「aims」の検索結果

Persistent research knowledge base that accumulates papers, ideas, experiments, claims, and their relationships across the entire research lifecycle. Inspired by Karpathy's LLM Wiki pattern. Use when user says "知识库", "research wiki", "add paper", "wiki query", "查知识库", or wants to build/query a persistent field map.

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 the full patent specification from claims and invention disclosure. Use when user says "撰写说明书", "write specification", "写说明书", "patent description", or wants to draft the complete patent specification.

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。

Zero-context verification that every number, comparison, and scope claim in the paper matches raw result files. Uses a fresh cross-model reviewer with NO prior context to prevent confirmation bias. Use when user says "审查论文数据", "check paper claims", "verify numbers", "论文数字核对", or before submission to ensure paper-to-evidence fidelity.

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 experiment integrity before claiming results. Uses cross-model review (external reviewer backend) to check for fake ground truth, score normalization fraud, phantom results, and insufficient scope. Use when user says "审计实验", "check experiment integrity", "audit results", "实验诚实度", or after experiments complete before writing 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。

Assess community issues, validate technical claims, request missing evidence, and prepare valid work for human disposition.

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。

Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.

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。

Records research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract decisions, experiments, dead ends, claims, heuristics, and pivots, and writing them into the ara/ directory with user-vs-AI provenance tags. Use as a session epilogue — never during execution — to maintain a faithful, auditable trace of how a research project actually evolved.

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。

Operate professional paid advertising across Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for account intake, source-grounded audits, strategy, budget and measurement planning, creative production, experiments, reporting, monitoring, and explicitly approved campaign changes. Also trigger on PPC, paid social, retail media, attribution, tracking, landing pages, cross-platform conversion totals, negative keywords or search terms, beta-feature scoring, stale platform claims, API-token or credential setup, campaign deletion, and safe Claude Ads installation or uninstall.

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。

Refresh Claude Ads platform, API, policy, regulation, benchmark, issue, pull-request, fork, and repository evidence. Use for ads research refresh, expired refresh_due dates, stale API or platform claims, reverify-or-demote decisions, release-current claim validation, ecosystem review, current platform changes, or updating paid-media knowledge. When tools or sources are unavailable, still demote the stale claim for the current run and block dependent release-current assertions before requesting access.

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。

Guided customization of your product counsel practice profile — change one thing without re-running the whole cold-start interview. Adjust risk calibration, escalation contacts, launch review framework, marketing claims posture, or matter workspace paths. Use when the user says "change my [thing]", "update my profile", "edit my framework", "retune my calibration", or "customize".

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。

Research a game, engine or modding technique on the open web with archive-aware, rate-limit-safe searches — Wayback Machine/archive.today for dead forums (XeNTaX, Zenhax, old threads), GitHub code/repo search, Nexus/Steam Workshop/Thunderstore APIs, Reddit JSON, YouTube transcripts, plus archive snapshots as evidence. Use when starting work on a game ("how did people mod X before?"), when a documented tool/link is dead, when forum threads are login-gated (semi-auto handoff to the human), and before writing a field note so claims carry source 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。

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

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。

Autonomous senior-operator mode for AI agents that resolve tasks end to end without babysitting and never create new problems. The agent verifies every claim against real evidence (web search dated to the current month and year, the codebase, and available tools, MCPs, and CLIs); it never guesses, never fakes confidence, and never claims something is done without proof. It stays silent and keeps working, interrupting the user only on three stops, namely a destructive or irreversible action, a dead-end with no evidence after exhausting sources, or genuine ambiguity that changes the outcome. Output is short, literal, and human. Use when the user says "not-your-babysitter", "nanny mode", "work autonomously", "stop babysitting", or "no hand-holding", or wants an agent that solves problems on its own, especially hands-on engineering and operational tasks. Do not use when the user explicitly wants a tutorial, a verbose walkthrough, or open-ended brainstorming.

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。

Keep a Linear issue aligned with implementation evidence, acceptance criteria, code review, and deployment state while avoiding premature completion 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。

Show the user real screenshots of the work as it progresses, without being asked. Capture the start, the key moment and the result of every visual change, send them as files with captions as soon as each is ready, and look at every image before sending it. Use on any task with a visible result (UI, pages, games, 3D, charts, motion), when the user says "show me", "screenshots", "keep giving me screenshots" or "where are the screenshots?", and before any report that claims a visual change works.

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 work, verify claims with concrete evidence, and explain the result in simple grade-5 language. Use when the user asks to review, audit, check, verify, explain a change, explain a fix, summarize test results, validate whether something works, or translate technical findings into plain language for non-technical readers.

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 a website or digital experience against its supplied source references for originality and plagiarism risk. Use when Codex must compare current or historical site output with reference pages, capture packs, screenshots, copy, brands, numbers, images, assets, videos, layouts, motion, or code; raise evidence-backed red flags; distinguish common visual grammar from distinctive copying; and propose concrete fixes without making unsupported legal 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。

Turn a completed daily UI inspiration capture into exactly five original landing-page builds, one per separate Codex task, using Sites. Use when the user asks to turn the daily inspiration references, a five-item UI prompt pack, or a dated `*-ui-inspiration-capture` article into distinct HTML landing pages while changing the source brands, names, copy, people, numbers, pricing, claims, and imagery.

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。

Review Apache Pinot performance when hot paths change or a PR makes benchmark or efficiency 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。

Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose.

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。

Review and validate claims using counter-hypothesis testing. Use when verifying technical content, checking references, validating API endpoints, or performing quality assurance on deliverables.

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。

Evaluate factual claims in AI-generated text and teach a lightweight verification habit. Use when a learner wants to fact-check an AI answer, identify uncertainty, choose appropriate independent sources, or practise critical AI literacy.

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。

Find, verify, and synthesize scientific literature — from "what's the seminal paper for X" through full multi-source reviews. Covers grounding claims in real retrieved sources, avoiding fabricated citations, handling retractions, and calibrating confidence to evidence strength.

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 an implementation plan as one interactive HTML page - a tree of claims (why › what › how › where), each proved by one exhibit (UI mockup, state machine, call stack, schema or code), with the decisions the user has to make placed on the claim they change. Use when the user types /html-plan, or asks for a plan, RFC or design before building something that touches more than a couple of files.

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。