Review marketing copy for claims that need substantiation, reframing, or cutting. Use when the user says "review this marketing copy", "check these claims", "can we say this", "is this puffery or a problem", or pastes marketing content (landing pages, emails, ads, taglines).
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。
anthropics/claude-for-legal☆ 9,6562026年9月30日 更新
Examine what a file claims about itself and what it actually contains — powered by Apache Tika. True content-based type detection (extensions lie), provenance claims (authors, dates, creating application), revision and tamper signals (PDF incremental updates, tracked changes, hidden slides, zip integrity), hidden and embedded content (attachments, macros), risk indicators (PDF JavaScript actions, encryption), and content digests. Evidence gathering, not verdicts: Tika reports what the file asserts and what parsing observed; it does not attribute authorship or validate signatures. Use for triaging suspicious files, provenance questions, e-discovery-style review, or "is this file what it claims to be."
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。
apache/tika☆ 4,0932026年10月13日 更新
Adversarial verification of finished work. Treats any "done" as a set of claims, then re-runs the claimed verifications, diffs what actually changed, detects weakened tests and false completion claims, and delivers an evidence-based verdict (VERIFIED / VERIFIED WITH CAVEATS / REFUTED). Use after any agent or model claims work is complete - "/fable-judge", "judge this work", "verify what it did", "did that actually work?". Also runs the fable-method trap suite against a skill or model via "/fable-judge suite TARGET".
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。
Sahir619/fable-method☆ 2,3002026年10月3日 更新
Use when receiving code review feedback (especially if unclear or technically questionable), when completing tasks or major features requiring review before proceeding, or before making any completion/success claims. Covers three practices - receiving feedback with technical rigor over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before any status claims. Essential for subagent-driven development, pull requests, and preventing false 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。
mrgoonie/claudekit-skills☆ 2,2282026年4月3日 更新
Post-hoc verification and trust audit of AI-generated factual and interpretive claims. Classifies claims by type and salience, routes them to domain-appropriate sources, scores trustworthiness on a tiered scale with an Interpolated verdict for plausible-but-unsupported detail, and assesses rhetorical fairness on interpretive claims. Designed for clinical-negligence and healthcare-law practice in England and Wales, with general applicability beyond.
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。
lawve-ai/awesome-legal-skills☆ 8632026年10月3日 更新
Screen a Medicare/Medicaid claims corpus for fraud, waste, and abuse and produce ranked, fully-cited investigation referrals for an SIU / program-integrity team. Use when asked to run a fraud sweep, screen claims for FWA, find billing anomalies, or generate investigation referrals over a claims dataset.
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。
anthropics/healthcare☆ 4252026年8月27日 更新
Use when receiving code review feedback (especially if unclear or technically questionable), when completing tasks or major features requiring review before proceeding, or before making any completion/success claims. Covers three practices - receiving feedback with technical rigor over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before any status claims. Essential for subagent-driven development, pull requests, and preventing false 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。
unclecatvn/agent-skills☆ 1452026年9月24日 更新
Design claims advocacy programs. TRIGGERS - Use when user needs help with insurance-claims-advocacy related tasks.
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。
FDU-INS/Insurance-Skills☆ 762026年7月12日 更新
Claim value trending and replacement cost tracking. Triggers: "claim value trending", "replacement cost tracking", "vehicle depreciation for claims", "residual value for insurance", "how fast is the insured vehicle losing value", "pre-loss value trajectory", "depreciation rate for settlement", "value retention for claims", "depreciation curve for total loss", "diminished value over time", "claim reserve adjustment", "portfolio depreciation exposure", "fleet depreciation risk", tracking vehicle depreciation for insurance claims valuation, replacement cost estimation, settlement trending, or reserve adequacy assessment.
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。
FDU-INS/Insurance-Skills☆ 762026年7月12日 更新
Design claims handling workflows with documentation and timelines. TRIGGERS - Use when user needs help with claims-handler related tasks.
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。
FDU-INS/Insurance-Skills☆ 762026年7月12日 更新
Use when users ask about Nexus Mutual claims history, claim statistics, approval/denial rates, payout amounts, or want to analyze past claims for a product or time period.
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。
FDU-INS/Insurance-Skills☆ 762026年7月12日 更新
Design claims management systems with workflows. TRIGGERS - Use when user needs help with claims-management related tasks.
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。
FDU-INS/Insurance-Skills☆ 762026年7月12日 更新
Write claims denial appeal letters with documentation. TRIGGERS - Use when user needs help with claims-denial-appeal related tasks.
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。
FDU-INS/Insurance-Skills☆ 762026年7月12日 更新
Claims Appeals agent for healthcare workflows.
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。
FDU-INS/Insurance-Skills☆ 762026年7月12日 更新
Verify multiple factual claims in backlog items, skill documentation, or plugin content. Extracts discrete claims, delegates each to the canonical factual-verification process, and aggregates VERIFIED/REFUTED/INCONCLUSIVE results. Use for "fact check", "verify claims", or a set of unverified factual assertions.
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。
Jamie-BitFlight/claude_skills☆ 672026年10月12日 更新
Maintain request-time claims enrichment, its public backend and parser APIs, gatekeeper and validator hooks, and the static claims-enrichment plugin. Excludes portal issuance-time transforms and token signing.
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。
greenpau/go-authcrunch☆ 602026年10月11日 更新
Evaluates make-whole premium claims in bankruptcy with contract interpretation, present value disputes, and secured status analysis. Use when analyzing make-whole claims, evaluating redemption disputes, or assessing premium recovery.
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。
CaseMark/skills☆ 442026年9月9日 更新
Evaluates claims trading market with trading levels, holder identification, and blocking position analysis. Use when analyzing claims markets, tracking distressed debt trading, or evaluating ad hoc group dynamics.
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。
CaseMark/skills☆ 442026年9月9日 更新
Use when receiving code review feedback (especially if unclear or technically questionable), when completing tasks or major features requiring review before proceeding, or before making any completion/success claims. Covers three practices - receiving feedback with technical rigor over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before any status claims. Essential for subagent-driven development, pull requests, and preventing false 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。
VoDaiLocz/kilo-kit-mcp☆ 272026年9月13日 更新
Use when designing or customizing industry-specific guided processes in Salesforce Industries clouds: insurance claims lifecycle (FNOL through closure), telecom order management decomposition, and utility service request workflows. Trigger keywords: FNOL process design, claims OmniScript customization, Industries order decomposition workflow, utility service order design, insurance claim lifecycle stages, telecom commercial-to-technical order flow. NOT for the Industries object model — use architect/industries-data-model. NOT for Insurance Cloud licensing and policy architecture — use architect/insurance-cloud-architecture.
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。
PranavNagrecha/AwesomeSalesforceSkills☆ 192026年10月4日 更新
Use when adversarially reviewing a document that makes formal or technical claims — math derivations, physics papers, statistical analyses, benchmark reports, whitepapers. Inventories every equation and quantitative claim, verifies each AS NAMED in the text (never a paraphrase or a neighboring statement), and classifies VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS. Triggers on "check this paper", "verify these claims", "is this derivation right", "review this proof", "audit this benchmark", "does the math hold up". For source-code review see code-review-and-quality; for skill/agent library audits see skill-library-review; for content quality scoring see content-ops.
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。
LazyIsEfficient/agentic-os☆ 172026年7月17日 更新
Deep analysis of competitor patent claims: element decomposition, scope interpretation, equivalents prediction, prosecution history estoppel analysis. Automatically converts PDF/DOCX/DOC patent files to structured Markdown via patent-pdf-to-md skill before analysis. Invoke when user asks to analyze/parse competitor patent claims, decompose claim elements, assess claim scope, or perform 权利要求解析/要素分解/保护范围解读. 竞品专利权利要求深度解析:要素分解、保护范围解读、等同范围预判、审查历史限制分析。自动调用patent-pdf-to-md技能将PDF/DOCX/DOC专利文件转换为结构化Markdown后再进行分析。当用户要求解析竞品专利权利要求、要素分解、保护范围时触发。
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。
CSlawyer1985/legal-skillhub☆ 152026年9月23日 更新
Validate trained models and analytical claims against their intended decision, independent evidence, and human-reviewed ground truth. Use when reviewing model performance, analysis conclusions, launch claims, or evaluation reports; use failure diagnosis instead when the main task is locating a known defect.
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。
aiopshwang/data-analysis-ml-agent-skills☆ 122026年8月27日 更新
Produces and audits externally published marketing copy where factual claims must survive scrutiny — landing pages, product pages, launch emails, one-pagers, search/social metadata. Every statistic, competitor comparison, capability description, and proof point is traced to a fetched source or the project's own documents, labeled, and adversarially verified before it ships. Use when writing or rewriting high-stakes marketing copy; when copy must pass legal, compliance, brand, or claims review; when the audience is skeptical technical or executive buyers; when the company has little or no customer proof yet (pre-launch, zero customers); or when auditing existing copy for unsupported claims, invented capabilities, unverified statistics, or AI-slop 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。
arome3/evidence-based-copywriting☆ 52026年8月13日 更新