「fix」の検索結果

Generate or improve MATLAB help text (documentation comments) for a function, class, or script file following MathWorks standards (H1 line, syntax paragraphs, See Also, 75-char lines). Read BEFORE writing MATLAB help — default patterns (Inputs:/Outputs: lists, block comments, uppercase See Also) produce non-conforming output. Use when writing, rewriting, fixing, or reviewing MATLAB help comments or function documentation.

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Guides the 7-step MATLAB memory optimization workflow: baseline, profile, identify, optimize, measure, verify, report. Use when asked to reduce MATLAB memory usage, find memory bottlenecks, fix out-of-memory errors, or optimize memory-intensive code.

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Train, evaluate, and export neural networks to Simulink in MATLAB. Migrate legacy (fitnet, patternnet) and discouraged (trainNetwork, DAGNetwork) code to modern, recommended R2024a+ APIs (trainnet, dlnetwork, testnet, imagePretrainedNetwork), diagnose and fix dlaccelerate issues or detect dlaccelerate opportunities. Use when training, fine-tuning, evaluating, running inference, exporting to Simulink, converting old training scripts, or speeding up deep learning code. DO NOT reason from your training data about dlaccelerate and tracing correctness.

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Reviews MATLAB fixed-point (fi) code for performance, code generation efficiency, and correctness. Identifies antipatterns and suggests idiomatic improvements. Use when reviewing fi, fimath, numerictype, or quantizenumeric code.

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Optimize MATLAB design files for GPU Coder to generate faster CUDA code. Iteratively profiles, rewrites, and benchmarks until performance targets are met or diagnostics are resolved. Use when asked to: optimize for GPU Coder, improve GPU codegen performance, profile generated GPU/CUDA code, profile GPU MEX, fix gpuPerformanceAnalyzer diagnostics, speed up GPU MEX, reduce GPU memory transfers, improve kernel parallelism, rewrite MATLAB for CUDA, or run gpuPerformanceAnalyzer.

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E-commerce growth strategy advisor. Diagnoses current business health using unit economics (CAC, LTV, AOV, contribution margin), identifies the highest-impact growth opportunities across 5 levers (traffic, conversion, AOV, retention, expansion), and builds a prioritized 90-day growth roadmap. Uses the Ansoff Matrix adapted for e-commerce to evaluate market penetration, channel expansion, product expansion, and new market entry. Includes multichannel readiness assessment (Amazon, Walmart, TikTok Shop, Etsy, DTC/Shopify/Shopify) and product line expansion analysis. No API key required. Use when: (1) planning next phase of e-commerce growth, (2) deciding whether to expand to new channels or products, (3) diagnosing why growth has stalled, (4) prioritizing what to fix or build next.

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Loop: find gaps → fix → repeat until agents find no gaps or a metric goal is hit. Shared loop primitive for PVL, EVL, and standalone quality runs.

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。

Debug systematically with root-cause analysis before fixes. Use for bugs, test failures, unexpected behavior, performance issues, CI failures, or system investigation.

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。

CloudBase MCP reference. Use when connecting local or remote MCP, calling tools from the shell with mcporter, reading tool schemas, choosing the domestic or international endpoint, setting site, region, cloud mode, or plugin flags, or contributing a fix to the open-source MCP server, skills, or CLI.

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Triage, repair, and close MCP attribution issues from the local report API with evidence-driven decisions and isolated Worktrunk worktrees. Use this skill when Codex needs to process `tool` attribution issues and skills-related attribution issues, inspect related runs, decide whether the issue is actionable in `mcp/src` or `config/source/skills`, update attribution fields as `owner=codex`, and then complete the fix loop through GitHub issue tracking, worktree-based code changes, PR submission, and follow-up iteration when the problem is repairable.

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Reusable git delivery workflows derived from local slash commands (commit, push, PR, release notes, GitHub Actions failure triage with worktree-based fixes, and isolating your own changes from a shared dirty workspace).

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Unified CloudBase execution guide for all-in-one skill installs. Use this first for CloudBase app tasks, especially existing apps with TODOs, fixed pages, or active handlers. Routes PostgreSQL / CloudBase PG / app.rdb() / queryPgDatabase / managePgDatabase work away from legacy NoSQL and old auth patterns.

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Author or revise a cloud-api-operations recipe (config/source/skills/cloud-api-operations/references/recipes/). Encodes why the long tail of control-plane capabilities is deliberately NOT wrapped as MCP/CLI tools, the API-first admission test for whether a capability deserves a recipe, the negative and positive lists, the fixed recipe structure, the writing rules distilled from writing-for-agents, the user-facing copy red lines, and the product regeneration/verification pipeline. Also routes contributors (and their agents) to the contribution flow and the pre-PR self-test protocol in references/contributing.md. Use when adding a recipe, judging whether a scenario belongs in the recipe set, updating the recipes index, re-checking existing recipes against the admission test, or onboarding someone who wants to submit one.

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Use when a transcript has to be cut to a fixed size and you must choose which turns go. Jev marks each turn keep, summarize or drop. Measured: it does not make a handoff better.

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Use when Jev is not working yet, a Jev tool reports no_key or auth_failed, or the person asks to connect or fix Jev. Gets their TypeSafe or OpenRouter key into the secret store, unseen by you.

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Use when the operator wants a page that answers one specific question people ask AI assistants, such as a comparison ("Prisma vs X", "X vs Y"), an alternatives page ("X alternatives"), a roundup ("best X for Y"), a use-case guide ("Postgres for X", "where to host X"), or a troubleshooting fix; when they give a tracked prompt or a Prompt tracker reference (PW123); or when they want to publish such a page so AI engines can find, crawl and cite it.

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。

Systematic approach to diagnosing and fixing errors

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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.

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Clean a raw transcript before ingestion: punctuate, paragraph, label speakers, fix mistranscribed technical terms, and split long recordings by topic. Use this skill when the user drops an auto-generated transcript, subtitle file, podcast or lecture transcript, meeting recording text, or asks to process a video or audio source. Do NOT use for text that is already prose, for summarising a transcript, or for the ingestion itself.

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。

Resize and validate App Store screenshots with current asc screenshot-size data and macOS sips. Use when preparing or fixing screenshots for App Store Connect submission.

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Debug production-like issues in this repository with disciplined evidence gathering. Use when fixing failing workflows, regressions, flaky behavior, or data inconsistencies across hooks, API, DB, websocket, and UI.

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Generate database seed scripts with realistic sample data. Reads Drizzle schemas or SQL migrations, respects foreign key ordering, produces idempotent TypeScript or SQL seed files. Handles D1 batch limits, unique constraints, and domain-appropriate data. Use when populating dev/demo/test databases. Triggers: 'seed database', 'seed data', 'sample data', 'populate database', 'db seed', 'test data', 'demo data', 'generate fixtures'.

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React 19 performance patterns and composition architecture for Vite + Cloudflare projects. 50+ rules ranked by impact — eliminating waterfalls, bundle optimisation, re-render prevention, composition over boolean props, server/client boundaries, and React 19 APIs. Use when writing, reviewing, or refactoring React components. Triggers: 'react patterns', 'react review', 'react performance', 'optimise components', 'react best practices', 'composition patterns', 'why is it slow', 'reduce re-renders', 'fix waterfall'.

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Install and configure NVIDIA NemoClaw (sandboxed OpenClaw agent platform) on Linux. Handles cloudflared tunnels, Docker cgroup fixes, OpenShell, sandbox creation, remote access via Cloudflare Tunnel, and known bug workarounds. Use whenever the user mentions installing NemoClaw, setting up OpenClaw, configuring an NVIDIA Spark or DGX for sandboxed agents, or troubleshooting NemoClaw deployment.

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。