「weight」の検索結果

Consolidate the five tdmcp surveyor reports into one prioritized FEATURE_BACKLOG.md — dedupe cross-surface overlaps, reconcile every candidate against the roadmap (NEW vs planned vs extension), rank by a selectable impact×effort weighting profile into P0/P1/P2 (high-confidence first), and emit per-surface tables + a recommended-next shortlist that hands straight to the build pipeline. Use when a td-synthesizer agent is consolidating surveys during the feature-discovery harness.

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 says 'analyze my wordpress site', 'what is running on my site', 'site dna', or 'what plugins are on my site'. Detects every page builder, audits active versus dead-weight plugins, maps content structure, finds orphaned shortcodes, and checks performance and security posture.

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 a rifle-scope reticle from a plain-language description and emit it as a BallisticCalculator `.reticle` file (BXml) plus a rendered SVG preview. Covers the complete `.reticle` element/attribute specification, reticle design principles (mrad vs MOA subtension, FFP/SFP, stroke-weight hierarchy, hash-mark ladders, christmas-tree wind holds, clutter budget, BDC anchors) and worked, verified patterns for duplex, mil-dot, hash-ladder, christmas-tree, chevron, circle-dot, dense-grid and rangefinding-stadia reticles. Also covers reproducing an existing commercial reticle from its manufacturer's technical data sheet. Use this skill whenever the user wants to create, modify, review or render a scope reticle, crosshair, mil-dot / MOA grid, holdover ladder, christmas tree, BDC ladder or rangefinding stadia — including any mention of a `.reticle` file, `ReticleDefinition`, `ReticleDrawController`, `SvgCanvasFactory`, or "draw me a reticle", and including requests to clone or model a named commercial reticle (Horus H58/H59, TReMoR, Mil-C, MOAR, Tremor3, EBR, and the like). Trigger it even when the user only says something like "make a crosshair with 0.2 mil hashes out to 5 mils" or "turn this reticle picture into a file", and trigger it before hand-writing reticle XML or hand-rolling reticle geometry, because the file format silently ignores misspelled attributes and mis-cased booleans.

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 whenever writing, reviewing, or debugging .NET/C# code that uses the BallisticCalculator NuGet package (namespace BallisticCalculator) or its Gehtsoft.Measurements unit types — even when the user doesn't name the package explicitly but is clearly doing external/interior ballistics in .NET (bullet drop, velocity, energy, windage, spin drift, time of flight, zeroing a scope) for rifles, air rifles, bows, or artillery. Covers the full public API (Ammunition, Rifle, Atmosphere, Wind, ShotParameters, TrajectoryCalculator, TrajectoryPoint); standard, custom, .drg, and multi-BC drag tables; saving/loading data and building your own file format around it (BXml and System.Text.Json serialization); and building or rendering scope reticles (e.g. to SVG). Also use it for this library's Gehtsoft.Measurements Measurement<T> unit types (DistanceUnit, VelocityUnit, AngularUnit, WeightUnit, PressureUnit, …). Skip for: generic physics or projectile-motion exercises, a different ballistics library (e.g. GNU/JBM), game-engine or Unity projectile motion, plain unit conversions, and non-code ballistics questions (load-data or forensics advice). Self-contained: no access to the library source or binaries is required — prefer this over scanning the package to rediscover the API. Describes 1.1.13+, including the named ZeroRangeCantBeReachedException / TrajectoryCannotBeCalculatedException 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。

Builds pricing models incorporating J-curve positioning with blind pool risk, early-vintage assessment, and age-weighted adjustments. Use when pricing early-vintage funds, analyzing J-curve risk, or adjusting for fund maturity.

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。

Automated brownfield codebase analysis with weighted keyword scoring, three-stream analysis, and design pattern recognition. Detects project type, frameworks, dependencies, architecture patterns, and generates comprehensive project profile.

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。

LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations

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。

Clarify priority and emphasis by fixing unclear primary actions, competing visual weight, loud section titles, and weak label/value treatment. Use when the user mentions hierarchy, prioritization, too much competition, grayscale confusion, loud headings, or unclear primary actions.

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 UI typography by fixing font choices, type scale, hierarchy, weight, and readability so text feels intentional. Use when the user mentions fonts, typography, type scale, readability, text hierarchy, or sizing that feels off.

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 probability-weighted alternative options that challenge default thinking. Forces unconventional alternatives and exposes hidden assumptions behind the "obvious" choice. For decision-point analysis, NOT full design exploration. Triggers on "대안", "alternatives", "옵션 뽑아", "options", "어떤 방법이", "아이디어", "다른 방법", "선택지".

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。

Route a 50-minute live iOS launch sprint across the lightweight requirements, Claude Design handoff, SwiftUI implementation, landing page, ASO, Simulator screenshot, promo-video, and privacy-scan skills bundled in this plugin. Use as the main entry point when the whole talk workflow should be planned or executed.

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。

Establish and maintain longitudinal baselines of CLI binary contents across versions. Covers marker selection by category (API / identity / config / telemetry / flag / function), weighted scoring, threshold-based system-presence detection, and per-version baseline records. Use when tracking a feature's lifecycle across releases, when probing for dark-launched or removed capabilities, or when verifying that a scanning tool itself still catches known-good markers on old binaries.

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。

Evolve SKILL.md files from agent execution traces using a three-stage pipeline: trajectory collection from observed runs, parallel multi-agent patch proposal for error and success analysis, and conflict-free consolidation of overlapping edits via prevalence-weighting. Based on the Trace2Skill methodology.

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。

Extract maximum value from existing code — performance optimization, API surface refinement, and dead weight elimination. The art of turning base code into gold through systematic identification and amplification of value-bearing patterns. Use when optimizing a working but sluggish codebase, refining an API surface that has accumulated cruft, reducing bundle size or memory footprint, or preparing code for open-source release — when code works correctly but doesn't shine and needs polish rather than a full rewrite.

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。

AI dynamic reasoning balance — maintaining grounded reasoning under cognitive pressure, smooth chain-of-thought coordination, and weight-shifting cognitive load across subsystems. Use at the beginning of a complex task requiring multiple coordinated reasoning threads, after a sudden context shift or tool failure, when chain-of-thought feels jerky, or when preparing for sustained focused work that requires all subsystems in alignment.

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。

Cofold protein-ligand, protein-protein, and nucleic-acid complexes with Boltz-2, and predict binding affinity with its trained affinity head. Use this skill to build Boltz input YAML, run structure prediction with MSAs, pocket constraints, templates, and modified residues, screen compound libraries by cofolding, and interpret confidence scores (pLDDT, pTM, ipTM, PDE) and affinity output (binder probability and log10 IC50). Also trigger on Boltz, Boltz-1, Boltz-2, cofolding, boltz predict, affinity_pred_value, affinity_probability_binary, ipTM, or open-weights AlphaFold3 alternatives.

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。

Step-by-step tutorial for adding a new lightweight SYCL JIT kernel for Intel XPU to sgl-kernel-xpu's python/sgl_kernel/jit module (SYCL source + Python wrapper + tests + benchmark)

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 and fix AI-generated writing patterns (slop). Comprehensive detection with 50+ patterns across 3 severity tiers, structure weighted above lexical tells, scoring system, and editor mode that directly fixes problems. Use when scanning any content for AI tells, auditing drafts before publishing, checking if writing "sounds like AI", humanizing AI-generated text, or verifying content authenticity. Trigger on "check for slop", "does this sound like AI", "humanize this", "AI audit", "slop check", "clean up AI writing", or any request to detect/remove artificial-sounding patterns. Also use proactively before publishing any AI-assisted content.

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。

Coordinate the custom Elementor Widget site workflow for kickoff, lightweight company intake, conditional reference research, new-versus-existing site style routing, uncertain next steps, project resumption, or continuous work across content, Design Systems, UI, HTML, and Widget implementation. Do not use for release, old-Widget troubleshooting, theme development, or remote WordPress management.

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。

Head-to-Head Stock Comparison — compares two stocks across valuation, growth, profitability, financial health, technical setup, sentiment, and risk with category winners and a weighted overall score. Triggered by "trade compare <TICKER1> <TICKER2>".

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。

Portfolio Analyzer — sector allocation analysis vs SPY benchmark, geographic exposure, correlation matrix, concentration risk (HHI), beta-weighted portfolio delta, dividend/income analysis, and prioritized rebalancing recommendations. Triggered by "trade portfolio" or "analyze my portfolio".

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。

Knowledge skill that applies behavioral psychology and persuasion principles to any marketing asset. Covers Cialdini's 6 principles, cognitive biases, and ethical persuasion frameworks. This skill is invoked BY other skills to enhance their output. Use it whenever copy needs more psychological weight, when a landing page feels flat, when email sequences lack urgency, or when any marketing asset needs to be more persuasive. Also use when someone says 'make this more convincing', 'add urgency', 'psychological triggers', 'persuasion framework', 'behavioral psychology', 'conversion optimization', 'nudge', 'influence tactics', or 'why isn't this converting'. Make sure to use this whenever ANY marketing copy needs to be more persuasive, even if the user just says 'this feels weak' or 'how do I get more signups', psychology principles likely apply.

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。

Lightweight refactor: audit → plan → approve → implement in a single Opus context, no sub-agent fan-out. Behavior preservation is the goal — verifies tests still pass, optionally commits, and offers a separate /code-review pass at the end. Use by default; reach for /refactor only when the cleanup needs parallel fan-out or exceeds one context.

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。

Lightweight refactor: audit → plan → approve → implement in a single Opus context, no sub-agent fan-out. Behavior preservation is the goal — verifies tests still pass, optionally commits, and offers a separate /code-review pass at the end. Use by default; reach for /claude-setup:refactor only when the cleanup needs parallel fan-out or exceeds one context.

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。