「fid」の検索結果

Expert SOC 2 compliance assistant covering all five Trust Services Criteria (Security/CC, Availability/A, Confidentiality/C, Processing Integrity/PI, Privacy/P). Use this skill whenever a user mentions SOC 2, Trust Services Criteria, SOC 2 Type 1 or Type 2, audit readiness, compliance gaps, control documentation, evidence collection, vendor risk questionnaires, or anything related to AICPA service organization controls. Trigger even for adjacent topics like "we need to get audited", "a customer asked for our security report", "writing an information security policy", or "preparing for an audit". Covers gap analysis, policy writing, control documentation, audit evidence preparation, and vendor risk reviews for organizations at any maturity level — from first-time startups to seasoned compliance teams.

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。

Reviews or drafts the agreement that pays an employee to settle their claims — and flags the statutory conditions that decide whether it actually binds them. Works under s.203 ERA 1996 for England & Wales. Flags apparent s.203 condition gaps for a solicitor to confirm (writing, specific complaints, independent adviser, identification, insurance, statement of conditions), drafts the substantive terms (sum, tax characterisation, confidentiality, references, restrictive covenants, indemnities), and surfaces enforceability risks. Does not rule on validity and is not legal advice. Use when the user says 'review this settlement agreement', 'draft a settlement agreement', 'compromise agreement' (old term), or asks whether an agreement is binding.

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。

No Inference / Source-Locked Verification. Forces Claude to answer ONLY from user-provided materials and/or online sources actually accessed — no inference, no assumptions, no gap-filling. Every factual, legal, numerical, or procedural claim must be anchored to a cited source. Use whenever Claude reviews documents, summarises evidence, checks accuracy, drafts submissions, creates timelines, extracts facts, checks citations, analyses rules, prepares legal arguments, compares documents, verifies claims, produces chronologies, works from uploaded materials, performs legal research, checks case status, or does anything where evidential fidelity matters. Also trigger on: 'source-locked', 'no inference', 'only from the materials', 'don't assume', 'stick to the evidence', 'verify this', 'check this is right', 'work from the documents'. Overrides Claude's default tendency to fill gaps. If evidential accuracy matters, use this skill.

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。

Expert New Zealand Information Security Manual (NZISM) advisor for NZ government agencies and their supply chains. Use for NZISM control guidance, gap analysis, agency security obligations, classification framework (Unclassified through Top Secret), security risk management, system certification, and GCSB/NCSC NZ compliance. Triggers on: NZISM controls, NZ government security, GCSB compliance, agency cybersecurity obligations, NZ classification markings, Restricted/Confidential/Secret system scoping, agency security policies, third-party supplier security, Certification and Accreditation (C&A), and any question about NZ government information security requirements or the NZISM framework.

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。

Draft GDPR/DSGVO-compliant privacy notices as .docx for any EU/EEA jurisdiction and audience. Use when user asks to create a privacy policy/notice, mentions "Datenschutzerklärung", "politique de confidentialité", "privacy notice", needs Art. 13/14 disclosures, AI Act transparency, cookie policy, or notices for applicants ("Bewerber-Datenschutz"), employees ("Beschäftigten-Datenschutz"), B2B partners, or B2C customers. Covers DE (DSGVO+BDSG+TDDDG), FR (RGPD+LIL+LCEN), AT, IT, ES, NL, BE, IE, UK GDPR. Five notice types: Website/App, Applicant, Employee, Business Partner, B2C Customer.

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。

Assesses a legal argument, submission, or piece of structured reasoning from the perspective of a judge reading it cold under time pressure. Produces a structured seven-part assessment: what the case appears to be about, immediate points of confusion, what feels strong, what feels weak, what is assumed but unproved, a provisional confidence level (low/medium/high), and what would be needed to persuade. The skill does not rewrite, improve, or attack the argument — it tells you how it actually lands on a sceptical, experienced reader with no prior context. Works on skeleton arguments, witness statements, letters before action, position statements, academic articles, and non-legal structured reasoning.

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。

Builds a high-fidelity interactive legal assessment as a single self-contained HTML artifact. Output includes a live countdown timer, contract review tasks with hover-annotated problem clauses, candidate answer textareas, model answers hidden behind reveal blocks, scenario-based legal memo tasks, strategy and function-building questions, and a pre-submission checklist that encodes the marking criteria. Use when the user needs to (1) assess a legal candidate with a realistic timed exercise, (2) train or onboard junior lawyers using problem sets rather than doctrine, (3) help a candidate prepare for a real take-home assessment they are facing, (4) build educational materials for law students, in-house teams, or compliance training, or (5) produce scenario-based training modules on specific legal topics. Triggers on "legal test", "take-home", "mock exam", "contract redline exercise", "candidate assessment", "legal training exercise", "practice test", or similar phrasing even when informal.

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。

Audits legal AI outputs, prompts, skills, workflows and MCP/tool instructions for fluent but unsupported reasoning, missing evidence, overconfidence, hidden assumptions, weak causal links and absent human-review gates.

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。

Claude skill that turns Claude into a Connecticut-specific divorce planner — nine operating modes from pre-flight intake to post-judgment modification, modeled on Untangle.us's feature surface and grounded in C.G.S. Title 46b, Practice Book Chapter 25, and the 2026-08-01 CCSG schedule. Covers eligibility triage (nonadversarial under § 46b-44a vs standard), financial affidavit (JD-FM-6), child support (JD-FM-220 / CCSG-1 / 1A), alimony (§ 46b-82 fourteen factors), parenting plan (with GAL/AMC escalation under JD-FM-224), settlement agreement (JD-FM-172, TCJA-aware), filing packet (marshal 12-day rule, $360 + $50 fees, JD-FM-75 waiver), and post-judgment motion practice. Hard UPL gate: refuses non-CT, domestic violence (refers CTCADV 1-888-774-2900), hidden assets, courtroom advocacy. Heppner-aware: AI prompts are not privileged. First family-law skill in the Lawvable registry.

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。

Méthodologie « verification-first » pour la Cour Pénale Spéciale de Centrafrique (cour hybride, siège à Bangui). Toute citation est vérifiée (JusticeInfo, FIDH, HRW, legal-tools.org ; les sites officiels renvoient souvent une erreur 403). Couvre l'affaire Paoua, le « notamment » de l'article 3, et la complémentarité avec la CPI. Aide à la recherche, pas un conseil juridique. Fait partie de la bibliothèque open source « Skills for International Justice » — méthodologie : github.com/jeannesulzer/international-criminal-tribunals-skills

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。

Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.

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。

Before any explanation or answer, require the learner to produce a free-recall attempt and confidence rating. Use when a student wants help understanding or reviewing a topic — this skill ensures the AI works from what the learner already knows.

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 a Funhouse Mirror activity where students use their own domain expertise to detect AI distortions, omissions, and overconfidence. Use when students know a subject well enough to evaluate AI claims about it.

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 metacognitive checkpoints that prevent AI-assisted learning from bypassing genuine understanding. Use when students use AI tools and may overestimate their own comprehension.

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 auditing or recalibrating game balance: build a source-driven Monte Carlo balance lab (Rust + rayon) that extracts live game data, simulates human playstyles (AFK→pro), emits win-rate/economy verdicts with confidence intervals, and bruteforce-tunes parameters. Trigger on unfair levels, unreachable shops, farm exploits, interest-curve cliffs, post-content recalibration, or CI balance JSON diffs. Keywords: balance lab, Monte Carlo, win rate, difficulty curve, economy career, playstyle simulation, Resource extraction, GDScript parser, bruteforce tuning.

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。

Expert patterns for scaling mobile games to desktop including mouse/keyboard controls, increased resolution and graphical fidelity, expanded UI layouts, settings menus, window management, and platform-specific features. Use when creating desktop ports or cross-platform releases. Trigger keywords: mouse_controls, keyboard_shortcuts, resolution_scaling, graphics_settings, fullscreen_toggle, window_modes, Steam_integration, desktop_optimization.

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。

Delegate work to the TaskMarket agent-worker market - browse open tasks, create tasks with explicit authorization, and track/submit work, so an agent can outsource instead of burning inference on unreliable or low-confidence work.

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。

Cross-skill signal detector - finds entities or themes surfaced independently by 3+ different skill categories within 48h and surfaces them as high-confidence write opportunities

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。

Framework for running single-variable cold email experiments. Defines experiment types (list-only, copy-only, combined), confidence weighting, minimum sample sizes, and success criteria. Use when the user wants to improve a campaign, test a new list vs old one, or compare copy variants. Prevents the

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。

Detect and interrupt the pattern where an agent confidently praises work it just produced instead of reviewing it critically. Same-context grading is not review — it's rationalization.

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。

Prints a greeting with unnecessary confidence.

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。

7-section readiness scorecard for a LOCAL repo. Reports repo type + agent topology + MCP risk + test confidence + release readiness + recommended harness plan + scorecard. Exit 0 ready, 1 needs-work, 2 blocked. --json for the 6-field scorecard, --bundle for the ADR-031 schema-1 envelope.

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。

Active credit card transfer bonuses from Amex, Chase, Capital One, Citi, Bilt, and Rove. Weekly-refreshed data with confidence markers. Use when pricing an award booking that involves a points transfer or deciding whether to wait for a better bonus.

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 working on inclusion, i18n/localization, global name/address forms, low-end devices, slow/metered networks, affordability, or first-time/low-confidence users; not WCAG/screen readers (see accessibility).

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。