「iter」の検索結果

Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints.

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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。

Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.

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.

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Improve AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.

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This skill covers the principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development.

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 users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation 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。

You are a senior documentation engineer that generates comprehensive technical documentation pages with evidence-based depth.

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。

This is the core skill for the deep research and writing tool—combining AI-driven deep research with well-formatted written outputs. Every document produced is backed by comprehensive literature search and verified citations through the research-lookup 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。

Create and improve agent skills following the Agent Skills specification. Use when asked to create, write, or update skills.

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。

Comprehensive investigation of complex multi-domain narratives (technology, theology, policy, finance). Systematically decouples factual claims from speculation through iterative verification, multi-source comparison, and contradiction resolution. Use for investigations requiring institutional knowledge, historical context, and handling of conflicting incentives.

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Write focused tdmcp tests for one assigned coverage gap. Use for Vitest/msw unit tests, integration tests, bridge tests, CLI/config/resource tests, and regression tests that should raise coverage without weakening behavior.

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Wire builders' isolated tdmcp tool files into the shared registries, CLI, and docs as a single writer, conflict-safe, and confirm a green typecheck + build. Use when integrating/wiring/registering new tdmcp tools, adding their CLI commands, resolving build breaks after parallel feature work, or merging several builders' files into the registry without conflicts.

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You are an expert technical writer creating comprehensive project documentation. Your goal is to write a README.md that is absurdly thorough—the kind of documentation you wish every project had.

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Use when asked to compare, cross-review, merge, judge, choose, or arbitrate competing plans from multiple agents such as Codex and Claude Code; when given two or more proposed plans, session IDs, transcripts, plan documents, PR descriptions, or pasted strategies; or when the user wants one recommended execution plan after agents review each other's proposals.

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。

Interactive 9-step prompt crafting and delegation protocol for autonomous multi-agent teams. Enforces objective verification, integrity modes, and acceptance criteria across Antigravity, Claude Code, Cursor, OpenCode, Codex, and Roo Code.

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LLM Agent engineering: pattern selection (12-mode matrix), data simulation, convergence iteration. Covers intent routing, function calling, ReAct, MCP, prompt chaining, guardrails, evaluation.

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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。

Generate engaging, localized App Store release notes (What's New) from git log, bullet points, or free text using canonical metadata under `./metadata`. Optionally pairs with promotional text updates.

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]"

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Write Korean job application cover letter drafts from a question, JD, resume.md, and optional company values input. Use when the user asks for 자기소개서, 자소서, 지원동기, 입사 후 포부, 필살기, 3C4P experience decomposition, experience-based application answers, or tailored cover letter text grounded in resume.md evidence.

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Analyze a job description, hiring post, or recruitment page for role requirements, evaluation criteria, keywords, risks, and resume or cover letter angles. Use when the user provides a JD URL/text, asks what a company is looking for, wants JD-resume gap analysis, or needs inputs for a tailored cover letter. 한국어 요청도 포함합니다 - 채용공고 분석, 공고 분석, JD 분석, 직무기술서 분석, 자격요건, 우대사항, 이 공고 뭘 원하는지, 공고랑 내 경력 비교.

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: writing or reviewing cover letters, recruiter email replies, LinkedIn outreach, or interview follow-ups. Removes AI-template patterns and writes with a specific, confident, human voice.

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。

Context-survival and proactive-iteration extensions. Always-on. Covers Working Buffer Protocol, Compaction Recovery, Relentless Resourcefulness, and Self-Improvement Guardrails.

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。