「claims」の検索結果

Comprehensive investigation of complex multi-domain narratives (technology, theology, policy, finance). Systematically decouples factual claims from speculation through iterative verification, multi-source comparison, and contradiction resolution. Use for investigations requiring institutional knowledge, historical context, and handling of conflicting incentives.

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 and launch a landing page: confirmed copy without invented claims, a generated page in your brand tokens, UI and SEO review, deploy only after GO, then a check on the live URL. Use for "landing page", "launch page for this product", "ship a one-pager".

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。

Initialize, update, and visualize codebase or personal knowledge wikis using LangChain OpenWiki. Enforces OKF v0.2, Grounded Claims, interactive visualizer graph, and MCP page-job lifecycle.

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。

Stress-tests ideas by surfacing assumptions, counterarguments, and confidence gaps. Use when evaluating claims, proposals, plans, or decisions that need rigorous intellectual scrutiny.

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。

Debug and troubleshoot WorkOS AuthKit authentication issues with Convex. Use when authentication fails, JWT validation errors occur, user identity returns null, email claims are missing, admin access checks fail, or sign in button does not work. Supports Netlify deployment.

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。

Run a project's GitHub Issues through Orca Workers from a coordinating session in the project's Hub folder. The Orchestrator reads Issues, claims one, dispatches an Orca Task into a fresh worktree of the target repo, supervises until worker_done, and writes the outcome back to the Issue — it never edits code itself. Use when the user says "take

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。

Plan, verify, and track demo/marketing video production in Busabase — idea to hook/pain-point/storyboard, codebase claim verification, recording progress, post-production handoff, and HyperFrame (Remotion) linkage. Use when the user invokes $kelly-demo-video-factory or /kelly-demo-video-factory, wants to plan a product demo video, write a storyboard, verify a video script's product claims against the codebase, track which shots are recorded, or hand a finished storyboard off to editing/Remotion.

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。

Validates compliance, security, and GRC terminology in marketing copy. Enforces accurate claims, prevents common mistakes (e.g., calling SOC 2 a "certification"), and applies risk-first narrative framing for B2B SaaS audiences. Use when writing or reviewing any marketing content that references compliance frameworks, security standards, regulatory requirements, or audit processes. Also use when creating ads, landing pages, emails, case studies, or sales collateral for GRC/cybersecurity B2B SaaS products.

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。

Rewrite AI-sounding text so it reads like the writer without changing what it says. Use when editing or reviewing prose for AI tells: not-X-but-Y contrasts, one-line closers, staged openers, forced triads, dashes everywhere, inflated claims, sales language, stock AI words, bold labels, or filler. Based on Wikipedia's "Signs of AI writing."

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。

Validate CTO Build Framework governance artifacts and file version-bound evidence (runs, reviews, evidence packets) without inflating claims. Use for independent re-execution, internal-consistency reviews, and verdict filing.

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。

Grilling session that mines the user for fragments — heterogeneous nuggets of writing (claims, vignettes, sharp sentences, half-thoughts) — and appends them to a single document as raw material for a future article. Use when the user wants to develop ideas before imposing structure, or mentions "fragments", "ideate", or "raw material" for writing.

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。

Performs subgroup and heterogeneous treatment effect (HTE) analyses for clinical trials. Covers Mantel-Haenszel pooling, Breslow-Day, interaction tests in regression, RERI for additive interaction, modern data-adaptive HTE methods (STEPP, SIDES, causal forests, X/R-learners), Bayesian shrinkage (Dixon-Simon, MAP, EXNEX), graphical multiplicity (Bretz-Maurer), and credibility frameworks (Sun BMJ, EMA 2019). Use when analyzing treatment effects across patient subgroups for regulatory submissions or precision-medicine 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。

Assigns honest lipid annotation levels, designs class-based internal-standard quantification, and runs lipid-aware differential and enrichment analysis with lipidr, guarding against in-source-fragment phantoms, sn-position over-claims, and invalid cross-class quantification. Use when naming or canonicalizing lipid species (shorthand separators, Goslin), deciding shotgun vs RP vs HILIC LC-MS, picking internal standards (SPLASH/EquiSPLASH), interpreting MS-DIAL/LipidSearch output, or comparing lipid classes. For general feature detection see metabolomics/xcms-preprocessing and metabolomics/msdial-preprocessing; for non-lipid annotation confidence see metabolomics/metabolite-annotation; for normalization/QC see metabolomics/normalization-qc; for multivariate stats see metabolomics/statistical-analysis.

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。

Extract employee, trip, mileage, per diem, expense lines, VAT, and totals from German travel expense 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。

Extract employee, trip, expense lines, VAT, totals, and approvals from French expense 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。

Self-review, audit, or verify CS/AI/ML paper drafts as a critical peer reviewer. Three-round review (evidence→argument→style) with Verification Status and debt tracking. Use when: reviewing a paper draft before submission, checking evidence compliance of claims, simulating peer reviewer feedback, verifying citation closure and evidence debts, performing cross-section consistency checks. Triggers on: 审修, self review, 自查, verification, revise, 修订, check draft, 审稿, evidence compliance, peer review, 论文审查, draft audit, 验证论文, 检查引用, cross-section 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。

Configures JWT Bearer authentication for .NET APIs. Includes token generation, validation, refresh tokens, and user context extraction from 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 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。

Prepare for a Japanese job interview by working from the documents already submitted: find where an interviewer will dig in (claims the applicant cannot back up, work described in the first person plural, outcomes with no measure, gaps or overlaps in the employment history, must-have requirements the documents never answer), and turn them into questions to prepare evidence for. Use when a user has an interview scheduled and wants to know what will be asked and what to have ready, or wants to prepare reverse questions from earlier company research; do not use to predict whether they will pass, to write answers containing experience they did not report, or to schedule or contact anyone.

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。

Delimits putative species boundaries from molecular data within the de Queiroz 2007 unified-lineage framework using ASAP (Puillandre 2021 successor to ABGD), mPTP C++ (Kapli 2017 successor to bPTP; bPTP is Python NOT R), GMYC single/multi-threshold (Pons 2006; Fujisawa 2013), multilocus BPP v4 with prior calibration from data (NOT defaults; Yang 2015), SNAPP + BFD* for SNP delimitation, DELINEATE (Sukumaran 2021) speciation-process modeling to address Sukumaran & Knowles 2017 PNAS critique that MSC delimits structure not species, integrative-taxonomy congruence (Padial 2010; Carstens 2013), Dsuite for introgression testing before sister claims (Malinsky 2021), and Meyer & Paulay 2005 barcoding-gap-absence caveat. Use when delineating species from DNA barcoding data, resolving cryptic complexes, choosing among ASAP/mPTP/BPP/DELINEATE, calibrating BPP priors, distinguishing introgression from ILS, or applying the Sukumaran-Knowles oversplitting correction.

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。

Performs subgroup and heterogeneous treatment effect (HTE) analyses for clinical trials. Covers Mantel-Haenszel pooling, Breslow-Day, interaction tests in regression, RERI for additive interaction, modern data-adaptive HTE methods (STEPP, SIDES, causal forests, X/R-learners), Bayesian shrinkage (Dixon-Simon, MAP, EXNEX), graphical multiplicity (Bretz-Maurer), and credibility frameworks (Sun BMJ, EMA 2019). Use when analyzing treatment effects across patient subgroups for regulatory submissions or precision-medicine 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 configuring Spring Boot as an OAuth2 resource server, validating JWTs from an external auth provider (Keycloak, Auth0, Okta, Cognito), extracting claims, or implementing scope-based authorization.

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。