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。

Heuristic read-only story-point estimation for one Jira ticket via jira-estimator agent. NOT complexity analysis (mk:jira-evaluator) or full RCA (mk:jira-analyst).

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。

Evaluate Jira ticket complexity and inconsistencies via jira-evaluator agent, read-only. NOT estimation (mk:jira-estimator) or full RCA (mk:jira-analyst).

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。

Evaluate Jira ticket complexity + inconsistencies via the jira-evaluator agent. Read-only. Triggers: 'evaluate KEY', 'analyze ticket complexity for KEY', 'check ticket quality for KEY'. NOT for estimation (mk:jira-estimator); NOT for full RCA (mk:jira-analyst).

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。

Full Jira ticket context analysis via the jira-analyst agent — including media (attached images / PDFs / screenshots) and linked issues. Produces structured findings suitable for posting back as a Jira comment. Read-only. Triggers: 'analyze KEY', 'rca for KEY', 'describe KEY with media'. NOT for complexity scoring (mk:jira-evaluator); NOT for story-point estimation (mk:jira-estimator).

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。

Manage DAG execution lifecycles including start, stop, pause, resume, and cleanup. Activate on 'execution lifecycle', 'stop execution', 'abort DAG', 'graceful shutdown', 'kill process'. NOT for cost estimation, DAG building, or skill selection.

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Audit LLM token cost estimates against actual API usage. Activate on 'cost verification', 'token estimate accuracy', 'API cost audit', 'estimation variance'. NOT for pricing lookups, budget planning, or cost optimization strategies.

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Track real-time API cost accrual during LLM execution. Activate on 'cost tracking', 'token usage', 'API costs', 'budget monitoring', 'usage metrics'. NOT for cost estimation, pricing tiers, or billing systems.

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。

Strategic analyst that maps competitive landscapes, identifies white space opportunities, and provides positioning recommendations. Use when users need competitive analysis, market positioning strategy, differentiation tactics, or "how do I stand out?" guidance across any domain (portfolios, products, services). NOT for market size estimation or financial forecasting.

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。

Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.

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。