「ipa」の検索結果

Create a new package in the One Page monorepo with the required LICENSE symlink, README, and workspace registration. Use when adding a new core or feature package.

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 the project's verification harness (analyze, lint, format, tests) after code changes. Use after editing Dart code to verify the change before declaring it complete.

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。

Your AI compliance officer. Guides startups and scale-ups through SOC 2, ISO 27001, GDPR, HIPAA, and PCI DSS — from zero to audit-ready. No consultants needed.

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 fair, transparent raffles and sweepstakes. Randomly select winners from participant lists with verification and documentation for credibility.

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。

Map Azure architectures and operations to security and compliance controls. Use this skill when users ask for governance, policy enforcement, audit readiness, or regulatory alignment. Covers ISO, SOC2, HIPAA, PCI-DSS, and custom compliance frameworks.

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。

Product Discovery through an 18-task methodology in 6 blocks — from market analysis to an investor-ready financial plan. Use when someone wants to run Product Discovery, validate a startup, assess a market hypothesis, prepare for an investment round, or raises an adjacent topic — idea validation, niche sizing, competitor teardown, product-market fit, pitch preparation, startup unit economics, geographic expansion into a new country, go-to-market for SEA / Asia / MENA. People rarely name PD explicitly; they say 'is there a market for this', 'assess my idea', 'I need a deck for an angel', 'we are entering Thailand/Singapore/UAE, how do we size it'. Use the skill in those cases too. Three modes: Light (~45 min, idea stage), Full (~2-3 h, MVP with customers), Geographic Expansion (~2 h, product entering a new geography). Produces 3-4 artifacts in /mnt/user-data/outputs/: one-pager.pptx, financial-plan.xlsx, presentation.pptx, optionally interview-guide.docx.

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Auto-activate for litestar_security, SecurityPlugin, SecurityConfig, SecureController, CurrentUser, Principal, SecurityContext, or requires_role/scope/tenant/capability/assurance. Not for basic Litestar Guards.

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Define la identidad visual de un producto — propone dos o tres direcciones de color y tipografía justificadas por lo que el producto es, las escribe en design/tokens.css y las deja listas para verlas aplicadas en preview.html antes de decidir. Úsalo tras definir el producto y ANTES de prototipar (p. ej. "define la identidad", "qué paleta usamos", "elige los colores del producto"). No construye vistas.

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Genera las vistas estáticas navegables del producto (landing, auth, app, legales, errores y las propias del mapa de pantallas) usando el design system de design/, sin lógica de backend. Úsalo en el paso "prototipar" del sprint de definición o cuando haya que maquetar vistas nuevas (p. ej. "haz el prototipo", "maqueta las vistas", "crea la landing estática").

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。

Drafts a Bring Your Own Device (BYOD) policy for U.S. employers governing personal device access to company systems. Covers MDM enrollment, encryption, remote wipe authority, privacy expectations, data classification, and regulatory overlays (HIPAA, GLBA, SOX, GDPR). Use when creating or updating BYOD policies, mobile device security policies, or personal device programs.

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Drafts legally compliant data breach notification letters to affected consumers under multi-state and federal statutes (HIPAA, GLBA, state AG requirements). Use when drafting breach notices, security incident consumer notifications, or data compromise letters.

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Summarizes cybersecurity breach incidents into structured legal and compliance records. Trigger when synthesizing incident reports, forensics, logs, or notifications into a defensible chronology, scope-impact analysis, response ledger, or regulatory-risk assessment. Keywords: data breach, incident response, unauthorized access, ransomware, exfiltration, GDPR, CCPA, HIPAA.

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。

Drafts a defendant's Answer with Invalidity Contentions responding to a U.S. patent infringement complaint. Covers FRCP 8(b) admissions/denials, affirmative defenses, and PLR 3-3 invalidity contentions with claim charts under 35 U.S.C. §§ 101, 102, 103, 112. Use when representing a defendant in the pleadings phase of federal patent litigation who must respond to an infringement suit and assert prior art, anticipation, obviousness, or § 112 defenses.

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Italian geographic and property data through Openapi - geocoding/reverse geocoding, zip codes (CAP), municipalities/provinces/regions with ISTAT codes, Italian cadastre (catasto) property and owner lookups, visure catastali/ipotecarie, real estate valuations.

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Call this skill when faced with "wicked problems", complex challenges, or when a user asks for strategic innovation, root-cause analysis, or long-term problem solving. Do not use for simple, linear tasks. This skill forces the agent to bypass superficial symptoms, map the entire ecosystem, and anticipate second-order consequences before proposing an intervention.

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。

Conversation patterns and interaction protocols for multi-agent systems. Covers request/response, pub/sub, blackboard, delegation chains, debate, critique, consensus, fan-out/fan-in, supervisor-worker, and peer negotiation. Deep analysis of AutoGen conversation patterns, CrewAI delegation, LangGraph state passing, and FIPA-ACL performatives. Teaches how to design what agents say to each other and in what order. Activate on: "agent conversation", "agent protocol", "multi-agent debate", "agent delegation", "supervisor worker pattern", "agent voting", "consensus protocol", "fan-out fan-in", "agent negotiation", "blackboard pattern", "agent dialogue", "conversation topology", "agent handoff". NOT for: wire format or serialization (use agent-interchange-formats), orchestration infrastructure (use agentic-infrastructure-2026), single agent behavior (use agentic-patterns).

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。

Cryptographic security for agentic systems — zero-trust agent networking, signed message envelopes (JWS/JWE), capability-based security (ocaps), Merkle tree audit trails, WASM sandboxing, and formal verification. Covers CLI dev tool security, mTLS between agents, permission boundaries (least privilege for AI agents), and supply chain security for skills/plugins. Activate on: "agent security", "zero trust agents", "secure agent communication", "capability-based security", "ocap", "signed messages between agents", "agent audit trail", "sandbox agent execution", "agent permissions", "mTLS agents", "cryptographic verification", "agent supply chain", "OWASP agentic", "prove agent did X", "tamper-proof agent logs". NOT for: application-level SAST scanning (use security-auditor), network firewall rules (use infrastructure), SOC2/HIPAA compliance (organizational), or prompt injection defense (use prompt-engineer).

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。

Safety, privacy, cost management, and frank advice for building always-on AI agents with episodic memory. Covers data hygiene, privacy risk surfaces, runaway cost prevention, scope creep, psychological effects of persistent AI companions, and responsible deployment patterns. This is the skill that tells you what can go wrong and how to prevent it. Activate on: "agent safety", "always-on agent privacy", "agent cost control", "persistent agent risks", "AI companion safety", "agent data hygiene", "runaway agent costs", "parasocial AI risk", "/always-on-agent-safety". NOT for: architecture design (use always-on-agent-architecture), input design (use always-on-agent-inputs), application brainstorming (use always-on-agent-applications), healthcare compliance specifically (use hipaa-compliance).

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。

Compose multi-panel publication figures with patchwork, cowplot, gridExtra (R), or matplotlib GridSpec/subfigures (Python) including shared axes/legends/guides collection, panel labels in Nature/Cell convention, and journal-spec sizing. Covers patchwork ≥1.2.0 axes='collect' feature, Type-42 font embedding, and the cairo_pdf save path. Use when composing 2+ subpanels into a single figure for journal submission.

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Analyzes species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape data.

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 ChIP-seq quality across antibody specificity, fragmentation, enrichment, replicate concordance, and library complexity. Computes FRiP, NSC/RSC (phantompeakqualtools), library complexity (NRF/PBC1/PBC2), deepTools plotFingerprint (JS distance, AUC, synthetic JS), ChIPQC, IDR with ENCODE Nself/Nt rules, and detects hyper-ChIPable artifacts. Use when validating an antibody, diagnosing failed peak calls, deciding whether to proceed with downstream analysis, grading against ENCODE thresholds, or auditing replicate concordance.

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。

Calls ChIP-seq peaks with MACS3, MACS2, HOMER, or SPP across narrow (TF) and broad (histone) modes. Handles input control matching, fragment-size modeling vs --nomodel, effective genome size, ENCODE-style IDR vs naive overlap, hyper-ChIPable artifacts, and aligner-specific shifts. Use when calling peaks from ChIP-seq alignments, choosing between narrow vs broad mode for a histone mark, deciding model vs nomodel for low-depth data, applying ENCODE pseudoreplicate IDR, or reconciling MACS vs HOMER vs SPP results.

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。

Transition insulin pump to scheduled subcutaneous basal bolus insulin when anticipated hospital length of stay exceeds 1 to 2 days and pump expertise is unavailable. Triggers include: "Patient expected to stay >2 days, should we switch pump to scheduled insulin?

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Screen a hypercalcemic patient for medication- and supplement-induced causes — thiazides, lithium, vitamin D, vitamin A/retinoids, antiestrogens, theophylline, milk-alkali, SGLT2 inhibitors, immune checkpoint inhibitors, denosumab rebound, teriparatide/abaloparatide, foscarnet, ketogenic diet, aluminium. Trigger when a clinician asks "is this hypercalcemia drug-induced", "thiazide hypercalcemia", "lithium hypercalcemia", "denosumab rebound hypercalcemia", "vitamin D toxicity", "milk-alkali syndrome", "SGLT2 hypercalcemia", or any new hypercalcemia where medication review is needed.

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。