「claim」の検索結果

Use for social science academic paper drafting, outlining, diagnosis, review, and revision. Trigger for topic diagnosis, research question refinement, literature review planning, CNKI/Google Scholar literature search-to-Zotero workflows, structured paper reading notes, theoretical framework design, research design critique, draft review, section or paragraph revision, citation and evidence risk checking, causal-claim checking, and pre-submission review. Do not use for purely creative writing or non-academic editing.

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 record, claim, rate the severity of, or report any security finding — before marking anything [CONFIRMED] or writing it into the 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。

Verify a claim with fresh local evidence: restate it falsifiably, capture baseline and treatment, compare artifacts, and return VERIFIED, NOT VERIFIED, or INCONCLUSIVE.

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 doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).

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。

Access USPTO patent data via PatentsView REST API and Google Patents Public Data (BigQuery). Search by inventor, assignee, CPC, or keywords; download metadata and claims; analyze portfolios; track tech trends. For IP landscape analysis, competitor monitoring, prior art search, and tech forecasting in life sciences and biotech.

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, redesign, generate, and improve IEEE manuscript figures, tables, captions, result presentation, plotting scripts, visual polish, hybrid Python/R plus vector-editor workflows, publication-ready matplotlib house style, and layout using routed visual-evidence checks. Use when checking or creating plot readability, axes, legends, line overlap, table structure, metric reporting, captions, grayscale accessibility, IEEE one-column/two-column layout, figure/table placement, claim-evidence mapping, reviewer first-impression risks, matplotlib/seaborn or ggplot2 figure code, SVG/PDF/TIFF/PNG export, Illustrator/Inkscape/PowerPoint/Figma finishing plans, or IEEE-style engineering evidence graphics.

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。

Check, clean, verify, and improve IEEE citations, references, BibTeX entries, citation positioning, related-work logic, DOI metadata, venue names, and reference formatting using routed citation and metadata guidance. Use when preparing IEEE manuscripts, fixing bibliography errors, verifying reference completeness, improving related work, checking whether citations support claims, or identifying missing classic/recent baselines.

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。

How to find and fix performance problems in Shift's desktop app. Use when something is slow, choppy, janky, or laggy (scrubbing, dragging, editing, undo, opening fonts), when profiling or measuring, when adding or reviewing perf tests, and before claiming a change made something faster.

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。

Adversarially fact-check DOCS.md files against the actual source code, verifying every concrete claim rather than trusting structure checks. Use when the user asks to audit docs, verify documentation accuracy, check whether docs are still true, or on a scheduled documentation review. This is the semantic layer the mechanical checkers cannot cover.

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 running any confirmatory analysis or looking at outcome data, when testing a hypothesis, computing a p-value, or about to claim an effect - locks predictions and decision rules before results are seen

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。

Analyze construction schedule delays for claims and recovery. Perform time impact analysis, identify delay causes, calculate damages, and document for disputes.

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。

Track and manage construction warranties. Monitor expiration dates, claims, and manufacturer documentation.

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。

Take any claim and design + execute a complete research protocol to test it. Apply scientific method automatically: design study, gather data, run analysis, provide verdict with confidence level.

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。

Aggregate and analyze customer reviews from G2, Capterra, Trustpilot, App Store, and other platforms. Performs sentiment analysis, identifies pain points, extracts feature feedback, generates marketing claims, and compares competitor reviews. Use when users need review analysis, competitive intelligence, or customer feedback insights.

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。

Build an insurance-grade home inventory from a folder of photos and receipts -- identifies items, pulls values from receipts, estimates replacement costs, organizes by room, and outputs the documentation an insurance claim actually requires. Update mode keeps it current after new purchases.

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 your calendar with Cowork's calendar tools -- measure meeting load and fragmentation, identify which recurring meetings earn their slot, propose consolidations and focus blocks, and draft the diplomatic messages that reclaim your week.

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 an AI coding agent is writing or refactoring production code and its known failure modes need to be held in check — over-engineering, silent scope creep, invented APIs, claiming work is done without checking, deleting tests to make them pass. Trigger when the user asks for careful, production-grade, or reviewed code, or when a previous agent run produced confident output that turned out wrong.

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。

Applies anti-sycophancy checklist to override agreement bias. Use when analyzing contested claims or avoiding socially convenient but inaccurate conclusions.

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。

Enforces validation and evidence before claiming work complete. Use before declaring implementation done, creating a PR, or submitting deliverables for review.

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。

Enforce evidence bar, coverage gates, and regression guards. Use when adding tests or claiming done. Do not use to run suites; use night-market-operations.

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 drafting a grant or challenge proposal for a radiology or medical AI project, including a Korean government industry-academia plan. Structures significance, innovation, approach, aims, milestones and consortium roles, keeping claims evidence-based and executable.

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。

HTTP request smuggling / desync hunting - CL.TE, TE.CL, TE.TE, CL.0, and HTTP/2 downgrade. Timing-based detection, differential confirmation, no-blind-claims. Wiki-first, FIND schema output.

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。

Check agent-produced plans, tests, or code against the owner's actual intent. Find missing meaning, unrequested work, stale truth, unreachable decisions, unsupported completion claims, and implementation debt. Use before approval or merge.

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 a developer value proposition that is specific, provable, and free of puffery. Use when the messaging leans on "powerful," "better," "seamless," or "best-in-class," when claims have no proof, or when the same line is supposed to reach both the developer and the buyer.

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。