「metric」の検索結果

Generate a daily standup summary from recent Claude Code sessions — completed work grouped by project (cwd), session costs from the pricing engine, tool invocations, error/compaction/APIError events, and turn velocity metrics from session metadata (turn_count, total_turn_duration_ms).

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。

Calculate a productivity score using actual Agent Monitor metrics — session completion rates, cache efficiency (cache_read vs input), compaction pressure (baseline tokens), turn velocity (turn_count / total_turn_duration_ms), tool success ratio (PreToolUse vs PostToolUse), and the workflow intelligence API's complexity and effectiveness scores.

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。

One-line summary of key Agent Monitor metrics — active sessions, total cost from the pricing engine, events today from daily_events, top tool from tool_usage, and current model from the most recent session. Use for a fast at-a-glance check without leaving the terminal.

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 one session (or a small recent set) against the rolling average using Agent Monitor data — cost, total tokens, tool count, and workflow complexity score — and report where each metric lands as a percentile of the population. Tells you whether a session was normal, cheap, or an outlier. Use when judging whether a session was typical or out of band.

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。

Detect quality and efficiency regressions over time using Agent Monitor data — rising error rate (APIError events), falling cache hit rate, growing compaction frequency, and climbing cost-per-session. Splits history into an earlier baseline window and a recent window and reports which metrics are getting worse, by how much, and where. Use when checking whether things are degrading or trending in the wrong direction.

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。

Record a dated snapshot of the vault's health numbers and compare against previous snapshots so trends are visible. Use this skill for a monthly or quarterly check, when the user asks whether the vault is improving, or asks to track its numbers over time. Do NOT use for a one-off graph analysis, which is second-brain-graph, or for structural repairs.

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。

Analyse the vault's link graph and report on its shape: orphan rate, average degree, components, hubs, bridges and clusters, with what each number means for retrieval. Use this skill when the user asks about the health or structure of their graph, wants metrics, asks which pages are most connected or most isolated, or asks whether the vault is fragmented. Do NOT use for fixing what it finds, which is second-brain-lint, or for answering a content question.

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。

Automatically invoke this skill whenever the user asks why a Fabric capacity is busy, throttled, at 90 or 100 percent, or what is consuming CUs; asks for current capacity utilization, carry forward or per-item CU usage; wants to query or repair the Microsoft Fabric Capacity Metrics app or its semantic model; or wants to start, pause or monitor a capacity from a script or status bar.

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 lighting or rendering a Godot 4.7 3D scene: pick a renderer (Forward+, Mobile, Compatibility), choose GI (SDFGI, VoxelGI, LightmapGI, reflection probes), bake lightmaps without a mouse, tune WorldEnvironment, tonemapper (AgX, ACES, Filmic), glow, fog, volumetric fog and god rays, shadows and shadow acne, quality presets for PC and phones, Compositor post effects, or when 'my scene looks flat', 'too dark indoors', 'light leaks', 'lightmap is black', 'looks different on mobile'.

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 animating 2D game art with Scenario: walk, idle or attack cycles in 4 or 8 directions, isometric sprite sheets, animated GIFs, frame-by-frame pixel art animation, VFX loops such as fire or smoke, looping a sprite seamlessly, animating an existing character image, a full animation sheet from one prompt, extracting animation frames from a generated video, or slicing a sprite sheet into engine-ready frames for Unity, Godot, or Unreal. Keywords: spritesheet, keyframes, frame grid, GIF.

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 creating game art through Scenario MCP: sprites, sprite sheets, icons, props, loot, tilesets and autotile terrain transitions, seamless tiles, isometric buildings, top-down maps, pixel art, UI buttons and panels, parallax background layers or depth planes for side-scrollers, and character or concept art; or when assets need transparent backgrounds, background removal, style-consistent variation batches, upscaling, pixel-grid cleanup, or PNG export for Unity, Godot, or Unreal.

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。

Generate 3D CGI and rendered video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants 3D rendered, CGI, Pixar-style, Unreal Engine, photorealistic 3D, computer-generated, or digitally rendered video content. Triggers on: 3D animation, CGI, rendered, Blender, Unreal Engine, octane render, ray tracing, volumetric, subsurface scattering, physically based rendering, or any 3D/CG video request. Always use even if the user just says "make it look 3D" or describes a rendered aesthetic.

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 measurement frameworks including event taxonomy, KPI hierarchy, dashboard architecture, attribution models, and analytics implementation strategy. Use this skill whenever the user wants to plan analytics, design dashboards, build event taxonomies, define KPIs, set up tracking, or audit existing measurement. Triggers on analytics strategy, measurement plan, event taxonomy, tracking plan, KPI framework, dashboard design, north star metric, attribution model, conversion tracking, GA4 setup, Mixpanel setup, analytics audit. Also triggers when the user has data but no clear way to use it, or wants to make decisions but doesn't know what to track.

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 discipline for designing experiments (A/B tests, multivariate, holdouts) so the results actually answer the question you asked. Hypothesis writing, sample size, duration, segment analysis, running discipline, matching a result to a pre-committed decision rule, and the common failure modes that produce confidently wrong shipping decisions. Use this skill whenever the user is planning a test that has not run yet: framing a hypothesis, sizing the sample, setting duration, choosing guardrails, or deciding whether something is worth testing at all. Triggers on design an experiment, experiment plan, A/B test, split test, multivariate test, holdout, experiment hypothesis, sample size, minimum detectable effect, MDE, test duration, guardrail metric, no peeking, pre-committed decision rule, is this worth testing. Use `experimentation-analytics` instead when the test has already run and the question is how to read the result panel.

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。

The operational playbook for launching a feature well. Positioning, internal alignment, customer comms, sales enablement, support readiness, rollout strategy, monitoring with pre-defined rollback triggers, post-launch measurement against spec hypotheses, and the discipline that distinguishes shipping from releasing from actually launching. Triggers on launch plan, feature launch, launch checklist, ship vs release, rollout strategy, gradual rollout, sales enablement, support readiness, launch announcement, post-launch measurement, launch failure, declared victory too early. Also triggers when planning a launch (any size, any segment), auditing an existing launch process, fixing the we shipped it but the metric did not move problem, or building a launch checklist for the team.

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。

Iterative measurement-driven improvement loop. Measure, profile, mutate, re-measure, commit. Works for performance, bundle size, complexity, test coverage — anything quantifiable. Use when the user wants to systematically improve a metric through repeated cycles of profiling and targeted changes.

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。

Kubernetes diagnostics for metrics, health checks, resource comparisons, and cluster analysis. Use when analyzing cluster health, comparing environments, or gathering diagnostic 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。

Improve an open-source GitHub skill and open a friendly suggestion PR upstream: fork, run skill-creator's retrofit, attach asm eval before/after metrics. Don't use for local-only skills, authoring from scratch, bulk repos, or registry publish.

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 comprehensive stock deep analysis tool that combines real-time quotes, fundamental metrics, technical indicators, and growth analysis into a single professional report. Supports A-share, US stocks, HK stocks. Generates detailed investment recommendations with risk assessment and actionable trading strategies.

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。

Reconstruct a readable parametric ForgeCAD model from an existing CAD or mesh file such as STL, OBJ, 3MF, STEP, or STP.

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。

Reconstruct a real parametric ForgeCAD object from reference images by using images as evidence, not as a one-view facade.

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。

Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics. Per-person breakdowns with praise and growth areas. Modes: default 7d, 24h, 14d, 30d, compare, global cross-project. Shipping streaks and tweetable summary.

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 DeFi protocol metrics including TVL, yields, and liquidations

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 codebase health metrics including complexity and dependencies

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。