「session id」の検索結果

Apply STRIDE methodology to systematically identify threats. Use when analyzing system security, conducting threat modeling sessions, or creating security documentation.

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Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.

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Work with OpenViking, the persistent context database behind this agent's memory. Use it whenever the user refers to earlier sessions or shared history ("like last time", "what did we decide"), asks to remember or forget something, shares files, URLs, or repos worth keeping, or when the task needs context this session does not have — even if nobody says the word "memory". Also use it when the user asks where memories are stored: per project, per folder, or shared between repositories. Covers choosing between context search, find, list search, and grep, reading viking:// URIs, and when (not) to write.

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Detect and respond to OAuth token theft and replay in Microsoft Entra ID (Azure AD), covering access token theft, refresh token replay, Primary Refresh Token (PRT) abuse, pass-the-cookie attacks, and Token Protection conditional access policies. Use for impossible-travel or anomalous token-usage alerts, suspected session hijacking, sign-in log analysis, or configuring token-binding defenses in Azure/M365.

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Conduct internal Active Directory reconnaissance using BloodHound Community Edition's graph database with the SharpHound (AD) and AzureHound (Entra ID) collectors, mapping ACLs, sessions, and group memberships into attack paths from a low-privileged foothold to Domain Admin. Use after an initial AD foothold to identify privilege escalation chains, or to validate that AD hardening closed known attack paths.

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Import AI-assistant chat exports (ChatGPT, Claude, Perplexity) and agent session transcripts into the brain as one dated page per conversation under conversations/, validate each page against the native conversation parser, extract facts via the native conversation-facts flow, and keep the archive gap-free with a detect-and-backfill loop. Then answer archive questions: "when did I first discuss X", trace how an idea evolved across past conversations, pull a specific thread.

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Reference skill for Zoom Video SDK. Use after routing to a custom-session workflow when the user needs full control over the video experience rather than an actual Zoom meeting.

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Zoom Video SDK for macOS native desktop apps. Use when building custom macOS video sessions with native UI control, tokenized join, and desktop-oriented media/device workflows.

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。

Zoom Video SDK for Web - JavaScript/TypeScript integration for browser-based video sessions, real-time communication, screen sharing, recording, and live transcription

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Phase 2 of building a Claude Managed Agent — turn a validated build sheet into exact API payloads and a resumable BYOK curl launch script, then launch (environment → agent → session → kickoff) using the founder's OWN Anthropic key. Use when the user says "launch it", "deploy the agent", "create the agent now", or when the orchestrator routes phase=stage-launch. payload_generator.py emits the four ordered payloads; launch_script_writer.py writes launch.sh that reads $ANTHROPIC_API_KEY at runtime and never embeds it; payload_validator.py runs a pre-launch check including an API-key-leak scan. No tool in this skill makes network calls — the user runs launch.sh themselves. Distinct from interview (planning) and grade-iterate (the outcome loop).

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Use when testing a local or public URL on a real device via BrowserStack, opening a live browser session on Android, iOS, or desktop browsers, or when the user mentions BrowserStack, real device testing, mobile testing, cross-browser testing, touch testing, or wants to verify behavior on a specific phone, tablet, or browser version. Also trigger when the user says "test this on Android/iPhone/Safari/Chrome mobile", asks to open a live session, or mentions demo-mobile.html, even if they don't mention BrowserStack by name.

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Provides guidance and instructions on managing remote devices on Developer Device Platform (DDP). Use when reserving remote Android devices, establishing connection tunnels, checking session status, or extending/cancelling leases. Don't use for iOS or local device/hardware inquiries.

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Canonical reference for Kortix projects, Apps (sites, servers, backends with volumes) and internal business apps, the CLI, sessions, sandboxes, change requests, triggers, connectors, secrets, system skills, and the two session harnesses, pi and OpenCode. Covers `kortix.yaml` versions 1 and 2, serverless App deployments, harness configuration (`harnesses/pi/`, `harnesses/opencode/`), session identity, credential boundaries, and the complete pi and OpenCode references. Load when the user asks how Kortix works, what Kortix can do, how to deploy an App, how an agent discovers platform instructions, how to customize or configure this project's agents (create or fix an agent, subagent, skill, tool, plugin, extension, pi package, command, MCP server, model or permission rule; edit `opencode.jsonc`), how to edit `kortix.yaml`, how to use the `kortix` CLI, how to land work through a change request, or how to schedule and automate work.

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Route code, repository, and data/SQL work to isolated Kortix sessions instead of burning your main context on it. Use when asked to implement a feature, fix a bug, make failing tests pass, work a ticket/issue, refactor, navigate or change a codebase, ship a PR, review a pull request, or run SQL/warehouse analysis against a dataset — and when the user wants two agents or parallel reviewers/investigators on the same work. Covers the explore-vs-session routing call, deciding where the code lives (this project's repo vs cloning an external GitHub repo) or where the data lives, finding the repo with gh, spawning sessions in parallel, dual PR reviews, and reporting results back. Triggers: 'implement', 'fix the bug', 'make the tests pass', 'work this ticket', 'refactor this', 'open a PR', 'review this PR', 'run two agents on it', 'query the warehouse', 'analyze this dataset'.

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Backend-specific Windows guidance for `computer_use_remote`. Load after `status` or `start_session` reports backend_family/backend_id `windows` or Windows UI Automation features. Covers UIA structural targeting, Windows session caveats, and screenshot verification.

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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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Use when implementing authentication/authorization, securing user input, or preventing OWASP Top 10 vulnerabilities — including custom security implementations such as hashing passwords with bcrypt/argon2, sanitizing SQL queries with parameterized statements, configuring CORS/CSP headers, validating input with Zod, and setting up JWT tokens. Invoke for authentication, authorization, input validation, encryption, OWASP Top 10 prevention, secure session management, and security hardening. For pre-built OAuth/SSO integrations or standalone security audits, consider a more specialized skill.

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Automation and verification guide for running Native SDK apps. Use when the user asks to test a running app, inspect runtime state, list windows, wait for readiness, drive widgets, take deterministic screenshots, send bridge commands, debug why automation is not connected, create smoke tests, or verify a Native SDK example in a GUI-capable session.

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Use when you have just been primed into an EXISTING seat through a planned handover — a different agent retired and handed you the seat plus its earned context — and you need a world model of what just happened to you. Covers how a handover differs from compaction and from a fresh launch, the inherit-the-seat-not-the-identity rule, treating the handover packet as testimony you verify (and refusing stale ghost prompts, and verifying your OWN identity surfaces), why a seat is a COMPOUNDING LINEAGE (inherit the state, acquire the predecessor's epistemology, then improve and re-deposit so the next generation is better), how to query your predecessor, your duty to stream feedback and re-deposit your earned wisdom, and how to route to role-specific onboarding. NOT the driver-side handover mechanic (retiring-and-inheriting-a-seat) and NOT unplanned compaction/crash recovery (claude-compaction-restore / session-compaction-and-restore).

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。

Print the session id that correlates this Codex session in Weave Router telemetry and logs.

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Guide users from zero to their first working mirrord session — check system requirements, install mirrord via CLI, VS Code, or IntelliJ, run a first session against a Kubernetes target, and verify the connection. Use when a user is new to mirrord, wants to install it, needs help running their first session, or wants to debug or test a local process against their Kubernetes cluster.

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Hunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses) — persistent corpus poisoning that survives across sessions and users (distinct from one-shot indirect prompt injection, which is owned by hunt-llm-ai), cross-tenant vector-database IDOR (unauthenticated or unscoped queries against Pinecone/Weaviate/Chroma/Milvus/Qdrant/pgvector), source-text/metadata leakage in similarity-search results, and retrieval-hijack via adversarial embedding proximity ('SEO poisoning' for RAG). Targets: any app with a shared knowledge base, document upload feeding a chatbot, or a directly reachable vector-DB port. Validate: a second, clean session/account must inherit a poisoned result, or a cross-tenant artifact must be independently verifiable — confabulation is not a finding, same bar as hunt-llm-ai. Use when target is RAG-backed, exposes a vector-DB port, or lets users upload documents that other users' queries later retrieve.

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Authentication patterns: session vs JWT vs OAuth comparison, provider selection (NextAuth, Clerk, Supabase Auth), security checklist, and common mistakes. Use when implementing auth, reviewing auth flows, or choosing auth providers.

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Plug-in vision for text-only models. Hard rule: when a file path or URL with an image extension (.png, .jpg, .jpeg, .webp, .gif, .heic, .heif) appears anywhere in the conversation (typed by the user, injected as a `[Image: source: <path>]` line, or inside a tag) and you cannot see that image's content, run this skill on it before any other approach: no self-built OCR, no PIL, no tesseract. Also triggers on pasted-image placeholders such as `[Image #1]` and `[Unsupported Image]`. If you can actually see the image, do not use this skill. When unsure, run `modlens guard` before the first read of a session: a deny verdict means the active model has native vision and must read the image itself. Runs the modlens CLI to convert the image into structured JSON evidence: every word transcribed, layout regions, semantics, visual clues. Also use when the user asks how to install, configure, or switch modlens providers (Gemini API key, OpenAI-compatible endpoints, Claude API or Claude Code CLI).

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。