「rsa」の検索結果

Use when a plan, feature, or launch needs an explicit adversarial pass to find weak assumptions, abuse cases, or strategic blind spots before execution.

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Create colorful infographic PNGs from a conversation, topic, file, skill, or workflow. Use when: インフォグラフィック, 図解, 挿絵, 章扉, X投稿用画像, OGP, HTML→PNG, visualize session, poster image. Produces 2-3 self-contained HTML patterns, renders static PNGs, and verifies every image visually before reporting. Not for animated GIFs, architecture/sequence/flow diagrams (editable .drawio or interactive HTML), or HTML slide decks.

Create or review a reusable skill (SKILL.md) that packages a workflow, and decide whether the request should be a skill instead of a prompt, instruction, agent, or hook. Use when creating a new skill, extracting a workflow from a conversation, updating an existing skill, reviewing SKILL.md quality, or fixing weak skill triggering. Triggers on "create skill", "/create-skill", "new skill", "review skill", "fix skill trigger", "SKILL.md", "スキル作成".

Prepare to deliver difficult technical news to a client — a conversational prep session before the hard conversation happens

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"Design conversational AI chatbots including intent recognition, slot filling, dialogue flow, and response generation. Use this skill when the user needs to build a chatbot, design conversation flows, implement intent classification, or improve chatbot accuracy — even if they say 'build a chatbot', 'our bot doesn't understand users', 'design a FAQ bot', or 'improve our chatbot's responses'.".

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Exploit path traversal and local/remote file inclusion (LFI/RFI) via URL parameters, cookies, and hidden fields using ../ sequences, URL encoding (%2e%2e%2f), double encoding (%252e%252e%255c), Unicode bypasses (..%c0%af), and Windows UNC paths. PHP include/require with $_GET/$_POST/$_COOKIE pattern. Target /etc/passwd, boot.ini, web.config. Tools: DotDotPwn, WFuzz, Burp Suite, ZAP.

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Path traversal and LFI playbook. Use when file paths, download endpoints, include operations, archive extraction, or wrapper behavior may expose filesystem control.

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Simulate supply chain and adversarial machine learning attacks by injecting poisoned data or targeted backdoors into training and fine-tuning datasets. Use this skill when assessing the integrity controls of MLOps pipelines or evaluating the resilience of AI models against highly targeted, stealthy manipulation intended to alter model behavior on specific triggers.

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Identify and simulate Data Poisoning attacks aimed at degrading or skewing an AI model's accuracy. This skill focuses on Adversarial Machine Learning concepts where attackers inject malicious or mislabelled data points into training or fine-tuning datasets (e.g., feedback loops) to bias the AI.

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Run a seven-agent adversarial pipeline against a resume and cover letter before submission. Produces channel-conditional verdicts anchored to the realistic applicant pool, separates materials quality from submission expected value, and ends with a contrarian pass that can overturn the verdict.

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Orchestrate a whole-registry sweep of Gaia — fan out 13 parallel audit agents across every skill, run adversarial verification, surface Semantic Fusion candidates, propose new generic skill references, and synthesize a publish-ready HTML report under docs/meta/reports/. Use this skill for broad, systemic analysis across many skills at once: "run a meta sweep", "sweep the meta", "full meta audit", "audit the whole registry against META.md", "widespread nomenclature issues", "find all skills missing a GitHub link", "produce a meta report", "check for evidence type mismatches across the registry", "find skills that document a third-party tool with no attribution", or explicitly types /gaia-meta-sweep. This is the registry-wide macro companion to /gaia-meta-audit (a prioritized queue, single-pass) and /gaia-audit (fixes one skill). Use it when you need the full surface — 13 audit dimensions, adversarial verification, fusion proposals, and a durable findings artifact — not just a queue.

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Top-level orchestrator for the Gaia Skill Tree evidence verification pipeline. Run this when you want to do a full evidence pass — collecting raw sources, verifying live GitHub star counts, running Phase 2B benchmark-source verification, adversarially auditing for quality/formatting issues, and checking that every URL is reachable — all in one coordinated sequence. Trigger phrases: "run the evidence pipeline", "full evidence pass", "verify evidence", "evidence verification pipeline", "run ev-pipeline", "check all evidence", "audit the data lake", "evidence quality sweep", "refresh evidence", "validate evidence sources". Also aliased as /evidence-verification-pipeline. Use the individual sub-skills (ev-collection, ev-star-verification, ev-adversarial-audit, ev-link-validation) only when you need to re-run one phase in isolation; for end-to-end work, always start here.

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Convert current conversation context into a structured Product Requirements Document (PRD) and optionally post it to GitHub Issues. Use before /supergraph:plan when requirements came from a conversation, user story, or feature discussion rather than a formal spec.

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Use when a task needs the judgment of a professional dancer — preparing for a company audition, managing rehearsal load against injury risk, deciding whether to dance through pain or report it, negotiating a casting or return-to-dance plan with a rehearsal director, or critiquing a performance for technical and artistic fidelity to the choreography.

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Manages cloud infrastructure through natural language conversations with Pulumi Neo, an AI agent for platform engineers. Enables infrastructure analysis, resource provisioning, stack deployment, and configuration management via conversational AI. Use when creating Neo tasks, requesting infrastructure analysis, automating cloud deployments, managing infrastructure as code (IaC), provisioning AWS/Azure/GCP resources, managing infrastructure through natural language prompts, reviewing PRs with Neo, handling Neo approval workflows, or checking Neo task status and events. Also use when the user mentions "Pulumi Neo", "Neo task", "Neo agent", or wants AI-assisted infrastructure management.

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Synthesises the current conversation context into a Product Requirements Document and publishes it to GitHub (as a comment on a referenced issue, or a new issue). Synthesises from context; does not interview. TRIGGER when: the conversation has produced enough understanding of a feature and the user wants it captured as a PRD. DO NOT TRIGGER when: a single small issue is enough → creating-issues; the idea has not been stress-tested yet → grilling-ideas first; bug reports.

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Keep long conversations coherent — summarization checkpoints, entity tracking, topic stacks, and graceful context handoffs. Use when dialogues run long or span sessions and the agent keeps losing the thread.

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。

Use conversational marketing — chatbot strategy, conversation design, lead qualification bots, and messaging ROI.

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Deliver feedback using Kim Scott's Radical Candor framework - care personally while challenging directly. Use when a leader needs to give difficult feedback, says "I need to tell someone something hard", "how do I give feedback without hurting them", "I've been avoiding a conversation", "my direct report isn't performing", "someone on my team has a blind spot", "I keep sugarcoating things", or "how do I be honest without being a jerk". Also trigger when someone describes being too nice (ruinous empathy) or too harsh (obnoxious aggression), or when they describe avoiding a conversation they know they need to have.

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Identify expansion signals and structure upsell or cross-sell conversations using land-and-expand and Net Revenue Retention principles. Use when user says "upsell", "expansion", "cross-sell", "grow the account", "increase ARR", "find expansion opportunities", "NRR improvement", "upgrade conversation", "add-on", "renewal and expand", or "land and expand" - even if they don't say "expansion discovery" explicitly. Applies to CSMs managing account growth or CS teams building expansion playbooks.

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Save a user-selected answer, decision, insight, or session summary into an Obsidian vault as one reviewed transaction. Use only when the user explicitly asks to preserve specific conversation content, not when they supply a file or URL to ingest. Triggers: /save, save this, save that answer, file this conversation, save this analysis, keep this insight, preserve this chat result.

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Audit X Ads measurement, X Pixel and Conversions API, campaign objectives, keyword and conversation targeting, creative, budgets, brand safety, app measurement, and reporting. Use for X Ads, Twitter Ads, promoted posts, X Pixel, X Conversions API, conversation targeting, or paid campaigns on X.

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Use when Agentforce run costs are climbing, you need to forecast scale, or you want to reduce tokens per conversation without hurting quality. Covers topic (now subagent) design impact on cost, prompt/template reuse, grounding size discipline, caching, and model-tier selection. Triggers: 'agentforce cost', 'tokens per conversation too high', 'reduce agentforce runs spend', 'forecast agentforce scale cost', 'einstein trust layer tokens'. NOT for capping spend per user with a budget gate and fallback — use agentforce/agent-rate-limit-strategy. NOT for org-wide model-tier and BYOLLM platform strategy — use architect/ai-platform-architecture.

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Use this skill when building custom channel integrations with the Agentforce Agent API or BYOC (Bring Your Own Channel) for CCaaS — covering session lifecycle management, webhook handling, externalSessionKey design, sequenceId sequencing, BYOC Interaction API integration, and conversation state management. NOT for standing up a standard channel (Embedded Service, Slack, Experience Cloud, Messaging) — use agentforce/agent-channel-deployment. NOT for writing the Apex actions the agent invokes — use agentforce/custom-agent-actions-apex.

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。