「reduce」の検索結果

Use when a task needs the judgment of an Energy Engineer working on building and industrial energy efficiency — running an ASHRAE Level 1/2/3 energy audit, calculating envelope heat loss/gain with the degree-day method, comparing HVAC equipment on SEER/EER/IEER/COP rather than nameplate alone, designing an IPMVP measurement and verification (M&V) plan, or ranking energy conservation measures (ECMs) by savings-to-investment ratio for a capital plan. Distinct from a wind-energy-engineer or solar/PV engineer (own generation-asset design and yield) and from an electrical-engineer (owns utility-scale power delivery and protection) — this role owns the demand side: how much energy a building or process actually needs, and which retrofit reduces that number with numbers that hold up after the fact.

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Use when a task needs the judgment of an Automotive Engineering Technician — setting up and instrumenting test equipment (strain-gauge bridges, thermocouples, load/torque sensors) to an engineer's written test plan, selecting DAQ sample rate and an SAE J211 CFC filter class for a vehicle test channel, verifying instrument calibration (torque wrench, thermocouple, load cell, shunt-cal check on a strain bridge) against a traceable standard before a test run, reducing dyno or road-load test data (SAE J1349 power correction, rainflow-counted durability damage fraction) into engineering units, and documenting test results against the engineer's target with stated margin. Distinct from an automotive engineer (owns the system-level design decisions — structure, powertrain sizing, suspension geometry, NVH) — this role installs the sensors, configures the DAQ, executes the instrumented test, and reduces the data under a design and test plan the engineer specified.

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Analyze cybersecurity threat intelligence, triage security alerts, classify IOCs, map attacks to MITRE ATT&CK kill chain, reduce false positives, and attribute threat actors. Covers SIEM tuning, threat feed quality, detection coverage gaps, Diamond Model analysis, and strategic threat assessments for SOC and incident response teams.

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Audits and implements mandatory image resizing and compression for all uploaded user images to reduce storage costs while preserving visual quality.

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Analyze frontend bundle size, detect heavy dependencies, find duplicates, evaluate tree-shaking, recommend code splitting, and generate size budget configs. Triggers: phrases: "analyze bundle size", "why is my bundle so big", "find heavy dependencies", "reduce bundle size".

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Run product discovery to identify what to build. Use when the user says "product discovery", "how do I know what to build", "validate this idea", "talk to customers", "are we building the right thing", "discovery process", or wants to reduce the risk of building something users don't want - even if they don't say "discovery".

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Design product experiments to test hypotheses. Use when the user says "run an experiment", "A/B test this", "build-measure-learn", "validate this assumption", "test this hypothesis", "we don't know if this will work", "minimum viable test", "lean experiment", or wants to reduce risk before fully building a feature - even if they don't explicitly say "experiment".

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Design retention and engagement features using the Hook Model. Use when the user says "improve retention", "reduce churn", "make it habit-forming", "engagement design", "hook model", "trigger action reward", "users aren't coming back", "increase DAU/MAU", or wants to design features that bring users back repeatedly - even if they don't explicitly say "Hook Model".

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Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.

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Generates valid Cloud Monitoring ListTimeSeries requests and aggregation specifications from metric descriptors and resource parameters. Use when asked to create, generate, format, or build ListTimeSeries requests, JSON payloads, filter expressions, or aligner/reducer aggregations for Cloud Monitoring metrics and charts. Don't use for metric discovery or metric selection.

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Use this skill when designing the UX and content strategy for a Salesforce-powered self-service portal or help center — pre-deflection article surfacing, Help Center search UX, friction-calibrated case submission forms, community peer support layers, and deflection measurement. Trigger keywords: design self-service portal, case deflection strategy, help center UX design, reduce support volume with self-service, knowledge base search experience. NOT for picking which contact reasons to deflect and through which channel — use architect/case-deflection-strategy. NOT for building the Experience Cloud site itself — use admin/experience-cloud-site-setup. More trigger keywords: article visibility matrix IsVisibleInCsp IsVisibleInPkb, which articles show in the customer portal, case visibility for portal users, CaseComment IsPublished customer visible comment, self-registration profile and account for a portal, Help Center template does not support login, deflection metrics SOQL KnowledgeArticleViewStat, self-service journey map, moderation policy for a support community.

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Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

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Reduces JS/TS bundle size via unused deps, tree-shaking, code splitting with keep/discard

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One page, hands-on manual tier — drive a live page through the web accessibility (a11y) checks a rule engine can't decide: keyboard operation and focus order, screen-reader names, roles and states from the accessibility tree, reflow and zoom, reduced motion, form errors, and target size. Grades each finding by evidence basis (verified / confirm-with-a-human / human-required) and severity, and closes every criterion in a ledger: verified, flagged, not exercised, or N/A. Locates and assesses; does not fix (use `accessibility-fix`). Use it for keyboard testing, focus-order checks, screen-reader or a11y-tree review, reflow and zoom at 200%, or 'is this operable, not just lint-clean'. The automated tier is `accessibility-scan`; `accessibility-audit` runs both across a sampled site.

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Production-ready CSS transition snippets for web apps. Use when adding or reviewing UI motion for badges, dropdowns, modals, panel/page reveals, card resizes, number pop-ins, text/icon swaps, success checks, avatar-group hovers, and validation shakes. Supports namespaced commands: transitions reveal (list catalog), transitions review (audit project fit), and transitions apply (install the best-fit snippet with hooks and reduced-motion handling).

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Analyze, benchmark, and reduce your customer acquisition cost across every channel.

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Routes LLM requests to a local model first (Ollama, LM Studio, llamafile), validates the response quality, and escalates to cloud only when the local result fails. Tracks local vs escalated vs cloud outcomes in a persistent dashboard. Use when: (1) user asks to run a task with a local model first, (2) user wants to reduce cloud API costs or keep requests private, (3) user wants post-outcome quality validation before committing to a local result, (4) user asks to see token savings or the routing dashboard, (5) any request where local-vs-cloud routing should be decided automatically with a quality gate. Supports Ollama, LM Studio, and llamafile as local providers.

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Load a skill profile to switch active plugin set. Use when user wants to focus on a specific workflow (web-app/data-eng/harness-dev/minimal) and reduce skill enumeration block size per

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Hypertree decomposition approach to planning problems for reduced computational complexity

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Tracks cumulative LLM costs across DAG execution and makes real-time decisions to stay within budget. Downgrades models, skips optional nodes, or stops early when cost exceeds thresholds. Use when managing execution budgets, analyzing cost breakdowns, or optimizing model routing for cost. Activate on "cost budget", "too expensive", "reduce cost", "cost optimization", "model downgrade", "budget exceeded". NOT for LLM model selection logic (use llm-router), pricing comparisons across providers, or billing/invoicing.

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Design and implement systematic checklists that reduce errors by 30-50% in complex, high-stakes domains (medicine, aviation, construction, finance). NOT for simple tasks or when comprehensive instruction is needed.

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Aligns sample metadata with count matrices and constructs design matrices for downstream DE, handling the alphabetical-reference-level trap (relevel BEFORE DESeq), LRT reduced-model rules, the interaction-term resultsNames trap, continuous-covariate scaling and splines, repeated measures via duplicateCorrelation or dream, high-cardinality categorical pseudo-singular designs, sample swap detection via XIST/RPS4Y1 expression and somalier/NGSCheckMate genotypes, SABV (sex-as-biological-variable) mandate, Simpson's-paradox collapsing of technical replicates, and the `~ 0 + group` parameterization for clean contrasts. Use when building a design matrix, troubleshooting reversed fold-change direction, encoding paired or repeated-measures designs, detecting sample swaps, deciding sex-as-covariate, or aggregating technical replicates.

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Analyzes time-series and longitudinal RNA-seq for differential expression and trajectory structure. Covers DESeq2 LRT with reduced models, time as factor vs continuous vs natural splines, maSigPro (Nueda 2014 for RNA-seq), ImpulseDE2 with explicit impulse-model failure modes, DREAM for repeated measures via linear mixed models, pseudoreplication avoidance, conditional vs marginal modeling, and trajectory clustering with DPGP, Mfuzz (with Schwämmle 2010 fuzzifier estimation), and splines+k-means. Use when modeling time-course or longitudinal expression, choosing factor vs spline, handling repeated measures from the same subject, avoiding pseudoreplication, clustering temporal trajectories, or selecting between dedicated time-course tools and pairwise+LRT.

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Recommends CGM over SMBG for type 1 diabetes patients on multiple daily injections to reduce hypoglycemia risk. Triggered by clinician questions such as "Should I use CGM or SMBG for this T1D patient on MDI?" or "Is CGM preferred for glucose monitoring in this patient?"

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。