「bun」の検索結果

Maxim L2 pack. Bundles: L1.5 Brand & Design Pro + L1.6 Behavioral Intelligence + L1.2 MemPalace Pro. Primary framework: EAST (Easy, Attractive, Social, Timely).

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Maxim L2 pack. Bundles: All six L1 packs. Primary framework: Behavioral Moat Framing Doctrine (ADR-007).

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。

Create new Agent Skills for GitHub Copilot from prompts or by duplicating this template. Use when asked to "create a skill", "make a new skill", "scaffold a skill", or when building specialized AI capabilities with bundled resources. Generates SKILL.md files with proper frontmatter, directory structure, and optional scripts/references/assets folders.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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Add focused Bun unit tests for mission-critical behavior and edge cases — not blanket coverage.

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Meta-skill for creating Agent Forge skills under .claude/skills/ with SKILL.md, optional references/ and scripts/, and Bun scaffolds. Use when the user wants to add or author a skill, scaffold a new skill folder, or align skill docs with harness conventions (JSON script output, Beads for tasks).

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。

Tests Blazor components. bUnit rendering, events, cascading params, JS interop mocking.

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。

[BETA] Expert assistance for the Adobe I/O CLI plugin `@adobe/aio-cli-plugin-aem-rde` — the `aio aem rde` / `aio aem:rde` command tree used to deploy, inspect, log-tail, snapshot, and troubleshoot AEM Rapid Development Environments (RDEs). Activate ONLY when the user explicitly references RDE concepts: 'AEM RDE', 'Rapid Development Environment', `aio aem rde`, `aio aem:rde`, `aem-rde`, RDE snapshots, RDE deploy/install, `rde install`, `rde inspect`, `rde status`, `rde history`, `rde reset`, the `@adobe/aio-cli-plugin-aem-rde` package, or Cloud Manager program/environment configuration that is specifically for an RDE environment. Do NOT activate on generic AEMaaCS phrases like 'deploy to AEM Cloud', 'push my bundle', 'tail the publish log', 'cloud sandbox', or unqualified 'dispatcher-config / frontend / env-config deployments' — those belong to Cloud Manager pipelines, not RDE. This skill is in beta. Verify all outputs before applying them to production projects.

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。

Lighthouse audits, bundle analysis, image optimization, font loading, Core Web Vitals tracking, and performance monitoring setup.

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。

E2E artifact handling routing. Use when traces, videos, screenshots, reports, or failure bundles need controlled repository-local placement; do not use for simple unit tests or production-mutating E2E flows.

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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".

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Turn a project directory or a website URL into a short, shareable launch video with music, motion, and share copy. One file, no bundled assets — built entirely by the model with the tools already on the machine. Use when someone says "/brag-slim", "let's /brag about this", "brag about <url>", "make a launch video", or wants to show off what they built. If the /brag skill is also installed, let /brag handle those phrases; it hands off here on Opus 5.5.

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Social engineering attack techniques beyond email phishing for authorized red team and physical penetration testing engagements. Covers pretexting methodology (persona creation, authority and urgency psychological triggers, rapport building), vishing (voice phishing via caller ID spoofing, IVR system exploitation, VoIP infrastructure setup with Twilio/Asterisk), smishing (SMS-based phishing, carrier gateway abuse, short code impersonation), physical social engineering (tailgating and piggybacking, RFID badge cloning with Proxmark3, lock picking and bypass, dumpster diving for sensitive documents), USB drop attacks (Rubber Ducky keystroke injection, Bash Bunny multi-vector payloads, O.MG cable covert implants, BadUSB firmware attacks), watering hole attack planning and execution, and OSINT-driven targeting (LinkedIn harvesting, organizational chart reconstruction, employee pattern analysis). Integrates with the Social Engineering Toolkit for attack automation, Proxmark3 for RFID/NFC cloning, USB Rubber Duc...

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External recon for software supply-chain attack surface — package-namespace squatting candidates, dependency-confusion vulnerabilities, GitHub Actions injection openings, container image registry exposure, SBOM mining, internal-package-name leakage, and CI/CD configuration exposure. Reconnaissance and identification ONLY — actual package publishing / typosquat attacks are EXTERNAL-OFFENSIVE and require explicit written sign-off because they can affect the entire npm/PyPI ecosystem. Use when the target has a public GitHub org, when their build artifacts/SBOMs are reachable, when their docker images are on Docker Hub/GHCR, or when you find internal package names in their JS bundles.

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Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation ...

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Cloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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Use when introducing a feature flag system, choosing between release flags / experiment flags / operational flags / kill switches / permission flags, designing percentage rollouts, building kill-switch + circuit-breaker patterns, structuring evaluation contexts (user IDs, plan tier, region), or building flag-cleanup discipline. Triggers: LaunchDarkly / GrowthBook / Unleash / Flagsmith / OpenFeature, percentage ramp, sticky bucketing, kill switch wired to alerting, "we still have flags from 2 years ago", flag debt, OpenFeature provider, evaluation context, default value on provider failure. NOT for A/B test statistical analysis (separate skill), traffic-split routing at the edge, build-time bundler defines, or environment-based config.

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Verifies build output integrity after code changes. Runs builds, validates artifact structure, checks for regressions in bundle size, asset references, and static export completeness. The last line of defense before a bad deploy ships.

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Produces a narrow-interval quality signal for a WinDAGs skill that a third party can verify without inspecting model weights or method internals. The mechanism is attribution-kNN over a tamper-evident outcome log (task→skills→accept/reject store), combined with a conformal-prediction calibration certificate that provides a formal coverage guarantee. Thompson/Beta sampling is explicitly rejected as a category error: it produces a selection signal for stationary i.i.d. rewards, not an attestation signal for context-dependent LLM output quality. The resulting bundle — outcome-log Merkle root + conformal threshold + optional TEE guardrail signature — constitutes a "narrow-interval trust" credential: verifiable, bounded, and internals-opaque.

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Own whether a multi-document product-architecture binder is internally consistent, complete against its stated customer/contingency/architecture coverage, and honest about which older product ambitions it has absorbed, superseded, deferred, contradicted, orphaned, or rejected. Use when running a binder Architect of Record pass, before an implementation chain cites a binder chapter as ready, when a proof-gate owner is missing, or when reconciling the binder against the older ambition corpus (website, plans, examples, ADRs). NOT for auditing a single Claude Skill bundle's structure or frontmatter (use skill-hygiene), rendering a single-PM accept/reject verdict on one finished deliverable (use port-daddy-user-surrogate-pm-review), or sequencing/stewarding a roadmap's sidequests once a gap or operator decision has been surfaced (use legible-roadmap-with-sidequests).

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Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Compares the version-pinned A2A, MCP, and JSON-RPC role boundaries covered by this bundle; OpenAI and LangChain-specific APIs require their own current sources. Teaches when to use rigid schemas versus free-form content with validation, typed versus untyped boundaries, and streaming versus batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).

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。

Interacting with Mediabunny

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Interacting with Mediabunny

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。