「claim」の検索結果

Design, preview, implement, and assess mini-program interfaces against an approved prototype, screenshot, visual reference, design system, or bounded UI request while preserving product semantics and existing accepted behavior. Use when users ask to reproduce a mini-program screen, refine visual hierarchy, adapt layouts across device sizes, handle safe areas or keyboards, inspect touch targets, scrolling, media, or gesture conflicts, compare an implementation with a reference, or prepare a device-verification matrix. Separates proposed visual previews, user approval, source integration, local checks, and real-device evidence; never invents product functionality for visual completeness or claims device validation without device-specific proof.

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 WeChat Mini Program platform constraints and evidence layers for an idea or existing repository, including source configuration, build output, WeChat DevTools loading, device behavior, permissions, privacy declarations, cloud or backend linkage, upload, trial, review, and production status. Use when users ask about WeChat-specific configuration, project roots, compile paths, capability permissions, privacy compliance, official platform rules, upload or release readiness, or why source and platform behavior differ. Performs read-only evidence classification by default, verifies time-sensitive or high-risk claims against current official WeChat sources, redacts identifiers and secrets, and never upgrades one evidence layer into another.

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 mini-program implementations and fixes with risk-calibrated evidence across static checks, unit tests, integration tests, state matrices, simulators, real devices, cloud environments, and release artifacts. Use when users ask to test, validate, accept, regression-check, quality-check, confirm readiness, or determine whether a mini-program feature is actually complete. Binds results to a source and build fingerprint, records commands and observable evidence, separates passed, failed, blocked, and not-run layers, prioritizes the next highest-information check, and never converts local success into device, cloud, release, or formal acceptance 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。

Perform a read-only, evidence-first intake of an existing mini-program repository before planning or modifying code. Use when users ask to take over, understand, audit, resume, scope, or continue a WeChat or other mini-program project; when project facts may conflict with historical documents; or when an agent needs the framework, rules, Git state, build path, risks, unknowns, protected behavior, and change boundary. Produces a project fact map and handoff without changing code, installing dependencies, building artifacts, or claiming runtime, device, cloud, upload, acceptance, or release status.

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, revise, audit, or rebut a research manuscript from Harness Research evidence. Use for paper intake, related-work research, claim and citation control, section architecture, LaTeX patching, figure planning, reviewer response, or final manuscript hardening when the workspace contains Harness research artifacts.

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 the user wants a cited, structured read of local documents and project knowledge. Triggers on: "analyze these docs", "scan my project for context", "read the docs folder", "summarize what's in .beagle/concepts/", "extract context from docs/", "what's in this folder", "go read everything in X and tell me what's there". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups ("find this function", "search the repo"), web research (use web-research), LLM-as-judge evaluation (use llm-judge), or document editing (use humanize-beagle). Produces a written scan plan, parallel-subagent findings, and a cited synthesis report on disk — never inline prose, never unsourced 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。

Use when the user wants web research: gathering cited, multi-angle evidence on a specific question. Triggers on: "research X for me", "do web research on", "look up sources for", "find citations for", "gather evidence on", "what does the web say about X". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups ("find this function", "search the repo"), local file search, LLM-as-judge evaluation, or paywalled/auth-gated scraping. Produces a written plan, parallel-subagent findings, and a cited synthesis report on disk — never inline prose, never unsourced 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。

Process external code review feedback with technical rigor. Use when receiving feedback from another LLM, human reviewer, or CI tool. Verifies claims before implementing, tracks 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。

Test kolu's remote-host features (multi-host / padi-remote) in a real browser against a real remote box — the ONLY full end-to-end harness for this surface (real ssh provision, no mock). Covers the isolated nix-run invocation (or just dev, which bakes the same agent source), ssh- provisioning a real remote box without touching production or another user's box, the chrome-devtools drive sequence for host-switch / split / code-browser / per-host-canvas, PID-exact teardown, and the reproduce- first rule for any bug the feature surfaces. Triggers on "test remote hosts", "test multi-host", "test padi-remote", "verify the host switch", "browser-test a remote host change", or before claiming a remote-host fix 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 an implementation against its plan with a hostile peer agent, debate findings to consensus, and drive fix waves until the auditor runs dry. Use when a done-claim needs verification the implementer cannot game ("hostile review", "adversarial audit", "is this PR faithful", "find the escape hatches") — the loop that beats the laziness bias with its own game theory.

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 essays, articles, and blog posts in Paul Graham's voice — plain, spoken prose that reasons out loud and lands surprising true claims, not AI filler. Use when asked to write or rewrite something "like Paul Graham", "in PG's style", or to make a piece read like a person thinking on the page rather than generated text. Built from a stylistic model of 18 of his essays (see SOURCES.md).

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 truthful state of workflow contracts from git, gh, worktrees, and transient launch claims; offer archive, resume, reconciliation, or wf-run actions.

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。

Retirement projection with Monte Carlo simulation logic. Calculates required nest egg via 4% rule and 25x expenses, projected vs needed gap, contribution recommendations, asset allocation by age, Social Security claim optimization, healthcare cost projections, and withdrawal sequence planning. Use when the user says "/finance retirement", "am I on track for retirement", "how much do I need to retire", "Social Security timing", or any retirement question.

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。

Quellenbasierte Profile einzelner Wettbewerber aus öffentlichen Informationen erstellen. Nutze diesen Skill, wenn Positionierung, Zielgruppe, Produkt, Preise, Organisation und Belegbehauptungen eines Anbieters zusammengetragen werden sollen, als Kurzbrief, fokussiertes Profil oder vertiefte Recherche. Trennt Tatsache, Anbieterangabe, Schätzung und Hypothese in einem Claim-Ledger, hält Quellen mit Datum fest und beachtet Datenschutz, Datenbankrechte, Urheberrecht und Geschäftsgeheimnisse. Kein Scraping über das Freigegebene hinaus, keine Personendossiers. Für vergleichende Seiten: competitors.

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 the reasoning of a document or argument (memo, proposal, investment analysis, board paper, article, the user's own draft): claims, evidence, unstated assumptions, logical gaps, fallacies, and what would falsify it, each anchored to quoted text. Use whenever the user wants reasoning examined, in any language ("audit this argument", "is this analysis sound", "poke holes in this proposal", "review the logic of my draft"; Vietnamese "phản biện giúp tôi", "soi lập luận này", "tài liệu này có lỗ hổng gì", "góp ý bản nháp của tôi"), even when they never say "critical thinking". Also use when the user drops a document and asks whether to trust or act on it, or asks to see their reasoning profile. Not for company-level strategic bets (strategy-board) or learning a topic through dialogue (socratic-questor).

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。

ウェアラブルやドライブレコーダーのデータから個人のリスクを瞬時に算定し、保険料の決定と支払いを自動化するスキル。

Ensures correct tariff, package, insurance, co-pay, discount, tax & claim logic in HIMS billing module.

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。

Retrieves and analyzes FHIR Coverage and Organization resources to produce a structured insurance summary with coordination of benefits analysis. Use when user asks to "check insurance", "coverage details", "verify coverage", "insurance summary", "what plan is the patient on", "primary vs secondary insurance", or "coverage status". Do NOT use for clinical data, demographics beyond insurance, or billing claim submission.

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 demo: Generate pseudo-labels from a strong teacher model, build a cheap student function, and evaluate accuracy. Showcases pseudo-labeling and teacher-student distillation.

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。

Licensed insurance agent with 10+ years specializing in personal and commercial insurance. Conducts needs analysis, compares policies, advises on coverage, and advocates for clients during claims. Use when: insurance-agent, buy-life-insurance, umbrella-policy, coverage-gap-analysis, auto-insurance-quote, homeowners-insurance, business-insurance, term-vs-whole-life.

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。

保险方案顾问。险种推荐、产品对比、保费计算、理赔指南、定期寿险、健康险方案。Insurance advisor with recommendation, comparison, premium calculation, claim guide, term life, health insurance. Use when you need insurance advisor capabilities. Triggers on: insurance advisor.

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。

Load this skill when the user asks specific insurance education questions in the Indian context, such as term vs endowment vs ULIP, riders, claim settlement process, nominee concepts, or policy jargon; do not load for generic budgeting or emergency fund 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。

Health insurance planning for Indian families — Section 80D optimization, family floater vs individual, super top-up strategy, parents' coverage, critical illness, corporate cover limitations, and IRDAI portability. Triggers on 'health insurance', '80D', 'mediclaim', 'family floater', 'super top-up', 'health cover', 'parents health insurance', 'medical insurance', or 'health insurance for family'.

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。

当用户需要识别保险理赔案件是否属于高风险案件、分析案件中有哪些重点风险信号、判断是否存在高赔付高争议高投诉高时效高复杂度或高欺诈风险、输出高风险案件预警报告或为理赔审核、复核、调查和管理提供重点案件筛查支持时使用本 skill。适用于分析保单信息、理赔申请信息、案件事实、医疗材料、事故材料、历史行为、处理记录、沟通备注、投诉工单、调查线索、风险规则、预警标签和历史风险库信息，并形成结构化风险等级、触发依据、待核实事项和处置建议。

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。