「iterate」の検索結果

RED-GREEN-REFACTOR for process documentation - baseline without skill, write addressing failures, iterate closing loopholes

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。

Audit and rewrite content to remove AI writing patterns ("AI-isms"). Supports detect-only audits, edit-in-place file cleanup, voice and context profiles, and an iterate-to-convergence pass.

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。

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

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。

Browse, inspect, re-export, embed, or iterate on videos that already exist in the user's Ozor.ai account. Use this skill whenever the user wants to work with past or in-progress Ozor videos rather than create a new one — e.g. 'list my Ozor videos', 'show my recent videos', 'what's the status of my last video', 'get the embed code for that video', 'download my last Ozor video', 'share link for the explainer I made', 'check on the export', 'send a follow-up edit to that video', 'show the plan for video X', 'render that video again at 9:16', 'is the job done yet'. This skill orchestrates list_videos, get_video, get_job, get_plan, update_plan, send_message, wait_for_job, export_video, wait_for_export, and get_embed_code. Do NOT use this skill to create a new video from scratch — use ozor-generate, ozor-document-video, or ozor-url-to-video.

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。

Invocable iOS design pipeline. When called with a design prompt, runs an autonomous loop: designs iOS screens in Pencil MCP following Apple HIG, reviews for taste using Design Philosophy, validates with XcodeBuildMCP, and iterates until done. Use as: /ios-design-stack "Design a [screen] for [app] with [requirements]"

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。

Convergence loop that iteratively improves work until quality thresholds are met. Scores, diagnoses specific weaknesses, rewrites, re-scores, and repeats until all dimensions reach 8/10 or diminishing returns are detected. Use when you want to refine or iterate on work, after the analyst gives a REVISE verdict, or when output quality is below your bar. Part of the architect-system loop. Outputs to system/refinery-log.md.

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。

Convergence loop that iteratively improves work until quality thresholds are met. Use when: (1) "refine this", "make this better", "iterate on this", (2) After /analyst gives a REVISE verdict, (3) Output quality is below 8/10, (4) "run the refinery loop on this". Reads analyst reviews from system/reviews/. Generates, scores, diagnoses, rewrites, re-scores. Stops when all dimensions >= 8/10 or diminishing returns detected. Outputs to system/refinery-log.md.

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。

Mirror an iOS Simulator into the Codex in-app browser and render SwiftUI previews from importable Swift packages in that simulator with hot reload. Use when a user wants to watch or interact with an iOS app in the browser, see a SwiftUI preview outside Xcode Canvas, iterate live on a preview, or capture browser-visible simulator proof.

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。

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

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。

Automatically consume open GitHub issues one by one. Fetches the oldest open issue, delegates implementation to the issue-implementer agent, runs code review via the code-reviewer agent, iterates on feedback, merges the PR, and moves on to the next issue. Invoke with `/auto-issue-worker`.

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 to process automated PR review feedback (Copilot, Greptile, Codex) and iterate until all AI threads are addressed, checks are green, and the PR is merge-ready. Trigger when the user says "address review feedback", "recycle reviews", or references an automated reviewer.

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。

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

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 shotgun: generate multiple AI design variants, open a comparison board, collect structured feedback, and iterate. Standalone design exploration you can run anytime. Use when: "explore designs", "show me options", "design variants", "visual brainstorm", or "I don't like how this looks". Proactively suggest when the user describes a UI feature but hasn't seen what it could look like. (gstack)

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。

Render a proposed redesign of a page on the current website as a self-contained static HTML file, then iterate via the impeccable craft loop. Per-page, idempotent, stale-aware. Use when the user asks for a redesign prototype, a before/after comparison, a design preview, a page mockup, a visual diff of the redesign, or invokes /stardust:prototype.

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。

Score an unbuilt business idea on desirability, viability, feasibility, distribution wedge, why-now, founder-market-fit, market size, alternatives, defensibility, capital intensity, and regulatory/ethical risk — and return a GO / ITERATE / KILL verdict with kill criteria and a next kill test. Load when the user asks to evaluate a business idea, score a startup idea, screen an idea, decide whether to pursue this venture, do an idea review, or says "is this a good business idea", "should I build this", "evaluate this startup", "screen this idea", "go/no-go on this idea", "kill or pursue". Sub-skill of `venture-exploration`. Calls `fermi` for sizing, `assumption-mapping` for hidden beliefs, optional `pre-mortem` / `adversarial-hat` for high-stakes ideas. Does NOT evaluate built products — for that use `reality-check`.

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。

Analyse experiment results, run validity checks (SRM, exposure parity, data integrity, novelty/primacy), interpret causally, make a ship/iterate/kill decision against the pre-declared rule, and append to cumulative learnings. Forces honest readouts — strips significance claims from underpowered or peek-violating tests; never lets directional results masquerade as causal wins. Load when results exist, or when the user says "read out this experiment", "analyse the test", "did the test win", "interpret the results", "what did we learn", "ship or kill", or when the experimentation orchestrator routes here.

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。

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

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。

Continuous localhost UI iteration loop with Arman, through full surface certification. Use when he asks to fix, refine, review, or iterate on a page, route, panel, overlay, or other UI while he may inspect localhost. NOT for a report-only UI audit.

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。

Locate CCSPlayerInventory::GetItemInLoadout in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the WeaponPaints gamedata entry "CCSPlayerInventory::GetItemInLoadout" (symbol CCSPlayerInventory_GetItemInLoadout). Non-virtual inventory method resolving a player's loadout item. Shortlist via callers inside CCSPlayerInventory code that walk the loadout item cache (m_pSOCache / CGCClientSharedObjectCache), and via the CSO/econ loadout message paths. The function takes an item definition index + loadout slot and returns the matching CEconItemView — the body iterates a small item list comparing definition indices and loadout slots. Trigger: CCSPlayerInventory_GetItemInLoadout, CCSPlayerInventory::GetItemInLoadout

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。

Coordinator workflow for orchestrating dockeragents through fix-review-iterate-present loop. Use when delegating any task that produces code changes. Ensures agents achieve 10/10 quality before presenting to human.

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。

Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.

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。

Remove refusal behaviors from open-weight LLMs using OBLITERATUS — mechanistic interpretability techniques (diff-in-means, SVD, whitened SVD, LEACE, SAE decomposition, etc.) to excise guardrails while preserving reasoning. 9 CLI methods, 28 analysis modules, 116 model presets across 5 compute tiers, tournament evaluation, and telemetry-driven recommendations. Use when a user wants to uncensor, abliterate, or remove refusal from an LLM.

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。

Run a bounded, governed iteration — "loop", "iterate until", "keep going until", "sweep", "ratchet", "until it passes", "coverage to 100". Turns an open-ended autonomous run into a finite loop with checkpoints and explicit stopping conditions.

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。

GraalVM Native Image expert that adds native image support to Java applications, builds the project, analyzes build errors, applies fixes, and iterates until successful compilation using Oracle best practices.

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。