「output」の検索結果

Guide for optimizing MSBuild incremental builds. USE FOR: builds slower than expected on subsequent runs, 'nothing changed but it rebuilds anyway', diagnosing why targets re-execute unnecessarily, fixing broken no-op builds. Covers 8 common causes: missing Inputs/Outputs on custom targets, volatile properties in output paths (timestamps/GUIDs), file writes outside tracked Outputs, missing FileWrites registration, glob changes, Visual Studio Fast Up-to-Date Check (FUTDC) issues. Key diagnostic: look for 'Building target completely' vs 'Skipping target' in binlog. DO NOT USE FOR: first-time build slowness (use build-perf-baseline), parallelism issues (use build-parallelism), evaluation-phase slowness (use eval-performance), non-MSBuild build 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。

Choosing an MSBuild CopyToOutputDirectory / CopyToPublishDirectory mode: Never, PreserveNewest, Always, and IfDifferent (MSBuild 17.13+), plus $(SkipUnchangedFilesOnCopyAlways). USE FOR: removing the per-build Always copy perf hit; resetting output files mutated between builds. DO NOT USE FOR: general incremental-build diagnosis (use incremental-build); non-MSBuild build 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。

Verify that every quantitative claim in the paper is traceable to an analysis output file, and that no important output was omitted. Make sure to use this skill whenever the user wants to check that the paper and analysis are consistent before submission. Triggers include: "run the quality gate", "check the paper matches the analysis", "verify consistency", "does the paper match my results", "check my numbers", "are my tables right", "quality check before submission", "verify my claims", "make sure everything is consistent", "double-check the paper against my output files", or any pre-submission integrity check between paper text and computed results.

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 and process GLM output files. Use when you need to extract temperature data from NetCDF output, convert depth coordinates, or calculate RMSE against observations.

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。

Creates sashimi-style plots showing RNA-seq read coverage and splice junction counts using ggsashimi (general-purpose, condition-grouped overlays), rmats2sashimiplot (rMATS-output-aware), MAJIQ-VOILA (LSV posteriors interactive HTML), leafviz (leafcutter clusters Shiny), Jutils (tool-agnostic heatmaps and sashimi for rMATS/leafcutter/MntJULiP/MAJIQ output), or pyGenomeTracks (multi-track publication figures). Tool choice depends on the upstream differential-splicing tool's output format and the publication vs interactive use case. Use when visualizing specific splicing events, validating differential splicing calls, or producing publication-quality figures.

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。

Port MATLAB Data Acquisition Toolbox code from the discouraged (legacy) session-based interface (daq.createSession, addAnalogInputChannel, startBackground, DataAvailable listeners, queueOutputData, wait) to the recommended DataAcquisition interface (daq("ni"), addinput, start, ScansAvailableFcn, write, preload). Use when migrating legacy DAQ scripts, converting session-API calls, working with DataAcquisition objects, writing multi-feature DAQ scripts that combine triggers, callbacks, continuous acquisition, or analog output. Also use when a user says their DAQ script "used to work" or "errors on R20XX", since modernizing legacy session-API code is a frequent fix for those failures. Trigger keywords: daq, DAQ, NI, session interface, addtrigger, addclock, ScansAvailableFcn, ScansRequiredFcn, daq.createSession, addAnalogInputChannel, startBackground, queueOutputData, DataAvailable, evt.Data, evt.TimeStamps, wait(d), preload, discouraged, legacy, modernize, R2020a.

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 structured protocol for auditing AI-generated text against Ennis's six CT standards. Use when students need to critically evaluate AI output in any subject.

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。

Reduce mix output noise (5-15% token savings) by installing rtk filters that compress mix test/credo/dialyzer/compile output before it reaches Claude. Use when long mix output floods 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。

Reduce mix output noise (5-15% token savings) by installing rtk filters that compress mix test/credo/dialyzer/compile output before it reaches Claude. Use when long mix output floods 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。

Synthesize the shortlist into a discussion-ready research idea brainstorm memo, writing `output/REPORT.md`, `output/APPENDIX.md`, and `output/REPORT.json`.

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。

Choosing an MSBuild CopyToOutputDirectory / CopyToPublishDirectory mode: Never, PreserveNewest, Always, and IfDifferent (MSBuild 17.13+), plus $(SkipUnchangedFilesOnCopyAlways). USE FOR: removing the per-build Always copy perf hit; resetting output files mutated between builds. DO NOT USE FOR: general incremental-build diagnosis (use incremental-build); non-MSBuild build 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。

Guide for optimizing MSBuild incremental builds. USE FOR: builds slower than expected on subsequent runs, 'nothing changed but it rebuilds anyway', diagnosing why targets re-execute unnecessarily, fixing broken no-op builds. Covers 8 common causes: missing Inputs/Outputs on custom targets, volatile properties in output paths (timestamps/GUIDs), file writes outside tracked Outputs, missing FileWrites registration, glob changes, Visual Studio Fast Up-to-Date Check (FUTDC) issues. Key diagnostic: look for 'Building target completely' vs 'Skipping target' in binlog. DO NOT USE FOR: first-time build slowness (use build-perf-baseline), parallelism issues (use build-parallelism), evaluation-phase slowness (use eval-performance), non-MSBuild build 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。

根据 model_route.json、数据计划和清洗数据，为数学建模论文生成结果证据契约和 q1/q2/q3 建模代码脚手架。Invoke when 需要把模型输出、评价指标、结构化结论、论文表格和当前赛题专用建模代码沉淀到 paper_output/results/、paper_output/tables/ 和 paper_output/code/modeling/，供 QA 与正文生成读取。

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。

Shapes turns action-first: action leads, steps numbered, state restated. Use for ADHD-friendly output. Do not use to trim tokens; use response-compression.

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 test cases using metamorphic testing by applying transformations based on metamorphic properties. Use when you need to expand test suites, test programs without oracles, validate mathematical or algorithmic properties, or detect subtle bugs through input-output relationships. The skill takes a program, original test cases, and metamorphic properties as input, generates new test cases by applying transformations, executes tests, verifies outputs satisfy properties, reports violations and anomalies, and outputs an expanded test suite with property coverage summary. Supports multiple programming languages and property types.

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。

Style terminal output with Chalk. Use when adding colors to CLI output, formatting log messages, building styled terminal UIs, or creating developer tools with colored output.

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 structured protocol for auditing AI-generated text against Ennis's six CT standards. Use when students need to critically evaluate AI output in any subject.

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。

Generates render and output configuration for Remotion videos. Focuses ONLY on output settings, codec, format, quality, resolution. Input is target platform/quality requirements. Output is RENDER_CONFIG.md with Remotion render settings.

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 imp outputs differ between two paths that should agree - chunk sizes, prefill vs decode, prefix-cache resend, two engines (imp vs llama.cpp vs HF), two builds or kernels - "output changes with chunk size", "first token differs", "logprobs moved", "which layer diverges", "who is right, imp or llama.cpp", "near-tie". Do NOT use for repetition loops or garbage output (check-degeneration), a new arch that loads wrong (add-model-arch), or perf (benchmark-cuda).

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。

Diagnoses and fixes Claude behavioral issues in system prompts and Projects using tested countermeasure templates. Use when "Claude is too verbose," "keeps hedging," "agrees with everything," "claims it did something it didn't," "won't use a tool," "fix Claude's output," "tune Claude's behavior," "Claude ignores my preferences," "adds unsolicited disclaimers," "uses too many lists." Covers ten tendencies: agreeableness (output-content + persistent-preference), hedging, verbosity, list overuse, fabricated precision, over-exploration, tool miscalibration (over- and under-triggering), LaTeX defaulting, editorial drift, self-referential fabrication. Also use when auditing a system prompt for behavioral calibration or recalibrating a pre-4.7 prompt, and when users describe recurring output problems without naming a tendency. Do NOT use for scoring a prompt's overall quality — use rootnode-prompt-validation if available.

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。

Detects seven structural anti-patterns in Claude Projects that cause unpredictable output, ignored instructions, and degraded quality. Diagnoses Monolith, Orphan File, Echo Chamber, Phantom Conversation, Kitchen Sink, Misaligned Hierarchy, and Blurred Layers. Use when user says "what's wrong with my project," "Claude ignores my instructions," "diagnose my project," "why is output inconsistent," "review my project setup." Also trigger on symptom-phrased: "Claude doesn't follow my rules," "my instructions keep getting overridden," "my Project isn't behaving as designed." Use alongside rootnode-project-audit if available for deeper structural analysis. Activate whenever the user describes symptoms of unreliable, inconsistent, or degraded Claude Project output, even if they do not name a specific pattern. Do NOT use when the user's primary request is Memory-layer rebalancing (use rootnode-memory-optimization if available) or scoring a single prompt (use rootnode-prompt-validation if available).

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。

Guides selection of identity, reasoning, and output approaches for Claude prompts based on task characteristics. Trigger on: "help me choose an approach," "which approach fits this task," "recommend a prompt pattern," "compare reasoning methods," "map this task to the right approach," "what combination of approaches," "which identity fits," "which reasoning method." Also trigger on symptom-phrased: "my prompt feels generic," "I don't know which approach to use," "my output lacks domain depth." Covers decision-tree logic across 8 identity approaches, 18 reasoning variants, and 10 output formats. After selection, use the relevant catalog skill if available to retrieve full templates. Activate whenever approach-selection across multiple categories is the primary decision. Do NOT use when the user already names a specific approach to retrieve (use the relevant catalog skill directly if available) or for evaluating existing prompts (use rootnode-prompt-validation if available).

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。

Fix stale Haskell analyzer binaries silently being used by the orchestrator even after a successful rebuild. Use when: (1) modified `packages/js-analyzer/` or other Haskell analyzer source, ran `scripts/build-native.sh ... cabal install`, but a subsequent `grafema analyze` shows old behavior (missing new edges, no new node types, etc.), (2) `~/.cabal/bin/grafema-analyzer` has fresh timestamp but `grafema analyze` produces output as if the change didn't happen, (3) a test verifying new analyzer output passes locally in unit tests but fails in end-to-end runs that go through the orchestrator. Root cause: the Rust orchestrator's `resolve_binary` checks `~/.grafema/bin/<name>` BEFORE `~/.cabal/bin/<name>`, so any stale copy that was once installed there (possibly months ago) shadows the fresh `cabal install` output.

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。

Build AI output validation systems with guardrails. TRIGGERS - Use when user needs help with ai-output-validator related 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。