709 件 ・ 関連度順
概要と使いどころ
/cs:aims-audit <scope> — ISO/IEC 42001 AIMS internal-audit 6-question forcing interrogation. Use before certification stage 1, before annual internal audit cycles, or when onboarding a new AI system into an existing AIMS.
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 asks to "check our positioning against what we can actually ship", "trace which differentiators we can defend", or "reconcile the positioning canvas with the claims ledger"; reconciles the reused positioning canvas against the shippable stage and the claims ledger to produce a differentiation truth set — every differentiating claim verifiable or marked '[needs source]' — that TALE-T1 is judged against. Not for building the canvas — use positioning-mapper; not for adjudicating claims — use offer-claims-registry; not for authoring the message house — use message-system-architect. 定位真相/差异化校准/可交付现实/主张核对
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 asks to "package our proof points", "build reusable stat cards and case snippets", or "put proof where each pillar makes its claim"; turns claims-ledger-approved proofs into reusable proof modules — stat cards, case snippets, testimonial blocks, comparison proofs — each pinned to a message-house pillar and the ledger claim ID it substantiates, and flags any pillar making a claim with no approved proof behind it. Never adjudicates a proof: unverified or ledger-absent proofs are marked '[needs source]' and routed to the claims candidates. Not for adjudicating or substantiating claims — use offer-claims-registry; not for fabricating a benchmark to fill a gap — a missing proof is flagged, not invented; not for scoring narrative quality — use narrative-quality-auditor. 证据模块/证据卡/客户案例/主张对齐
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。
Systematic claim-by-claim verification for any content before it ships. Modeled on professional fact-checking desks (The New Yorker, ProPublica, IFCN standards): extract every verifiable claim, check each against live citable sources (never training data), assign a 6-level confidence status, apply corrections, and produce a scored pass/fail report. Includes a data-derived-claims gate for outputs produced FROM the brain or a database: PRODUCER ≠ VERIFIER (re-derive each claim via a different query path) and AFFILIATION ≠ AUTHORSHIP (person→thing claims resolve through typed edges), with delivery hard-blocked on unsupported 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。
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。
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。
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。
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。
Improve the clarity and voice of AI-assisted academic writing (papers, theses, rebuttals) and funding proposals (NSF Project Summary/Description, NIH Specific Aims): preserve scholarly conventions, match claims to evidence (and, for proposals, claims to feasibility), and match the author's own voice. It never changes a number, result, or citation, and it is not for evading AI-use disclosure. Use when editing AI-assisted academic prose or grant proposals.
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。
Designs primary aims, secondary aims, and testable hypotheses from broad biomedical research ideas. Use this skill when a user needs to convert a loose study idea into a tighter protocol-framing structure with clear aim hierarchy, hypothesis discipline, and separation between hypothesis-driven and exploratory components. Always keep aims answerable, non-overlapping, and aligned to the intended evidence type and study scope.
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。
ISO 42001 AI Management System (AIMS) compliance. Use for ISO 42001 readiness assessments, AI governance planning, AI impact assessments, Annex A control validation, responsible AI implementation, and AIMS certification preparation.
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。
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。
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。
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。
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。
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。
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。
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。
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。
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。
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。
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。
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。
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。