「rsa」の検索結果

Facilitates conversational discovery to create Architectural Decision Records (ADRs) for non-functional requirements using the ISO/IEC 25010:2023 quality model. Use when the user wants to document quality attributes, NFR decisions, security/performance/scalability architecture, or design systems with measurable quality criteria. This should trigger for requests such as Create ADR for Non-functional requirements; Document Non-functional requirements; Capture Non-functional requirements; Generate Non-functional requirements in an ADR. Part of cursor-rules-java project

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Check whether a user may start side work alongside their current job, by reading the employer's own rules and contract clause by clause: whether side work is prohibited, needs prior permission, or only a notification, and which duties the planned side work could touch (non-compete, confidentiality, exclusive attention to the main job, use of company assets and information, combined working hours). Separate what is confirmed in a document from what is hearsay, and produce the questions to ask the employer plus the facts an application or notification will need. Use when someone with a main job is considering side work, freelance or gyomu-itaku work, a second part-time job, or paid trial work for another company, and needs to know what their own employer's rules require first; do not use to rule on whether a clause is lawful or enforceable, to help conceal side work from an employer or avoid filing obligations, to predict whether permission will be granted, or to submit the application or contact the employer.

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Use OpenAI Codex CLI as a peer collaboration partner — same standing as Claude, not a one-shot tool. Bring Codex in EARLY (ideation, framing decisions, stuck moments), not only for late peer-review. Hand it strategic context (target, research, draft, reasoning), iterate conversationally over ~3-8 turns, converge before surfacing to the human. Invoke when the user says "check / iterate / ideate with Codex" or "ask Codex" — and proactively when stuck between two reasonable framings, pressure-testing a load-bearing claim or structure, or about to ask the human to pick between options two agents could resolve.

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Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), MSIngs, MANTIS, MSIPanel, MSIDetect, and ngsMSI for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome / dMMR ICI biomarker. Use when stratifying ICI eligibility (Le 2015), pairing MSI with TMB-H (Sha 2020 / Salem 2018), screening Lynch syndrome (universal IHC + MSI), or distinguishing MSI-H tumors from POLE-exo hypermutator with overlapping signatures.

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Provides Spring Data Neo4j integration patterns for Spring Boot applications. Use when you need to work with a graph database, Neo4j nodes and relationships, Cypher queries, or Spring Data Neo4j. Creates node entities with @Node annotation, defines relationships with @Relationship, writes Cypher queries using @Query, configures imperative and reactive Neo4j repositories, implements graph traversal patterns, and sets up testing with embedded databases.

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Hunt for adversary techniques in telemetry you are authorized to query. Hypothesis-driven, evidence-first, no live offensive operations.

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Plan purple-team / adversary-simulation exercises against systems you are contracted to test. High-level objectives and detection gaps only. No live attack procedures or payloads.

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Read this skill before the first step of any request to do something in an app on the person's own computer (Notes, Finder, System Settings, any desktop app), to look at their screen, or for "computer use". Computer use (desktop control) lets Claude take screenshots of the person's desktop and control it with clicks, typing and scrolling through the Claude desktop app; its tools are named mcp__computer-use__* when the session runs in the desktop app and mcp__remote-devices__computer_* when a cloud session is linked to the person's computer; before computer use is turned on for a conversation there may be no such tools, only an enable__mcp__remote-devices__computer tool, which turns it on. It covers turning it on, picking the right tool, the access flow, and the safety rules for tiered apps, links and financial actions. It is not for websites, which go through Claude in Chrome or the built-in browser and their own skills.

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Import a memory export from another AI assistant into Claude's memory — conversationally, additively, and with the content treated as data.

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Azure Key Vault Keys Java SDK for cryptographic key management. Use when creating, managing, or using RSA/EC keys, performing encrypt/decrypt/sign/verify operations, or working with HSM-backed keys.

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Azure AI VoiceLive SDK for Java. Real-time bidirectional voice conversations with AI assistants using WebSocket.

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Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

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Adversarial thesis testing — act as a short seller to find the weakest points in a thesis. Use when user says "stress test", "devil's advocate", "challenge this thesis", or "break [TICKER]".

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Conversational AI-first interface with minimal controls, clear outcomes, and delegated task flows for agentic workflows.

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Adversarial verification of one SDD Composy task in verify_required: reproduce every claim with fresh commands, build the truth table, refute stale evidence, and produce the verdict that gates complete. Use when review is done and the task claims to be finished — 'verificar a TASK-003', 'a task está pronta mesmo?', 'is this task really complete'. Do NOT use for QA, code review, or a general 'verify my work' outside an SDD task.

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Use when about to claim work is complete, fixed, or passing, and when a finished feature needs adversarial verification before integration

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Use when starting any conversation in a repository that uses PWDEV Power - establishes how to find and apply Power skills before any response, including clarifying questions

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Deliver a small, bounded code change through inspection, a mini-plan, implementation, testing, review, and adversarial verification. Use for bug fixes, configuration changes, and features expected to touch no more than five files.

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Adversarially verify an implementation against its objective, acceptance criteria, definition of done, and prohibitions using fresh evidence. Use for completion gates, release readiness, or independent verification after implementation and review.

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Triage application logs, open GitHub issues, pending feedback, in-app Issues, and agent conversations. Runs five phases: logs → close shipped issues → feedback → in-app issues → agent FAQ gaps. Use when /whats shows pending feedback, checking app logs, cleaning up shipped issues, or working the in-app Issues backlog.

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Run multiple Reforge-guided section-refactor lanes in parallel, each in its own worktree/branch off origin/main, with a score-blind adversarial review panel gating every commit, one draft PR per section. Use when the user wants to reduce Reforge surface/internal score across several sections at once via architecturally-correct deletions (dead surface, entity-leak removal, cross-section read-splits) — not by relocation, parameter bags, or accessibility-dodging. Wraps the per-lane process in .codex/skills/humans-refactor. Triggers: 'refactor swarm', 'parallel section refactors', 'run reforge refactor on Users/Tickets/...', 'burn down surface score across sections'. Has an intensity dial (light|standard|deep) and a workflow|solo execution mode to trade token burn against autonomy per unit of output.

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Adversarial triage of open review findings on a PR. Every finding (Codex, Claude bot, Gemini) is a hostile hypothesis to REFUTE — fix only what is proven real, reachable, in the PR's scope, and above the round's severity bar. The bar rises every review round. Everything else is declined or filed as an issue. Use for 'fix the PR findings', '/fix', '/fix 123', or before any fix commit in a review loop.

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When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'ad iterations,' 'creative testing,' 'ad performance optimization,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' or 'I need more ad variations.' Use this whenever someone needs to produce ad copy at scale or iterate on existing ads. For campaign strategy and targeting, see paid-ads. For landing page copy, see copywriting.

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Self-tuning question sensitivity + developer psychographic for gstack (v1: observational). Review which AskUserQuestion prompts fire across gstack skills, set per-question preferences (never-ask / always-ask / ask-only-for-one-way), inspect the dual-track profile (what you declared vs what your behavior suggests), and enable/disable question tuning. Conversational interface — no CLI syntax required. Use when asked to "tune questions", "stop asking me that", "too many questions", "show my profile", "what questions have I been asked", "show my vibe", "developer profile", or "turn off question tuning". (gstack) Proactively suggest when the user says the same gstack question has come up before, or when they explicitly override a recommendation for the Nth time.

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