'rsa' 검색 결과

Automate Endorsal operations through Rube MCP, a connection for agent tools. The skill searches for suitable actions, checks that the service connection is active, and executes tasks using the latest tool input requirements.

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• Discovering available Endorsal actions
• Running Endorsal tasks after checking the connection
• Retrieving results across multiple pages

Build Python features that identify a speaker’s intent and extract details such as names from conversation text using Azure. Get guidance on request structure, authentication, client cleanup, and exception handling.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding intent detection to a Python application
• Extracting names and other details from conversation text
• Structuring requests for ConversationAnalysisClient

Collect an X conversation from its root post ID, including replies and nested replies visible to the logged-in account. Return structured text, author details, engagement counts, and reply relationships for reviewing discussions or preparing further analysis.

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• Collect replies to a widely discussed post
• Review question-and-answer discussions
• Reconstruct reply relationships in long conversations

Connect a ChatGPT or Claude account to import conversation history into knowledge pages. Sync new and changed conversations incrementally, revisit recent history to catch updates, and optionally enable scheduled syncing.

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• Importing ChatGPT conversation history
• Syncing Claude conversations into knowledge pages
• Keeping new and edited conversations up to date

Turn exported AI chats and agent session logs into dated, searchable pages in gbrain. Check for missing conversations, extract facts, and trace when a topic first appeared or how an idea developed, with quotes and dated references.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Organizing exported AI chat histories
• Finding the first discussion of a topic
• Tracing how an idea developed

Assess how applications use encryption, signed tokens, and random values. Identify implementation weaknesses, select relevant testing tools, and document causes and fixes for issues involving encryption modes, RSA parameters, predictable randomness, and key derivation.

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• Assessing encrypted cookies and tokens
• Checking RSA keys and cryptographic settings
• Testing session token predictability

Review AI agent spending by conversation, with each session’s start time, message count, main model, and total cost. Use the results to identify expensive sessions and understand typical costs before planning longer work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review spending across completed conversations
• Identify conversations with high costs
• Estimate typical costs before a long session

End-to-end Coval adversarial / red-team testing workflow. Builds one adversarial test set (12 core attack vectors plus legitimate controls, each with an expected-behavior checklist), creates a persistent "Adversarial User" persona and a Composite Evaluation metric that scores each scenario against its own expected behaviors, launches a multi-iteration run against the agent (voice or chat), polls for completion, builds a per-scenario pass/fail scorecard, and creates a saved report grouped by Test Case. Use when a user wants to follow the Adversarial & Red-Team Testing cookbook (https://docs.coval.dev/guides/adversarial-red-team-testing) without doing each step by hand. Triggers: "adversarial test set", "red team my agent", "jailbreak / prompt-injection testing", "test my agent against bad actors".

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Plan and measure defensive deception operations with MITRE Engage. Connect decoy systems and credentials to specific attacker techniques, define measurable objectives, and document operating boundaries, response procedures, and criteria for assessing results.

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• Giving existing honeypots a coordinated strategy
• Selecting decoys for a specific threat actor
• Writing an adversary engagement operation plan

Automate X direct message workflows by finding conversations awaiting replies, reading history, and sending text prepared by the calling agent. Also search for users, check messaging permissions, start conversations, and verify delivery.

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• Finding unread conversations or messages awaiting replies
• Sending replies based on a defined persona and conversation history
• Searching for users to contact about collaborations

Analyze successful Google and Meta ads to find useful patterns in headlines, body text, and calls to action. Generate new copy variants that preserve those patterns, with platform formatting, test priorities, and suggested pairings for comparison.

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• Refreshing ad copy when existing creatives lose effectiveness
• Starting an ad copy brainstorming session
• Testing messaging angles for a new audience

Draft, confirm, and post a single conversational reply to GitHub PR conversation comments (issue comments). The reply addresses all tracked items in one natural-prose message. Use when the user asks to "reply to PR conversation", "post PR conversation replies", or "draft PR conversation messages".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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).

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Implement caching and data conversion for syncable entities in Twenty's server code. Build lookup maps, convert stored records and inputs into flat representations, and resolve references to universal identifiers for later validation and processing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a cache service for a new syncable entity
• Convert stored entities into flat data
• Transform creation and update inputs

Design memory systems that help AI assistants retain conversation information and retrieve it when relevant. Explore short-term, long-term, and entity memory, along with memory consolidation, prompt integration, storage lifecycle management, and separation between users.

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• Designing an assistant that remembers across conversations
• Storing and updating facts about people or other entities
• Adding relevant memories to prompts

Create evaluation drafts for existing skills using actual conversations and user corrections. Produce criteria and repeatable test cases, distinguish evidence from specification assumptions, and prepare an anonymized draft for human review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turn user corrections into repeatable test cases
• Compare promised behavior with actual usage
• Draft an evaluation from conversation history

Create paid ad headlines and body copy tailored to each platform's character limits. Use existing performance data to develop variations, explore new messaging angles, and check copy for length, quality, and potential rejection risks.

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• Creating Google RSA headlines
• Writing Meta and LinkedIn ad copy
• Developing variations of successful ads

Review code changes from three critical perspectives: production failures, maintainability, and security. Get a consolidated report that ranks findings by severity and provides merge guidance, helping examine assumptions that an ordinary self-review may overlook.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing a pull request before merging
• Getting a second opinion on AI-written code
• Checking authentication or data access code

Request an owner’s permission to use a listed keychain credential needed by a command. An approval card appears in the conversation, and owner approval automatically reruns the blocked command with access shared across that conversation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Request permission for a credential needed by a command
• Resume a blocked command after its owner approves access
• Share approved access across sessions in one conversation

Build image conversations with LLaVA, a model that connects image recognition with language. This skill guides setup, image descriptions, visual questions, and follow-up conversations, with examples for Python, command-line use, and a Gradio interface.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a chatbot that answers questions about images
• Write detailed descriptions of photos
• Ask follow-up questions about the same image

Create a new Claude Code session from the later half of the current conversation. Keep recent work while reducing conversation tokens, then receive a command to resume the copied session directly.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Continuing a long conversation with its later half
• Reducing tokens while keeping recent work
• Resuming a copied session with a direct command

Create a new Claude Code session containing only the last quarter of the current conversation. Preserve the most recent work, reduce conversation tokens, and get a command to resume the copied session directly.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Continuing with only the last quarter of a conversation
• Reducing tokens while keeping the most recent work
• Resuming a copied session with a direct command

Configure a new OpenRig agent seat, a managed place for an agent to run, using a prior Claude or Codex conversation. Covers fork settings, new session identities, and checks that distinguish forking from restoring.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create a new agent seat from an earlier conversation
• Add conversation source settings to a rig expand payload
• Distinguish conversation forks from seat restoration

Assess iOS apps from IPA acquisition through file inspection and runtime testing. The skill helps uncover embedded credentials, insecure network settings, and app link handling issues using tools such as Frida, objection, and binary analysis utilities.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Assessing an iOS app in a bug bounty program
• Finding credentials and API endpoints inside an IPA
• Reviewing ATS settings and inspecting app traffic