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「rest」の検索結果

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概要と使いどころ

Reapply and repair Windows Codex Desktop after Store upgrades, including custom provider models hidden by Statsig available_models filtering, the dependent blue-purple Power slider and its Ultra toggle, Fast Mode request/UI gates, locale i18n, plugin UI gates, Chrome/browser_use gates, Goal command gates, Windows Computer Use availability gates and plugin/runtime repair, phone remote-control pairing under third-party/API-key main app usage, Desktop dynamicTools/inputSchema thread-start schema drift, local conversation visibility recovery after model_provider switches, restored-conversation missing-cwd continuation repair, ASAR integrity repair, signing/installing patched MSIX packages, SDK cleanup, Fast Mode wire verification, local plugin marketplace registration, and optional custom model_instructions_file setup (the bundled system prompt, also called 听话水).

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。

chen0416ccc-cpu/codex-windows-fast-patch-skill1,2842026年10月12日 更新

Personalize COG for your workflow - creates profile, interests, and watchlist files with guided setup (run this first!)

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。

huytieu/COG-second-brain1,2822026年10月2日 更新

wp-guard

無料

Review generated or changed WordPress code — plugins, themes, and blocks — before it ships. Best used reactively after an agent writes, edits, or reviews code touching WordPress APIs: add_action/add_filter, shortcodes, meta boxes, AJAX handlers, REST routes, WP_Query or $wpdb, widgets, or WP-CLI commands. Use on 'review this plugin', 'is this safe to ship', 'make this translatable', 'speed up this query', or after tasks like 'write a plugin' or 'add an endpoint/shortcode/meta box'. Enforces escaping and sanitization, nonces plus capability checks, prepared database queries, core-API-first development, translation-ready strings, and query/caching discipline. DO NOT USE for WooCommerce-specific order, product, or checkout logic (use woo-guard), non-WordPress PHP, generic code quality review (use clean-code-guard), test code review (use test-guard), server or hosting configuration, or conceptual WordPress questions.

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。

amElnagdy/guard-skills1,2672026年7月5日 更新

Use when running the final pre-submission preflight for Agricultural Systems (AgSy) via the current Elsevier submission path / Editorial Manager — article-type selection, abstract <= 250 words, Highlights, graphical abstract, CRediT and declaration-of-interest statements, funding/AI disclosures, reference style, and data/code/model availability. Final checks; it does not draft 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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when targeting the Bulletin of the American Meteorological Society (BAMS) or deciding whether a broad-interest atmospheric/oceanic/hydrologic-sciences contribution fits this venue. Encodes the journal's review-and-community positioning, the broad-audience-significance bar, synthesis and field-campaign expectations, AMS house style, official-submission re-check, and misfit heuristics.

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when deciding whether a macro paper fits the American Economic Journal: Macroeconomics (AEJ: Macro) rather than AER, J. Monetary Economics, RED, or AEJ: Applied. Tests the broad-interest macro bar and venue fit; it does not write the paper or fix identification.

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when deciding whether a microeconomics project fits the American Economic Journal: Microeconomics (AEJ: Micro) rather than JET, GEB, Theoretical Economics, Econometrica, or AEJ: Applied. Tests scope and broad-interest fit; it does not develop the model (see aejmic-theory-model).

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when revising prose, the abstract, or the introduction of an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript for AEA house style and the broad-interest macro arc. Late-stage polish on framing and clarity; it does not fix identification, the model, or exhibits.

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when targeting Earth and Planetary Science Letters (EPSL) or deciding whether a quantitative solid-earth or planetary-science manuscript fits this venue. Encodes the journal's broad-interest process-science fit, the quantitative geochemistry/geophysics evidence bar, Elsevier house style, official-submission re-check, and desk-reject heuristics.

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when the contribution of an American Economic Journal: Microeconomics (AEJ: Micro) manuscript is fuzzy or oversold relative to the closest existing results. Stakes the theorem-relative delta against the nearest theory; it does not build the model (see aejmic-theory-model) or frame the prose (see aejmic-writing-style).

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when assembling the data, code, and documentation package for an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript to pass the AEA Data and Code Availability Policy and the AEA Data Editor's pre-publication reproducibility check. Covers macro specifics (simulation/calibration code, restricted-access data); it does not write the analysis 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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when polishing the prose of an Advanced Materials manuscript for Wiley house style, concision, precise materials nomenclature and units, and readability across materials subfields. Polishes language; does not restructure the advance or manage the length budget.

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when the empirical identification of a macro shock or dynamic causal effect is the bottleneck for an American Economic Journal: Macroeconomics (AEJ: Macro) manuscript — SVAR, local projections, narrative, high-frequency/proxy-VAR, or micro-data macro designs. Stress-tests the identification to the AEJ: Macro broad-interest quantitative bar; for model-parameter identification see aejmac-theory-model.

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when assembling the data and code deposit for an AEJ: Economic Policy manuscript to satisfy the AEA Data and Code Availability Policy and the AEA Data Editor's pre-publication reproducibility check. Builds the openICPSR deposit, README, and restricted-data access paths; it does not run the analysis or write the paper.

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when an Advanced Materials manuscript must be fit to its article-type format — Communication versus Research Article — where word count and display items are budgeted together against a typeset page limit. Manages the length budget; does not restructure the science or polish prose line by line.

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Use when running the final pre-submission preflight for an Accounting, Organizations and Society (AOS) manuscript — Editorial Manager files (anonymized manuscript, separate title page, declarations), Elsevier policies (competing interests, AI, ethics), and open-access decisions. Checks readiness to submit; it does not handle the post-decision response (aos-rebuttal).

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。

brycewang-stanford/Awesome-Journal-Skills1,2582026年9月27日 更新

Apply approved Xcode build optimization changes following best practices, then re-benchmark to verify improvement. Use when a developer has an approved optimization plan from xcode-build-orchestrator, wants to apply specific build fixes, needs help implementing build setting changes, script phase guards, source-level compilation fixes, or SPM restructuring that was recommended by an analysis skill.

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。

AvdLee/Xcode-Build-Optimization-Agent-Skill1,2562026年9月14日 更新

Email campaign/sequence performance review composite. Pulls campaign data (sends, opens, replies, bounces), reads actual email copy and subject lines, analyzes reply content (objections, positive interest, questions), and produces a diagnostic report covering quantitative metrics, copy quality, lead quality, and actionable recommendations. Tool-agnostic — works with Smartlead (MCP), Instantly, Outreach, Lemlist, Apollo, or CSV 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。

gooseworks-ai/goose-skills1,2522026年10月15日 更新

Research LinkedIn profiles and write personalized messages for any LinkedIn message type — connection requests, InMails, DMs, message requests, post comments, and comment replies. Takes LinkedIn URLs as input, researches each person (profile data + recent posts via Apify), and generates messages tailored to each lead's background, interests, and recent activity. Exports tool-ready CSVs for Dripify, Expandi, Botdog, PhantomBuster, or generic format. No LinkedIn cookies or login required.

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。

gooseworks-ai/goose-skills1,2522026年10月15日 更新

Monitor competitor pricing pages via live web scrape and Web Archive snapshots. Track plan changes, tier restructuring, new pricing models, and feature gating shifts. Produces a pricing comparison matrix and flags when a competitor changes packaging. Use when a product marketing team needs to stay current on competitive pricing or when preparing for a pricing change of their own.

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。

gooseworks-ai/goose-skills1,2522026年10月15日 更新

Recreate a static graphic ad (Pinterest pin, IG/FB feed image, poster) from a reference image, swapping in a new brand's product and new copy while keeping the reference's layout, composition, and visual energy. ALWAYS generated with GPT Image 2 in edit-the-reference mode (fal-ai/gpt-image-1/edit-image, a billed FAL generation); the HTML/goose-graphics overlay is only an optional text-finishing step, never the generator. The static-graphics counterpart to the video remix-ad skill; this is what the app calls when a user picks a reference ad and wants it for their own product.

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。

gooseworks-ai/goose-skills1,2522026年10月15日 更新

Assemble an animated character-explainer video ad (any art style — Pixar-style 3D, claymation, anime, paper-cut, felt) (~77s, 9:16) built on an "N types of X" listicle spine — a recurring human protagonist plus a locked cast of N persona characters, one per list item. Given the per-scene i2v clips + a per-scene target-duration table + a narration track, it trims each clip to its scene window, re-encodes every segment to identical 1080x1920/30fps/libx264/yuv420p (decrease+pad, never crop) so the concat demuxer never drops frames, concats, and muxes audio — in RESTYLE mode the source ad's VO+music mix is reused verbatim, in ORIGINAL mode fresh per-scene VO (loudnorm I=-14) is mixed under an optional music bed (loudnorm I=-26). A static-still fallback loops a scene's keyframe when its clip is missing/failed, so the master always assembles; libass captions are burned last. FREE deterministic assembly (Python + ffmpeg, no bash, no paid calls); the recipe supplies the clips, keyframes, VO or source audio, and caption table and gates the paid cast-anchor/keyframe/Kling-i2v/VO/music calls to their own capabilities. Use for the 3d-character-explainer listicle format.

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。

gooseworks-ai/goose-skills1,2522026年10月15日 更新

Render a 'search-grid' (Pinterest search-moodboard) video from a config — a real-DOM page with four continuous beats (masonry search grid + typing hook with counter-drift columns → 3 cards slide in from the right and stack → the top card box-grows to fullscreen then swipe-left ×2 through captioned feature shots → end card), frame-stepped via Chromium and encoded with FFmpeg — deterministic assembly, FREE (real brand photos + logo; the optional music bed comes from create-music-elevenlabs), so type/logo/photos stay pixel-crisp. Use for the search-grid format.

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。

gooseworks-ai/goose-skills1,2522026年10月15日 更新

Governs Microsoft Fabric OneLake catalog health, protection, and trust through Fabric Admin, Core, and Power BI REST APIs. Use for tenant or owner-scoped audits and guarded remediation of domains, workspace assignment, capacity, labels, tags, descriptions, refresh, and item identity. Catalog item discovery belongs to search-consumption-cli.

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。

microsoft/skills-for-fabric1,2502026年10月5日 更新