「toc」の検索結果

Agent2Agent (A2A) Protocol implementation - communicate with other AI 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。

Register and manage ERC-8004 Identity NFTs on Monad. Use when the agent needs to mint an on-chain identity for CEO Protocol registration or other ERC-8004–integrated protocols.

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 healthcare chart audit protocols covering clinical documentation review, coding accuracy, and billing compliance. Aligns with Medicare CoPs, OIG Compliance Program Guidance, RAC preparedness, federal sentencing guidelines, and the 60-day overpayment rule. Use when drafting routine periodic audits, targeted risk reviews, proactive compliance measures, or post-regulatory-update assessments.

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。

Citation format and verification protocol for legal documents that draw on Bates-stamped source records. Defines the bracket citation format, multi-source citation rules, quotation handling, the verification pass that runs before output, and the [UNVERIFIED] flag protocol. Use this skill any time another skill produces a legal work product that cites Bates-stamped pages, including medical chronologies, deposition summaries, demand letters, case briefs, and discovery responses. Also use any time the user asks how to format a citation or verify that a claim is supported by the source.

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。

Generates appellate-brief TOC, TOA, and Certificate of Compliance with defensible word-count methodology. Triggers on TOC/TOA rebuilds, certificate of compliance drafting, FRAP 32(g) compliance, word-count certification, or final brief formatting before 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。

Design Kafka consumer groups that survive rebalances, hit the right delivery guarantee (at-most/at-least/exactly-once), and handle poison messages without stalling the topic. Use when picking a partition assignment strategy (Range vs Sticky vs Cooperative-Sticky vs the new KIP-848 protocol), tuning heartbeat / session / max.poll.interval timeouts, choosing manual vs auto offset commits, designing dead-letter or retry topics, or migrating from Classic to the next-gen Consumer protocol. NOT for Kafka cluster ops (broker tuning, partition reassignment), schema design (Avro/Protobuf/Schema Registry), or stream processing topology (use a kafka-streams 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。

Benchmark multi-agent coordination systems with experiment design, power analysis, human rating protocols, bootstrap confidence intervals, and reproducible reporting. Use for salvage latency, recovery fidelity, coordination overhead, and protocol comparison studies. NOT for ML model benchmarking, web-product A/B testing, survey design, or general-purpose data science.

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。

Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-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。

Detect crisis signals in user content using NLP, mental health sentiment analysis, and safe intervention protocols. Implements suicide ideation detection, automated escalation, and crisis resource integration. Use for mental health apps, recovery platforms, support communities. Activate on "crisis detection", "suicide prevention", "mental health NLP", "intervention protocol". NOT for general sentiment analysis, medical diagnosis, or replacing professional help.

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Call germline SNPs and indels with GATK HaplotypeCaller and the GVCF joint-genotyping workflow. Covers the local-reassembly + PairHMM mechanism (why HC beats pileup callers on indels), the -ERC GVCF reference-confidence model and <NON_REF> allele, BQSR-vs-DRAGSTR and --dragen-mode error modeling, allele-specific (AS_) annotations, and edge cases (ploidy, Mutect2 mitochondria mode, sex chromosomes/PAR, contamination gating). Use when deciding whether to use HaplotypeCaller vs a pileup or DRAGEN caller, whether BQSR still earns its place, whether to call per-sample GVCFs for a cohort, or how to handle non-diploid, mitochondrial, sex-chromosome, or contaminated samples. Not for post-calling filtering depth (see variant-calling/filtering-best-practices) or cohort joint-genotyping scaling (see variant-calling/joint-calling).

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。

Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.

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。

Suggests that clinicians continue CSII in hospitalized patients with type 1 or type 2 diabetes when the institution has clear protocols for evaluating pump candidates and appropriate monitoring and safety procedures. Trigger phrases include: 'Admitted patient on pump, check hospital pump policy' and 'Inpatient with diabetes using pump, verify institutional guidelines'.

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。

Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.

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。

Search and preview Irasutoya illustrations with the installed `irasutoya` command-line tool. Use this skill whenever the user wants to find, recommend, preview, randomly pull up, or get the page/image URL of an Irasutoya (いらすとや) image — from a topic, scene, Korean/Japanese/English phrase, visual description, emotion, character, object, or action — even if they don't say "Irasutoya" by name but clearly want a free, cute illustration for a slide, 발표자료, blog, doc, or chat. Also use it to optimize vague requests into fast Japanese keyword candidates and to return page/image URLs. Do NOT use it to generate brand-new AI art (e.g. DALL·E, Midjourney), draw charts or diagrams, design logos or icons, cut out/edit existing images, or recommend other stock-image sites — it only searches Irasutoya's existing catalog.

Setup and optimize cryptocurrency mining operations — AI-powered mining (soul.md protocol), parallel agent deployment, accumulation strategies, and performance 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。

Expert-level probability theory knowledge. Use when working with probability spaces, random variables, distributions, expectation, variance, conditional probability, stochastic processes, Markov chains, martingales, or measure-theoretic probability. Also use when the user mentions 'sample space', 'random variable', 'expected value', 'variance', 'conditional probability', 'independence', 'Markov chain', 'Poisson process', 'moment generating function', 'law of large numbers', 'central limit theorem', or 'stochastic process'.

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-level green chemistry knowledge. Use when working with sustainable synthesis, atom economy, solvent selection, catalysis, renewable feedstocks, waste reduction, life cycle assessment, or the 12 principles of green chemistry. Also use when the user mentions 'atom economy', 'E-factor', 'green solvent', 'catalysis', 'renewable feedstock', 'waste minimization', 'sustainable chemistry', 'life cycle assessment', 'PMI', 'solvent selection guide', or 'benign by design'.

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。

[Skill Management] Use when shared protocol checklists change and need propagation across 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。

Phase 5 part of disease-market-sizing-orchestration. Injects consulting palette (navy/gold/blue) + base CSS + floating TOC + section dividers into raw report HTML. Validates token coverage ≥60% (warn) and floating TOC li ≥5 (block). Use AFTER content-verification passes, BEFORE report-bundle-builder build_all_deliverables.

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, audit, harden, review, or upgrade MCP servers and MCP Apps with revision-aware protocol profiles, explicit HTTP/deployment boundaries, capability-centered validation, bilingual reporting, and reproducible evidence. Use for MCP server architecture, JSON-RPC or Streamable HTTP bugs, security hardening, protocol-version migration, MCP Apps widget boundaries, review reconciliation, test planning, and public engineering evidence.

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。

The LAW a council SEAT is bound by — deliberation protocol, pact obligations, governance, and decision-ledger recording — the discipline half of a seat. Trigger when: - Holding a seat on a bound council (architect, lead-maintainer, process-auditor, or a summoned guest). - Depositing an independent assessment, routing a decision, or recording assent or a finding. - Auditing whether the council honored the pact, the delegation table, or the barring lifecycle. - Prompt contains: /council, council seat, deliberation protocol, pact, delegation table, decision ledger, barring, merge-consent.

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。

Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.

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。

This skill covers detecting cyber attacks targeting Supervisory Control and Data Acquisition (SCADA) systems including man-in-the-middle attacks on industrial protocols, unauthorized command injection into PLCs, HMI compromise, historian data manipulation, and denial-of-service against control system communications. It leverages OT-specific intrusion detection systems, industrial protocol anomaly detection, and process data analytics to identify attacks that traditional IT security tools miss.

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。

This skill teaches security teams how to detect and respond to unauthorized cryptocurrency mining operations in cloud environments. It covers identifying cryptomining indicators through compute usage anomalies, network traffic patterns to mining pools, GuardDuty CryptoCurrency findings, and runtime process monitoring on EC2, ECS, EKS, and Azure Automation workloads.

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。