「concise」の検索結果

Cut token usage across the whole session without losing correctness or substance — concise user replies, lean tests/docs/plans/comments, tight code, disciplined context and tool use, and cheap sub-agent delegation. Load when the user wants less verbosity, lower cost, fewer tokens, or a "token diet" / "lean mode"; also triggered by /token-diet or "token diet on".

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 concise executive summaries from detailed analysis. Use when preparing board decks, executive briefings, or condensing complex analysis into decision-ready formats for senior audiences.

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。

AI-optimized web search, image search and content extraction via BytePlus InfoQuest API. Use this skill when you need to gather concise and up-to-date information from the web, find images, or extract clean content from specific URLs.

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。

Produce a high-confidence, CONCISE implementation / architecture / strategy PLAN that follows the OMC plan system end to end. It first runs OMC's real requirements interview (auto-chains the `omc-plan` skill: one question at a time, explore-first, Analyst consult) to produce an initial plan in `.omc/plans/`, then DEEPENS that plan with a 3-round ITERATIVE fusion loop — each round an Opus 4.8 panelist (Agent subagent) and a GPT-5.5 panelist (via codex) critique/improve it IN PARALLEL and BLIND, then Opus 4.8 (the orchestrator) judges and synthesizes one tighter plan that seeds the next round, stopping early on convergence. Writes the final dense plan back to the same `.omc/plans/<slug>.md`, then offers the OMC handoff (`/omc-plan --review` → `/team` or `/ralph`). Use for high-stakes planning, architecture decisions, strategy calls, and hard debugging — especially when the user runs /plan or asks how to approach a non-trivial build. Reuses the `fusion` skill's run_codex.sh + judge rubric. NOT for trivial tasks (single pass is enough).

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。

Push branch and create a GitHub PR with concise, issue-linked description

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。

Summarize authored commits over a user-specified time period into a concise update

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。

Scientific manuscript writing: IMRAD, citation styles (APA/AMA/Vancouver/IEEE), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA/ARRIVE), writing principles (clarity/conciseness/accuracy), venue-specific style. For LaTeX see companion assets.

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。

Canonical rules for writing git commits in the Shift codebase. Use whenever the user asks to commit, stage and commit, create a pull request that requires commits, or draft a commit message. Enforces Conventional Commits, release-note quality, concise subjects, and logical commit boundaries.

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。

Write less code and say less about it. Applies YAGNI and stdlib/native-first so the agent writes the minimum code that needs to exist, and responds tersely — stripping filler, hedging, and pleasantries while keeping code, identifiers, and technical terms exact. Use whenever writing, modifying, refactoring, reviewing, or explaining code, or any response where output volume drives token cost — even if the user never says "minimal" or "concise". Especially in agentic coding, where the volume of generated code and prose runs up the bill.

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。

Stage the relevant git changes and create a commit using this repo's emoji-prefixed conventional commit format. Use when the user asks Codex to commit changes, stage and commit selected files, or draft a concise Chinese commit message from the current diff.

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。

Implements GDPR Article 12 transparent information and communication requirements, covering concise, intelligible, and plain language obligations, response timelines, fee and refusal provisions, and layered notice design. Activate for transparent communication, Art. 12, privacy notice, plain language, response timeline queries.

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 an agent-produced diff is committed, pushed, opened as a PR, merged, landed, or applied to user files when explicit implementation approval is missing. Trigger for review gate, review pack, approve before landing, diff first then land, human approval, merge gate, commit gate, push gate, or PR readiness. Produces a concise review pack, records risks and verification, and blocks landing until a human explicitly approves or approves with required fixes.

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 natural vertical street-interview and walk-and-talk video prompts for MiniMax H3 or Seedance 2.0. Use when a user wants spontaneous documentary energy, a referenced recurring person, first-person handheld follow, concise dialogue, moving daylight, believable street parallax, or a consent-led interaction that must fit 4–15 seconds without unreachable beats.

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。

Discovers the core attributes of the current code repository and its projects — languages, frameworks, tooling, and where things live — and writes a concise reference section directly into the project's AGENTS.md or CLAUDE.md for other skills, agents, and hooks to consume. Use when scanning, analyzing, or detecting the project's technology stack, build tools, or repository structure. Does not create or update project documentation — use project-documentation for writing feature or system docs.

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 concise, structured summaries of requirements for quick team understanding. Use when analyzing requirements from text documents (MD, TXT, DOCX) or technical specifications to create bullet-point summaries that highlight core functionality and dependencies/constraints. Ideal for sprint planning, stakeholder updates, team onboarding, or any situation requiring rapid comprehension of requirement documents.

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。

Instrument code to support efficient git bisect by producing deterministic pass/fail signals and concise runtime summaries for each tested commit. Use when debugging regressions with git bisect, automating bisect workflows, creating bisect test scripts, handling flaky tests during bisection, or needing clear exit codes and logging for automated bisect runs. Helps identify the exact commit that introduced a bug through automated testing.

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。

Generates meaningful comments and documentation for code to improve maintenance and readability. Use when adding documentation to Python or Java code, including function/method docstrings, class documentation, inline explanations for complex logic, and code annotations (TODO, FIXME). Analyzes existing comment style in the codebase to match conventions. Produces clear, concise comments that explain the "why" not just the "what", following best practices for each 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。

Generate concise summaries of source code at multiple scales. Use when users ask to summarize, explain, or understand code - whether it's a single function, a class, a module, or an entire codebase. Handles function-level code by explaining intention and core logic, and large codebases by providing high-level overviews with drill-down capabilities for specific modules.

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 professional company tear sheets using S&P Capital IQ data via the Kensho LLM-ready API MCP server. Use this skill whenever the user asks for a tear sheet, company one-pager, company profile, fact sheet, company snapshot, or company overview document — especially when they mention a specific company name or ticker. Also trigger when users ask for equity research summaries, M&A company profiles, corporate development target profiles, sales/BD meeting prep documents, or any concise single-company financial summary. This skill supports four audience types: equity research, investment banking/M&A, corporate development, and sales/business development. If the user doesn't specify an audience, ask. Works for both public and private companies.

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 a concise 4-5 page equity research earnings preview for a single company. Analyzes the most recent earnings transcript, competitor landscape, valuation, and recent news to produce a professional HTML report.

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。

Condense rebuttal prose into fewer words without changing the original meaning. Use when a response block, paragraph, or selected passage is too long but all technical content, citations, and commitments must stay intact. Supports academic English.

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。

Summarize extracted paper text into concise Markdown memory for later Stage 2 and Stage 4 background use, with fixed section headings and no fabricated claims.

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。

Write clear, concise, and accurate technical documentation including API references, user guides, tutorials, changelogs, and architecture docs, tailored to the target audience. Use when the user requests technical writing or provides relevant inputs for this workflow.

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。

Summarize text using extractive, abstractive, hierarchical, and multi-document techniques, producing concise outputs at configurable detail levels. Use when the user requests summarization or provides relevant inputs for this workflow.

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。