「cti」の検索結果

Generate interactive Three.js canvases in six modes: narrative particle phase cycles, WebGPU spinner/loaders, infinite gallery tunnels, animated glTF specimens, vinyl showcase with webcam reflection, glass hero sections with physically-accurate refraction/dispersion/iridescence. Ships a reusable Phosphor Vigil FX post-processing module (CRT composite, scanlines, chromatic aberration). Self-contained HTML output. Triggers on particle system, ambient 3D canvas, WebGL art, spinner, loader, infinite tunnel, glTF animation, CRT post-processing, vinyl record, webcam reflection, 3D product showcase, glass hero, 3D glass, refraction, dispersion, iridescent glass, frosted glass panes, glass material.

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Design and build runnable iOS UI mockups in SwiftUI, including UI direction, multiple visual or interaction variants, realistic sample data, state switching, Xcode Previews, and Simulator validation. Use when the user wants to explore what an iOS screen should look like, compare SwiftUI UI ideas, create a clickable native prototype, validate an app flow before production implementation, or asks for a SwiftUI mock, iOS mockup, native prototype, 画面モック, UI案, SwiftUIで動くモック, or 実際に触れるiOSモック.

GitHub Actions の CI 失敗を検出・修正・再検証するスキル。 gh コマンドで PR の CI 状態を確認し、失敗時はログを取得して原因を分析、 コードを修正して push、CI が通るまでループする。 Use when: CI が落ちた、CI を直したい、PR のチェックが失敗している、 GitHub Actions のエラーを修正したい、CI を通したい。 Triggers: "CI", "ci-fix", "CI落ちた", "CI失敗", "checks failed", "GitHub Actions", "workflow failed", "CI通して", "CI修正"

Investigate root causes and manage CAPAs (Corrective and Preventive Actions) for compliance deviations. Covers investigation method selection (5-Why, fishbone, fault tree), structured root cause analysis, corrective vs preventive action design, effectiveness verification, and trend analysis. Use when an audit finding requires a CAPA, when a deviation or incident occurs in a validated system, when a regulatory observation needs a formal response, when a data integrity anomaly requires investigation, or when recurring issues suggest a systemic root cause.

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Apply GitHub repository security protections tier by tier — rulesets, read-only Actions token, secret scanning + push protection, Dependabot, and (gated) required status checks / required PR with a GitHub App bypass for a CI auto-commit bot. Mutating and confirmation-gated: always assess first, apply the no-regret baseline, then decide required checks separately. Use when hardening a public user-owned repo after an audit, when a repo has no branch protection, when adding required checks without breaking a bot that pushes to the default branch, or when provisioning a GitHub App bypass actor for trusted automation.

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Classify gate call variants in a minified JavaScript bundle. Covers context-window extraction around a flag occurrence, identification of 4–6 reader variants (sync boolean, sync config-object, bootstrap-aware TTL, truthy-only, async bootstrap, async bridge), default-value extraction (boolean / null / numeric / config-object literal), conjunction detection across `&&` predicates, kill-switch inversion detection, and production of a gate-mechanics record that feeds probe- feature-flag-state. Use when a flag's behavior cannot be inferred from its name alone, when the binary uses multiple reader libraries, or when config-object gates carry structured schemas distinct from boolean gates.

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Read-only audit of a GitHub repository's security posture. Gathers ref protection (rulesets AND classic branch protection), Actions token permissions, code and supply-chain features (Dependabot, secret scanning, push protection, CodeQL), and repo hygiene toggles via `gh api`, then classifies findings against essential / recommended / advanced tiers into a PASS/GAP report. Makes NO changes. Use when reviewing a repo before open-sourcing or a release, auditing a public user-owned repo whose CI auto-commits to the default branch, verifying a hardening change actually took effect, or producing a baseline security posture report for a repository.

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Angular Router (built-in `@angular/router`) — route configuration for standalone and NgModule projects, functional guards (Angular 14.1+), lazy loading, route resolvers, typed params via signals/observables, programmatic navigation, route data and meta. Use this skill to: - Configure routes (standalone-style or NgModule-style). - Use functional guards (canActivate as function, preferred over class-based in 17+). - Lazy-load components or feature modules. - Implement auth guards via route meta + functional guards. - Read params/queries via `inject(ActivatedRoute)` + signals or RxJS. Do NOT use this skill for: - General conventions (see angular-conventions). - State management (see angular-state-and-rx). - Forms (see angular-forms). - Testing routes (see angular-testing).

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Trigger when: (1) User mentions "manimgl" or "ManimGL" or "3b1b manim", (2) Code contains `from manimlib import *`, (3) User runs `manimgl` CLI commands, (4) Working with InteractiveScene, self.frame, self.embed(), ShowCreation(), or ManimGL-specific patterns. Best practices for ManimGL (Grant Sanderson's 3Blue1Brown version) - OpenGL-based animation engine with interactive development. Covers InteractiveScene, Tex with t2c, camera frame control, interactive mode (-se flag), 3D rendering, and checkpoint_paste() workflow. NOT for Manim Community Edition (which uses `manim` imports and `manim` CLI).

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Use when adding cross-cutting concerns to durable functions — structured logging or tracing across all functions, error tracking with Sentry, payload encryption for sensitive data, dependency injection of clients (DB, Stripe, etc.) into function handlers, custom telemetry, or behavior that should apply uniformly across many functions. Covers Inngest middleware lifecycle, creating custom middleware, dependencyInjectionMiddleware, @inngest/middleware-encryption, @inngest/middleware-sentry, and custom middleware patterns.

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Executes authorized attack simulations against Active Directory environments to identify misconfigurations, weak credentials, dangerous privilege paths, and exploitable trust relationships that could lead to domain compromise. The tester uses BloodHound for attack path analysis, Mimikatz for credential extraction, and Impacket for protocol-level attacks including Kerberoasting, AS-REP Roasting, and delegation abuse. Activates for requests involving Active Directory pentest, AD attack simulation, domain compromise testing, or Kerberos attack assessment.

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Use when you need to query an OpenCTI instance — is this IOC already known, what entities/reports/campaigns exist for an actor — or push new intel into it — creating indicators/observables, labelling, TLP markings, relationships, or importing a STIX 2.1 bundle. Two-way integration. Commonly invoked by /ip-investigation and friends to check whether an indicator is already in your knowledge base, and by analytical skills that want to publish their findings back to OpenCTI. Reads $OPENCTI_URL and $OPENCTI_TOKEN.

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Optimize oversized agent instruction files using progressive disclosure. Handles CLAUDE.md (Claude Code), AGENTS.md (OpenAI Codex / GitHub Copilot agents), and copilot-instructions.md (GitHub Copilot). Auto-detects all three formats in your repo, analyzes content tiers, creates sub-documents using each format's native mechanism, and rewrites the main file with zero information loss. Triggers: optimize CLAUDE.md, AGENTS.md too long, reduce copilot-instructions.md, agent instructions file too large, shrink context file, apply progressive disclosure, instructions file bloated

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Detect and exploit SQL injection vulnerabilities using both manual techniques and automated tools. Use this skill when testing web applications for database injection flaws including UNION-based, error-based, blind boolean, blind time-based, and out-of-band SQL injection. Covers WAF bypass, second-order SQLi, authentication bypass, and full database extraction with sqlmap.

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Test for indirect prompt injection vulnerabilities where malicious instructions are injected through external data sources (websites, emails, documents, database records) that the LLM processes. Use this skill when assessing LLM-integrated applications that process user-generated content, retrieve web pages, parse emails, or read documents. Covers injection via web content, email bodies, user profiles, and database records that are fed to LLM context.

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Test Large Language Models for direct prompt injection vulnerabilities where user input overrides system instructions, extracts system prompts, bypasses safety filters, or causes unauthorized actions. Use this skill when assessing chatbots, AI assistants, LLM-powered tools, or any application that processes natural language input through an LLM. Covers role-playing attacks, instruction hierarchy exploitation, multi-turn manipulation, and context window abuse for comprehensive AI security testing.

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Use when hunting GitHub Actions cache poisoning vulnerabilities where an attacker can inject malicious content into the CI/CD cache and have it restored by a privileged downstream workflow. Trigger on: "cache poisoning", "actions/cache", "actions/setup-node", "node_modules cache", "GitHub Actions cache", "pnpm cache", "LRU eviction", "10GB limit", "Cacheract", "poisoned cache", "workflow cache attack", supply chain via CI cache, "ng-renovate", "cache stuffing", scheduled workflow cache restore, shared cache key, "hashFiles package.json", cross-workflow cache, PR workflow release workflow same key, "npm install prefer-offline", Cacheract, Gato-X, supply chain npm token.

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Review computational protein or gene function predictions and fill PredictionReview YAML files using the COR/CNN/LSP/UNC/PLI/NPI/REP biological-validity taxonomy. Use for ProtNLM, DeepECTF, BioReason/GO-GPT, InterPro2GO, PANTHER/IBA, CLEAN, GloEC, MAPred, ProteinInfer, or other predicted EC/GO annotations, including audits of the evidence and reasoning in existing prediction reviews.

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Turns reverse-engineering findings into durable YARA detections: selecting stable code constructs and constants over volatile strings, extracting opcode/byte patterns with wildcards, and validating rules for low false positives. Activates for requests to write a YARA rule from reversed code, create a detection signature, or convert RE findings into hunting rules.

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Hunts for unusual outbound network connections by flagging direct-to-IP traffic, uncommon ports, rare destinations, high data-egress ratios, and connections from unexpected processes in network telemetry. Activates for requests to hunt unusual outbound traffic, detect suspicious egress, or find anomalous external connections.

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Handle sales objections using tactical empathy. Use when the user says "how do I handle this objection", "prospect said [X]", "they pushed back on price", "they said they're not ready", "how to respond to 'we already have a solution'", "they said 'send me more information'", "objection response", "they went dark after the proposal", "how to handle 'we don't have budget'", or wants to craft a response to a specific sales objection.

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Design Invocable Apex actions that return deterministic, agent-friendly errors instead of surfacing raw exceptions to the LLM. NOT for authoring the action itself — @InvocableMethod schema, labels, security context — use agentforce/custom-agent-actions-apex. NOT for the Apex tests that force each error branch — use agentforce/agent-action-unit-tests.

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Use when creating, configuring, auditing, or troubleshooting an Agentforce agent end-to-end: agent definition, agent user setup, channel assignment, system instructions, activation, and lifecycle management. Triggers: 'create agentforce agent', 'agent not appearing to users', 'how to activate agent', 'agent channel setup', 'agent lifecycle', 'deploy agent to production'. NOT for designing what the agent can DO — an agent that looks up an order, checks a case, or creates a record is action design, use agentforce/agent-actions. NOT for topic boundary design — use agentforce/agent-topic-design.

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Configure Einstein Activity Capture (EAC) for an org: enable the feature, create Configuration profiles, set auth type (User-Level or Org-Level OAuth), define email and calendar sync scope, excluded domains and privacy settings, assign users, verify sync health. NOT for querying synced emails or events in SOQL, Apex or reports — use apex/einstein-activity-capture-api. NOT for Opportunity Scoring or Pipeline Inspection — use agentforce/einstein-copilot-for-sales.

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。