「iter」の検索結果

Use when authoring or rewriting a roadmap in agents/roadmaps/ — phases, goal, acceptance criteria, council notes; fires even on 'write a plan for X' / 'draft a roadmap'.

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Use when designing or auditing a sales pipeline — stage exit criteria, per-cell conversion, coverage reasoning, leak detection. Triggers on 'tighten our pipeline', 'where is the leak'.

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 before merging a release-shaped PR — pre-merge checklist, rollout plan, rollback criteria, ops handoff. Triggers on 'ready to ship', 'launch checklist', 'rollout plan for X'.

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 drive a scalar metric down or up across bounded iterations — keep on strict improvement, revert otherwise, state on disk. Triggers 'minimize X', 'optimize until it stops improving'.

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。

Two agents co-create an artifact through turn-based iteration until both signal DONE.

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 an explicitly authorized overnight collaboration with one desktop portal, a durable CLI writer and independent CLI review. Use for unattended work, not routine short tasks.

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Use quando o Codex está construindo ou iterando em um jogo web (HTML/JS) e precisa de um loop confiável de desenvolvimento + teste: implementar pequenas mudanças, executar um script de teste baseado em Playwright com rajadas curtas de input e pausas intencionais, inspecionar screenshots/texto e revisar erros de console com render_game_to_text.

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Acelere a inferência de LLMs usando especulative decoding, múltiplas cabeças Medusa e técnicas de lookahead decoding. Use ao otimizar velocidade de inferência (aceleração de 1,5-3,6×), reduzir latência em aplicações em tempo real ou fazer deploy de modelos com recursos computacionais limitados. Cobre modelos draft, atenção em árvore, iteração de Jacobi, geração paralela de tokens e estratégias de deploy em produção.

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Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until it reaches the repository's configured Greptile merge threshold with zero unresolved actionable comments, or until the five-review maximum is reached. Triggers Greptile review, fixes all actionable comments, pushes/re-shelves, re-triggers review only for new head SHAs unless a 5/5 score is already published, and repeats. Use when the user wants to optimize a PR/MR/CL against Greptile's code review standards without creating runaway review loops.

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Load this skill whenever the project contains audio or video content, media players, podcasts, video embeds, or any <audio>/<video> elements. Under no circumstances publish audio or video without captions, transcripts, and audio descriptions where required. Absolutely always apply WCAG 1.2 criteria for time-based media.

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Load this skill whenever you are filing, reviewing, or generating accessibility bug reports — whether from automated tool output, manual testing, user reports, or testing with disabled people. The purpose of this skill is to make accessibility findings easier to report accurately, connect them to real people and tasks, and let developers reproduce, understand, and fix them without unnecessary back-and-forth. Absolutely always describe the barrier and its task impact before citing a WCAG criterion. Under no circumstances guess a disability diagnosis, treat automated tool output as a conformance conclusion, or expose secrets/personal data in a report.

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[Process] Use when the developer wants something explained or taught, or wants to know HOW TO REVIEW a change — by default the current working tasks + changes in context, or whatever the prompt names (a plan, a subsystem, a decision, a concept, a bug). AI derives WHAT to explain from the prompt and ALWAYS delivers a teacher-and-coach review guide, high level first then detail: what was done, a VISUAL MAP (system flowchart, domain ERD, sequence diagrams), the user stories and business rules with their REAL test-case IDs, a REVIEW PATH naming which files to open first and in what order with an exit criterion per stage, the technical concepts needed to follow it, how it works, why THIS solution, every alternative option with pros/cons, the trade-offs accepted, the blast radius, HOW TO TEST AND DEMO the change, the developer's decision levers, and written challenge prompts that provoke the reader to pressure-test the work. Works at ANY scope — from one line of code to the whole project: it SIZES the target into a scope tier, DECOMPOSES a large one into understanding groups, BREAKS the work into tasks before the first deep read, and ACCUMULATES the report group by group on disk so a huge explanation stays complete instead of thinning out. Writes the full report to a single combined markdown file (plans/reports/understand-*.md) that opens with a detailed summary section — or delivers it in full in chat when Step 3 finds no git-ignored directory for it — and always summarizes it in chat. Regardless of coding level. Never interrogates, never quizzes, never blocks.

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。

[Project Management] Use when converting ideas to PBIs, validating problem hypotheses, adding acceptance criteria, or refining 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。

[Project Management] Use when creating user stories, writing acceptance criteria, analyzing requirements, or mapping business processes.

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。

Evaluates candidate profiles against a job description and hiring criteria. Use when the user provides candidate profiles plus a role definition and wants consistent screening, matched requirements, and an interview recommendation.

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Qualifies and scores B2B prospects against a supplied ideal customer profile. Use when the user provides a lead list, company records, prospect data, or qualification criteria and wants prioritization, fit analysis, or disqualification reasons.

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Classifies professional profiles into buyer, influencer, user, decision-maker, founder, recruiter, or other personas. Use when the user provides profiles and wants persona labels with evidence and confidence. Must not infer sensitive personal attributes.

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Divides a lead list into useful commercial segments. Use when the user provides a combined lead list and wants segments with criteria, sizes, recommended treatment, and priority.

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Converts a job description into a structured candidate-sourcing workflow. Use when the user provides a role and wants candidate criteria, search terms, source recommendations, and a screening process. Must avoid sourcing on sensitive personal attributes.

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。

Virtual QA Lead that turns requirements into review-ready, TestRail-importable test cases in one conversation. Use it whenever the user has requirements, a spec, a user story, or acceptance criteria (PDF, DOCX, XLSX, TXT, MD, or pasted text) and wants test cases, a test plan, a checklist, test coverage, a regression suite, or a TestRail/Qase/Zephyr export, even without saying "test cases" ("write tests for this spec", "what should we check here?"). Especially useful when they attach their team's existing test cases to match. When the spec describes an API (endpoints, status codes, schemas, auth, OpenAPI/Swagger), Casely also builds a runnable Postman collection, so use it for "API tests", "Postman collection", or "tests I can run in Newman/CI". Triggers on the same request in any language.

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。

Project-level WeChat article drafting workflow for turning source materials, repo intakes, product notes, screenshots, or existing markdown into a publishable Chinese公众号 draft. Use for writing, rewriting, evidence-gating, title options, platform adaptation, and image planning before optional publishing.

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Project-level workflow for turning GitHub repositories, URLs, local product materials, or markdown drafts into WeChat Official Account articles and draft-box submissions. Use when the user asks to write, adapt, illustrate, verify, or publish a WeChat/公众号 article, especially from a GitHub repo or existing technical/product material.

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。

Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.

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Retrieves scientific papers from PubMed and creates plain-language research summaries. Use when users ask about medical research, scientific studies, clinical trials, disease treatments, or want to understand recent scientific literature on any biomedical topic.

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。