「data」の検索結果

Defines measurable performance budgets for bundle size, API latency, database queries, and render times. Provides enforcement strategies and monitoring plans. Use for "performance budgets", "performance monitoring", "web vitals", or "optimization targets".

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。

Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".

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。

Raw mechanical interfaces fusing Swiss typographic print with military terminal aesthetics. Rigid grids, extreme type scale contrast, utilitarian color, analog degradation effects. For data-heavy dashboards, portfolios, or editorial sites that need to feel like declassified blueprints.

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。

Builds end-to-end browser tests for critical user flows using Playwright or Cypress. Includes selector strategies, test data management, page objects, and visual regression testing. Use for "E2E testing", "browser tests", "Playwright", or "Cypress tests".

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。

Builds repeatable evaluation systems with golden datasets, scoring rubrics, pass/fail thresholds, and regression reports. Use for "LLM evaluation", "testing AI systems", "quality assurance", or "model benchmarking".

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。

Produces build artifacts with Software Bill of Materials (SBOM) and supply chain metadata for security and compliance. Use for "artifact publishing", "SBOM generation", "supply chain security", or "build provenance".

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。

Scans repository structure and generates comprehensive architecture documentation including system overview, entry points, module relationships, data flow diagrams, and "edit here for X" guides. Creates ARCHITECTURE.md for onboarding and navigation. Use when users request "document the codebase", "explain the architecture", "create onboarding docs", or "map the system".

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 when AI contribution metadata must match the actual workflow, when model alias and dated identifiers need auditing, when verified and fabricated citation counts feed a release decision, or when a venue's AI disclosure statement needs evidence behind it.

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 when choosing or configuring MCP servers for research work, when a literature, reference manager, or scholarly search server needs a trust check before installation, or when an existing research tool stack needs a data flow and permission audit.

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 when selecting a statistical test with AI consultation, when assumptions need checking against the actual data, when an analysis plan or decision log must be written before running anything, or when results need APA-style reporting with effect sizes.

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 for the search-planning stage of a literature review, when database lanes and language layers must be chosen, when DOI coverage policy is unclear, or when inclusion and exclusion criteria need drafting before any source is read; not for running the screening and PRISMA pipeline of a formal review, which is prisma-scoping-review-pipeline.

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 when a complete research workflow — its instructions, skills, data boundaries, and tool connections — must be assessed for portability across AI agents or environments, so each component is explicitly mapped before migration rather than assumed to transfer.

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 when authorship order, CRediT contribution roles, or AI-assistance attribution must be recorded transparently for a manuscript, when an author dispute needs an evidence trail, or before a contributorship statement is required at submission; this skill maintains the human-attribution ledger of who contributed what and in which role (authorship order, CRediT taxonomy, revision responsibilities), which is distinct from the disclosure-metadata audit owned by ai-disclosure-auditor.

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。

Wi-Fi reconnaissance methodology — adapter selection, monitor mode and packet injection setup, regulatory domain handling, multi-band airspace mapping, hidden SSID discovery, BSSID/ESSID/channel/PMF/encryption fingerprinting, client probe analysis, vendor OUI lookup, war-driving with Kismet/airodump-ng/Wigle, and structured airspace data capture for downstream attacks. Use at the start of any wireless engagement to build the target map before active attacks; covers 2.4 GHz, 5 GHz, and 6 GHz (Wi-Fi 6E) bands and adapter compatibility for each.

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。

Hunt shadow / zombie / undocumented API surface (OWASP API9 Improper Inventory Management) — enumerate the full API version history (v1/v2/beta/legacy paths, header- and subdomain-based versioning), pull and diff every reachable OpenAPI/Swagger spec (including ones only findable via the Wayback Machine), and behaviorally diff old vs. current versions for auth/rate-limit/validation regressions rather than just response-shape differences. Distinct from hunt-api-misconfig, which owns exploitation once you have a spec or endpoint (mass assignment, JWT, OData, Swagger-chain attacks); distinct from hunt-subdomain, which owns host-level discovery. This skill owns the version-inventory and behavioral-diff workflow itself. Use when the target has versioned API paths, multiple specs, a changelog referencing deprecated endpoints, or a mobile app whose hardcoded backend calls look older than the current web app's.

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。

Hunt gRPC vulnerabilities — server reflection enabled (enumerate all services/methods), missing authentication / metadata-stripping on internal endpoints, plaintext gRPC over HTTP/2, internal endpoint disclosure, proto file leakage, gRPC-Web/grpc-gateway transcoding injection, and HTTP/2 Rapid Reset DoS (CVE-2023-44487). Use when target exposes port 50051 / 443 / 8443 / 9090 with HTTP/2, when grpcurl/grpcui detects reflection, when an Envoy or grpc-gateway proxy is fronting a microservice, or when recon reveals a microservice architecture.

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。

Hunt Local File Inclusion (LFI), Remote File Inclusion (RFI), and Path Traversal — /etc/passwd read, log poisoning → RCE, PHP filter-chain RCE (no upload needed), php:// / data:// / zip:// / phar:// wrappers, RFI via allow_url_include, directory traversal read/write/delete. Covers OOB/blind LFI confirmation and false-positive discipline. Use when hunting file-include or path-traversal bugs on any target.

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。

Hunt JWT cryptographic failures — alg:none signature-stripping and RS256→HS256 key-confusion that let an attacker forge a token for any identity (e.g. an admin) without knowing a secret. Use when the app authenticates with a JSON Web Token (an `eyJ...` Bearer token in the Authorization header, a cookie, or a login response). This skill OWNS JWT signature/crypto forgery (alg:none, key confusion, kid/jku header injection); hunt-ato covers JWT as one ATO path, hunt-auth-bypass covers SSO/SAML token trust, hunt-api-misconfig covers non-crypto JWT handling. Critical when a forged token grants access to another user's data or an admin-only endpoint.

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。

Hunt Host Header Injection — password reset poisoning → ATO, web cache poisoning via unkeyed Host/X-Forwarded-Host, routing-based SSRF (Host picks upstream → cloud metadata/internal services), path-override SSRF/ACL-bypass (X-Original-URL/X-Rewrite-URL), OAuth redirect_uri/issuer poisoning, and absolute-URL link poisoning in emails. High to Critical when it reaches ATO or mass cache poisoning. Built on public Host-header research (PortSwigger 'Practical web cache poisoning' + James Kettle, and the classic password-reset-poisoning class). Use on any forgot-password flow, CDN/reverse-proxy-fronted app, OAuth/OIDC endpoint, or absolute-URL-in-email feature.

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。

Hunt NoSQL Injection — MongoDB operator injection ($where, $regex, $gt, $ne), CouchDB, Redis command injection, auth bypass via NoSQLi, data dump. Use when target uses MongoDB/Mongoose, CouchDB, Redis, or shows NoSQL error messages.

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。

Server-Side Request Forgery testing checklist: SSRF discovery, blind SSRF with out-of-band, cloud metadata endpoints (AWS/GCP/Azure), SSRF filter bypass techniques (IP encoding, DNS rebinding, redirect chains), and SSRF to RCE escalation. Use for web app SSRF testing and bug bounty.

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 Windows privilege escalation methodology for offensive security engagements. Covers the full attack surface from a standard user shell to NT AUTHORITYSYSTEM: token impersonation via SeImpersonate and SeAssignPrimaryToken privileges using JuicyPotato, PrintSpoofer, GodPotato, SweetPotato, and RoguePotato; service misconfigurations including unquoted service paths, weak service DACLs, writable service binaries, and insecure service creation permissions; AlwaysInstallElevated MSI exploitation; DLL hijacking through search order abuse, phantom DLL loading, and writable PATH directory injection; UAC bypass techniques via fodhelper.exe, eventvwr.exe, CMSTP, and environment variable manipulation; scheduled task abuse for writable task actions and new task creation; registry autorun exploitation for persistence and escalation; PrintNightmare (CVE-2021-34527) for remote and local privilege escalation; and credential harvesting from SAM database extraction, DPAPI blob decryption, LSA secret dumping,...

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。

Structured OSINT methodology framework: target definition, source selection, collection workflows, data correlation, timeline reconstruction, and reporting. Use to guide systematic OSINT campaigns or teach OSINT methodology.

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Triage ASM/recon output for ownership before testing — separate the target's real assets from namespace-collision noise. Automated recon keyword-matches on the brand name, so for any target whose name is a common/dictionary word, the output is dominated by assets belonging to UNRELATED same-named companies (repos, cloud buckets, mobile apps, breach corpora, typosquats). Built from an authorized engagement where an ASM report's 'Criticals' were overwhelmingly false positives and the combo/repos/mobile/bucket lists were polluted with unrelated same-named orgs. Use at the START of any engagement, immediately on receiving any ASM/recon/OSINT dataset, BEFORE testing anything.

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。