「rsa」の検索結果

Infers person-to-person transmission from pathogen genomes using outbreaker2 (Campbell 2018), TransPhylo (Didelot 2017), phybreak (Klinkenberg 2017), BadTrIP (De Maio 2018), SCOTTI (De Maio 2016), BEASTLIER (Hall 2015), and SNP-distance / cluster-picker approaches (HIV-TRACE for HIV; transcluster). Defines outbreak clusters using pathogen-specific SNP thresholds (NOT a universal cutoff -- TB <=12 SNPs / Walker 2013; MRSA <=15 / Coll 2017; C. difficile <=2 / Eyre 2013; Klebsiella <=21 / Snitkin 2012), models within-host diversity and transmission bottlenecks (Worby-Lipsitch-Hanage 2014; McCrone 2018; Sobel Leonard 2017; Lythgoe 2021 SARS-CoV-2), integrates contact-tracing data, distinguishes generation interval from serial interval (Britton & Scalia Tomba 2019; Ali 2020), attributes source via Bayesian source attribution (Mather 2013 DT104; islandR), and reconciles transmission-network reconstruction with epi metadata. Use when investigating outbreaks for who-infected-whom, defining SNP-cluster outbreak definitions, accounting for unsampled intermediates, choosing between outbreaker2 (rich epi data) and TransPhylo (genomic-only after dated phylogeny), running source attribution between host populations, calling HIV-TRACE thresholds appropriate to the local subtype, or distinguishing recent transmission from reactivation in TB / chronic HIV.

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。

Adversarial reviewer for The Federated Harbor whitepaper — the third paper in the Curiositech sequence after Anchor and Bonded Commons. Probes federation-specific threats: trust transitivity, cross-harbor token forgery, federated revocation under partition, cross-harbor Sybil, cross-domain settlement, equivocation, bond-pool draining, cold-start joining, federation-operator Sybil. Use during a versioned red-vs-white round; pairs with federated-harbor-whitehat. NOT for incident response, NOT for the Anchor or Bonded papers (use redteam-review).

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。

Classify every destructive/gated action an agent body can attempt (git, filesystem, network, shell, github) into block/approve/allow tiers, and audit whether the pre-tool and post-tool governance backing that classification is real: blocked actions proven zero-side-effect by a negative fixture, every denial backed by a receipt and a transcript event, every block-tier denial paired with a safe alternative, and no unmanaged or same-UID body ever marked "contained." Use when building or reviewing Agent Harbor's C5 governance gate (destructive git blocker, approval request/result, denial receipts), gating a new tool surface before it can run destructive commands, or auditing whether an existing "destructive-action blocked" claim actually has evidence behind it. NOT for proving an existing sandbox boundary actually contains an adversary once an action is isolated (use sandboxed-adversarial-test-harness), deciding where in a DAG to place a human review node or designing the approval UX itself (use human-gate-designer), or designing the general work-receipt schema across an entire agent task (use agent-work-receipt-designer).

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。

Meta-skill that orchestrates the discourse skill suite: routes between steel-man-argument, socratic-questioning, toulmin-argument-analysis, logical-fallacy-detector, bad-faith-rhetoric-detector, discourse-elision-analyzer, forensic-speech-structure, and productive-discourse-facilitator. Use when analyzing conversations, facilitating discourse, or operating as a dialogue copilot. Maintains mode (silent analysis, coaching overlay, active facilitator) and decides which skills to invoke based on conversation 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。

Expert bot developer specializing in Discord, Telegram, Slack automation with deep knowledge of rate limiting, state machines, event sourcing, moderation systems, and conversational AI integration. Activate on 'Discord bot', 'Telegram bot', 'Slack bot', 'chat automation', 'moderation system'. NOT for web APIs (use backend-architect), general automation scripts (use python-pro), or frontend chat widgets (use frontend-developer).

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 and audits closed, ordered, replay-safe message protocols between already admitted agent bodies. Use when a multi-agent exchange needs explicit epochs, audiences, per-sender sequencing, gathers, terminal fences, acknowledgements, and deterministic replay. NOT for selecting or spawning agents, granting identity or authority, choosing a runtime topology, general human facilitation, wire transport implementation, or deciding whether evidence is true.

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。

Discover failure modes in Coval runs, uploaded conversations or local conversation exports using scoped sampling and transcript, audio and trace evidence. Prepare human review without inventing ground truth or launching new runs.

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。

Redux state for agent execution and firing agent shortcuts. Use when editing features/agents/redux/, building agent UI, creating a conversation, touching assembleRequest or NDJSON stream state, wiring agent-state selectors, adding a per-conversation capability, or triggering a shortcut from a button, menu, or code (useShortcutTrigger, launchAgentExecution).

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 should be used when the user wants to "test a claim against data", "validate an empirical hypothesis", "refine a model/theory with evidence", "characterize a pattern and verify it", "演繹と帰納で検証", "仮説をデータで検証して更新", "実例と反例で確かめる", "弁証法ループ", "主張を現物で裏取り", "傾向分析を検証して精緻化", or mentions iteratively updating a hypothesis by deriving predictions and testing them against a real corpus. NOTE: Use this for VALIDATING/REFINING an empirical claim or model against real data through a derive→test→update loop. Use strong-inference for debugging an UNKNOWN cause, and devils-advocate for adversarially stress-testing a DESIGN proposal.

codex exec review を基本に、必要なら codex exec を使ってコード変更のレビューを依頼し、指摘事項を報告する。通常 / 厳しめ (--strict) / 敵対的 (--adversarial、実装を壊しにいく red team) の 3 モードを持つ。「codexでレビューして」「codex-review」「/codex-review」「敵対的にレビューして」で発火。Codex 単体での単独レビュー用途。複数エージェント並行レビューは cross-review、差分ではなくコードベース全体の監査は audit を使う。

Roleplay the most difficult, tech-resistant user for your product. Browse the app as that persona, find every UX pain point, then filter complaints through a pragmatism layer to separate real problems from noise. Creates actionable tickets from genuine issues only.

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 a conversational QA session where the user reports bugs or issues, and file durable Beads issues using project domain language. Use when the user wants to report bugs, do QA, file issues conversationally, or mentions a QA session.

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。

Detects defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.

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。

Build an automated system to track adversary infrastructure using passive DNS, certificate transparency, WHOIS data, and IP enrichment to map and monitor threat actor command-and-control networks.

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。

Generate React Spectrum UI components for Adobe Experience Cloud Shell SPAs and AEM UI Extensions. Provides patterns for pages, forms, data tables, dialogs, and navigation using @adobe/react-spectrum. Guides ExC Shell integration with @adobe/exc-app including runtime.done(), IMS token passthrough, and shell theming. Guides AEM UI Extension development with @adobe/uix-guest for Content Fragment Console, CF Editor, Universal Editor, and Assets View surfaces. Trigger on: building App Builder UI, React Spectrum components, ExC Shell pages, forms, data tables, dialogs, modals, navigation, theming, web-src, Spectrum design system, @adobe/exc-app, AEM extension, AEM UI extension, Content Fragment Console, Universal Editor extension, uix-guest, @adobe/uix-guest, extension points for AEM, customizing AEM surfaces.

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 path traversal and Zip Slip vulnerabilities where user-controlled path components can escape intended directories.

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 methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and byte-at-a-time decryption, hash length extension attacks against SHA1/SHA256/MD5-based MACs using HashPump, RSA vulnerabilities including small public exponent, common modulus, Bleichenbacher PKCS1v1.5 padding oracle, and Coppersmith's method for partial key recovery. Addresses weak PRNG exploitation targeting time-seeded generators and Mersenne Twister MT19937 state recovery from observed outputs, timing side-channel attacks against comparison operations, nonce reuse in AES-GCM leading to authentication key recovery, and key derivation weaknesses including insufficient iteration counts and missing salts. Primary tooling includes padbuster, RsaCtfTool, hashpump, and PyCryptodome for building c...

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。

Connect your AI assistant to GoHighLevel CRM via the official API v2. Manage contacts, conversations, calendars, pipelines, invoices, payments, workflows, and 30+ endpoint groups through natural language. Includes interactive setup wizard and 100+ pre-built, safe API commands. Python 3.6+ stdlib only — zero external dependencies.

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。

DiscordのローカルアーカイブからメッセージやDMを検索し、期間を絞った確認や要約に役立てるスキル。保存データの鮮度と取得範囲も確認します。

• Discordの過去の議論を探したいとき
• チャンネルの一週間を振り返りたいとき
• 保存済みの直近DMを確認したいとき

OpenClawへの自然な言葉の依頼をClaude Codeなどの外部コーディングエージェントへ振り分け、作業の開始や継続、スレッド内の会話をつなぐスキルです。

• Claude Codeをスレッドで開始
• 外部エージェントの作業を続けたいとき
• acpxから直接指示を渡したいとき

新しい機能や企画を作り始める前に、対話で目的や希望、制約を整理します。必要に応じて図や試作品で認識を確かめ、作業の規模に合った設計をまとめるスキルです。

• 新機能の目的を明確にしたいとき
• 講演や事業のアイデア整理
• 画面や部屋の配置を見比べたいとき

会話で話し合った内容とコードベースの理解から仕様書を作り、プロジェクトのIssue管理先に公開します。課題、利用者の要望、実装・テスト方針、対象外を整理します。

• 機能の議論を仕様書にしたいとき
• 合意した要件のIssue公開
• 実装とテストの方針の文書化

計画や設計を練り直したいときに、踏み込んだ質問を重ねるインタビューを行うスキル。考えを具体化するための対話を、関連スキルの呼び出しで始めます。

• 質問を通じて計画を練り直したいとき
• インタビューで設計を検討したいとき
• 対話で初期の案を具体化したいとき