「deep」の検索結果

Have a fast, conversational analysis with the AWS DevOps Agent. Use for cost optimization, architecture review, topology mapping, knowledge / runbook discovery, security audits, dependency questions, and quick diagnostics — anything that needs a 5-30 second answer rather than a 5-8 minute deep investigation. Trigger words include cost, optimize, review, architecture, topology, what runbooks, show me, compare, audit, what if.

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。

Performs a full AWS Well-Architected Framework review evaluating every framework question across all pillars discovered from the live AWS documentation by analyzing code, IaC, and configurations to produce evidence-backed findings with Eisenhower-prioritized remediation. Supports full reviews (every framework best practice with BP ID citations), quick reviews (question-level), pillar-scoped reviews, score-mode reviews (a maturity scorecard with per-pillar scores and filtered findings), and lens-specific reviews using lenses discovered from the live AWS documentation. Triggers on mentions of Well-Architected review, WA review, WAR, pillar assessment, architecture review across pillars, workload assessment, cloud readiness evaluation, or a Well-Architected score, grade, or scorecard request. Does not apply to single-pillar deep-dives, learning WA concepts, ADRs, or migration readiness assessments.

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。

Migrate notes between Apple Notes, Obsidian, Notion, and other platforms. Trigger: "apple notes migration".

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。

Comprehensive Apollo.io migration strategies. Use when migrating from other CRMs to Apollo, consolidating data sources, or executing large-scale data migrations. Trigger with phrases like "apollo migration", "migrate to apollo", "apollo data import", "crm to apollo", "apollo migration strategy".

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。

Migrate to Claude API from OpenAI, Gemini, or other LLM providers. Use when switching from GPT-4 to Claude, migrating from Text Completions, or building a multi-provider abstraction layer. Trigger with phrases like "migrate to claude", "openai to anthropic", "switch from gpt to claude", "multi-provider llm".

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。

Plan and execute a reversible migration from another search system or legacy index design to Algolia. Use when translating schemas, queries, relevance behavior, or production traffic. Trigger with "migrate to Algolia", "Algolia cutover", or "search engine migration".

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。

Analyze and execute a multi-workload migration into or across Adobe services with contract evidence, dependency waves, dual-run reconciliation, cost controls, and rollback. Use when the task requires adobe platform migration program. Trigger with "Adobe migration plan", "move workflow to Adobe", or "Adobe platform consolidation".

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。

Isolate complex Adobe failures across DNS/TLS, auth, entitlement, schema, async state, storage, Runtime, and downstream layers without leaking credentials or content. Use when the task requires adobe layered failure isolation. Trigger with "deep debug Adobe", "Adobe job stuck", or "Adobe intermittent failure".

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。

Rigorous, defensible email-spoofability verdict and SPF supply-chain risk analysis computed from published DNS alone. Deepens the record-level SPF/DMARC/DKIM/BIMI/MTA-STS/DNSSEC fetch recipes in the offensive-osint arsenal (§16.14) with the reasoning that section doesn't do: a priority-ordered composite verdict for whether an attacker can actually land header-From-spoofed mail in an inbox, and by which vector (exact-domain vs subdomain) — grounded in the single most-misunderstood distinction in email security: the envelope MAIL FROM that SPF authenticates vs the visible header From: that only DMARC governs. Explains precisely why SPF -all/~all alone is NOT spoof-proof without DMARC enforcement, and why SPF +all bypasses DMARC even under p=reject pct=100. Covers RFC 7208 §4.6.4's 10-DNS-lookup / 2-void-lookup PermError fail-open condition with a runnable stdlib-only lookup-counter script, plus the SPF-include-takeover supply-chain vector (an attacker re-registering a dead include inherits SPF-pass authority over the victim domain) with strict transient-vs-NXDOMAIN discrimination discipline so a temporary SERVFAIL is never mistaken for a takeover lead. Fully passive: DNS TXT reads only, no mail sent, no RCPT TO probe, no API keys. Use when auditing a domain's real spoofing resistance (not just its published records), explaining to a client why 'we have SPF -all' does not mean they're covered, investigating an SPF PermError or an unusually long include chain, evaluating a dead SPF include as a takeover lead, or writing a defensible spoofability finding for a deliverable.

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。

Organization-grade identity-fabric mapping: tenant/federation fingerprinting and the pre-auth user-ENUMERATION oracle methodology — enumeration and fingerprint only, never credential submission. Covers domain-to-tenant resolution (Microsoft getuserrealm.srf Managed/Federated namespace check, Entra OIDC metadata tenant-GUID extraction, Autodiscover v2), keyless Microsoft tenant-federation mapping (GetFederationInformation SOAP -> sibling-domain discovery, discover-only ROE, FEDERATED_WITH provenance edge held out of attack-path pivoting), Okta org-slug derivation + OIDC fingerprint + governed custom-domain enumeration, ADFS passive/active fingerprint + version inference, Google Workspace MX-correlated detection, generic OIDC (Auth0/Keycloak/Ping Identity/OneLogin/Duo) discovery, SAML metadata (5 paths), Azure AD Seamless-SSO Negotiate-challenge detection, Microsoft Defender for Identity (MDI) sensor-API presence check, the user-enumeration oracle methodology for Microsoft GetCredentialType (IfExistsResult semantics: exists / doesn't-exist / exists-in-federated-tenant / throttled) and Okta /api/v1/authn (errorCode differential), Medium-detectability discipline with a hard 20-candidate-per-tenant cap and admin/role interest-based ranking, and name x confirmed-email-pattern login-candidate synthesis that FAILS CLOSED with zero output when no org pattern is confirmed. Grounded directly in a production ASM implementation's sso_idp.py, tenant_recon.py, and core/email_patterns.py modules. Deepens — does not duplicate — offensive-osint skill's Identity Fabric endpoint reference with the tenant-federation MAP, the oracle WORKFLOW, and the candidate-SYNTHESIS methodology that reference lacks. Use when fingerprinting an organization's identity provider, mapping its tenant/federation boundary, running an authorized pre-auth user-enumeration pass, or synthesizing login candidates from harvested names to feed that oracle — never for password spray, credential submission, or auth bypass.

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。

Grida AI agent system work: `@grida/daemon` (DaemonServer, loopback HTTP perimeter, files/workspaces, secrets store, daemon discovery) and `@grida/agent` (the agent tenant: sessions, providers/BYOK, runtime/tool execution, skills discovery, prompts, tiers, sandbox hosts). Use for `packages/grida-daemon/**`, `packages/grida-ai-agent/**`, desktop sidecar protocol changes, agent chat transport, and bugs in agent state or streams. For pure Electron window, preload, menu, deep-link, or CDP work, use `desktop`.

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。

Grida Desktop Electron shell and release-impact work: BrowserWindow, preload, `window.grida`, menus, protocol/deep links, file associations, Forge, path-scoped bridge security, Electron-only UI bugs, and CDP / Playwright verification. Use for `desktop/`, `editor/app/desktop/**`, `editor/scaffolds/desktop/**`, `editor/lib/desktop/**`, `/desktop/*` CSP, GRIDA-SEC-004, and deciding whether linked-package or hosted-renderer changes require a native Desktop version bump or coordinated release. For implementing daemon/agent-tenant core behavior, use `agent-system` as well.

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。

Compile current scholarly evidence for a scientific manuscript or research brief. Use when the user explicitly asks to gather literature, references, background evidence, competing findings, or a manuscript research packet. Uses Parallel Search by default, Parallel Extract for source verification, Parallel Research for explicitly deep/exhaustive work, optional explicit Parallel Chat, and optional Perplexity only when requested or allowed as a failure fallback.

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 Parallel CLI for web search, URL extraction, deep research, structured data enrichment, entity discovery, and recurring web monitoring. Best for requests that explicitly need current web evidence, academic-source discovery, repeated entity lookups, exhaustive reports, or ongoing change tracking.

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。

Prototype pollution testing for JavaScript stacks. Use when user input is merged into objects (query parsers, JSON bodies, deep assign), when configuring libraries via untrusted keys, or when hunting RCE gadgets via polluted Object.prototype in Node or the browser.

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。

Entry P0 primary router and operating doctrine for HackSkills. Use when the task involves web application testing, API security assessment, recon, vulnerability triage, exploit path planning, authorized pentest, code audit, source-leak mining, middleware audit, SOC triage, detection engineering, incident response, or choosing the right next category skill before any deep topic skill. Also use when the user mentions 安全工程师, 渗透测试, 红队, 蓝队, 代码审计, 源码泄露, SRC. Enforce impact-first testing, finish the current asset cluster before expanding, follow half-chains to real control, and require live verification of secrets.

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。

Entry P1 category router for authentication and authorization. Use when testing login flows, sessions, object authorization, JWT, OAuth, CORS, CSRF, and enterprise SSO weaknesses before any deeper auth topic skill.

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。

Entry P1 category router for API security. Use when choosing between API recon, authorization, token abuse, and hidden-parameter workflows before any deeper API topic skill.

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。

Deep cultural adaptation of an already translated blog post for one target market: local examples, CTAs, legal references, statistic sources, and formality (Sie/du, tu/vous). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets. Use when the user says "localize blog", "cultural adaptation", "adapt for Germany", "lokalisieren", "localiser", "adaptar" and a translation already exists. Not for translating (use blog-translate), auditing a folder of translations (use blog-locale-audit), or the full write-translate-localize pipeline (use blog-multilingual).

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。

Cultural adaptation for translated content. Run AFTER blog-translate completes. Adjusts brand examples, CTAs, legal references, and formality for the target market (German, French, Japanese, Spanish, etc.). Deep cultural adaptation of translated blog posts. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets, plus a custom-locale template. Makes content feel locally authored, not translated. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "adapt for France", "lokalisieren", "localiser", "adaptar".

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。

向现有调研outline补充items（调研对象）。

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。

Add field definitions to existing research outline.

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。

向现有调研outline补充字段定义。

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。

对目标话题进行初步调研，生成调研outline。用于学术调研、benchmark调研、技术选型等场景。

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。