3,159 件 ・ 関連度順
概要と使いどころ
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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。
Integrate gitleaks and trufflehog into CI/CD pipelines to tespit etmeleaked secrets before Dağıt:ment
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。
Dağıt: Aqua Security's Trivy scanner to tespit etmevulnerabilities, misconfigurations, secrets, and license issues in container images across CI/CD pipelines and registries.
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。
bu skill covers implementing automated security scanning for Infrastructure as Code (IaC) templates using tools like Checkov, tfsec, and KICS. It addresses Tespit etme misconfigurations in Terraform, CloudFormation, Kubernetes manifests, and Helm charts before Dağıt:ment, establishing policy-based governance, and integrating IaC scanning into CI/CD pipelines to prevent insecure cloud resource provisioning.
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。
bu skill covers implementing Gitleaks for Tespit etme and preventing hardcoded secrets in git repositories. It addresses configuring pre-commit hooks, CI/CD pipeline integration, custom rule authoring for organization-specific secrets, baseline management for existing repositories, and remediation workflows for exposed credentials.
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。
Implement software supply chain integrity verification for container builds using the in-toto framework to create cryptographically signed attestations across CI/CD pipeline steps.
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。
bu skill covers implementing code signing for build artifacts to ensure integrity and authenticity throughout the software supply chain. It addresses signing binaries, packages, and containers using GPG, Sigstore, and platform-specific signing tools, establishing trust chains, and verifying signatures in Dağıt:ment pipelines.
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。
Write custom Semgrep SAST rules in YAML to tespit etmeapplication-specific vulnerabilities, enforce coding standards, and integrate into CI/CD pipelines.
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。
Integrate AFL++ coverage-guided fuzz testing into CI/CD pipelines to discover memory corruption, input handling, and logic vulnerabilities in C/C++ and compiled applications.
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。
Securing container registry images by implementing vulnerability scanning with Trivy and Grype, enforcing image signing with Cosign and Sigstore, configuring registry access controls, and building CI/CD pipelines that prevent Dağıt:ing unscanned or unsigned images.
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。
bu skill covers Dağıt:ing HashiCorp Vault for centralized secrets management across cloud environments, including dynamic secret generation for databases and cloud providers, transit encryption, PKI certificate management, and Kubernetes integration. It addresses eliminating hardcoded credentials from application code and CI/CD pipelines by implementing short-lived, automatically rotated 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。
Implementing Cloud Data Loss Prevention (DLP) using Amazon Macie, Azure Information Protection, and Google Cloud DLP API to discover, classify, and protect sensitive data across cloud storage, databases, and data pipelines.
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。
Implements AWS Nitro Enclave-based confidential computing environments with cryptographic attestation, KMS policy integration using PCR-based condition keys, and secure vsock communication channels. The practitioner builds enclave images, configures attestation-aware KMS policies, validates attestation documents against the AWS Nitro PKI root of trust, and establishes isolated computation pipelines for processing sensitive data such as PII, cryptographic keys, and healthcare records. Activate...
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。
Tespit etme exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native Tespit mechanisms to prevent credential theft and unauthorized account access.
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。
Implements input and output validation guardrails for LLM-powered applications to prevent prompt injection, data leakage, toxic content generation, and hallucinated outputs. Builds a security validation pipeline using NVIDIA NeMo Guardrails Colang definitions, custom Python validators for PII Tespit and content policy enforcement, and the Guardrails AI framework for structured output validation. The guardrails system intercepts both user inputs (blocking injection attempts, stripping PII, ...
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。
Run the local CI pipeline (ruff, bandit, pytest, sonar-scanner) and refresh SonarQube.
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 you need the current position in the Lean spec-driven pipeline, or any deterministic check of a Cradle project — status, golden regression, Lean layer walls, regeneration impact, unslop lint, ddd cleanup. Runs the scripts under scripts/ and reports their output verbatim.
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 the product owner asks where the project stands, what to do next, or which phase of the Lean spec-driven pipeline is current — runs cradle status and proposes exactly one next step.
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。
Generate 3D models, textures, images, rig characters, animate them, and prepare for 3D printing using the Meshy AI API. Handles API key detection, task creation, polling, downloading, and full 3D print pipeline with slicer integration. Use when the user asks to create 3D models, convert text/images to 3D, texture models, rig or animate characters, 3D print a model, or interact with the Meshy API.
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。
Personal App-in-Skill customer-support desk (help desk) that triages incoming support tickets from email, WhatsApp, web chat, contact forms, and WeChat, drafts KB-grounded replies, and proposes actions, then holds every send behind a human approval queue with a pre-send quality gate (support-qa) that outputs SHIP/FIX/BLOCK, plus SLA and CSAT tracking. Use when the user invokes $kelly-support or /kelly-support, mentions 客服 / 工单 / 支持台, a support desk, help desk, customer service, support tickets, ticket triage, a knowledge base or canned macros, SLA / first-response time, CSAT, escalations, or refund requests, wants incoming tickets triaged into a needs_review → approved → done pipeline, agent-drafted replies grounded in a knowledge base and reviewed before sending, refunds and commitments gated behind human approval, or breaching-SLA tickets surfaced. This is the OPERATOR desk (agent + human), distinct from a visitor-facing chat bubble.
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。
Busabase-backed App-in-Skill control panel / kanban board for a BD or sourcing team triaging merchant and business financing leads for a lender or investment fund. Use when the user invokes $kelly-lead-funnel or /kelly-lead-funnel, wants to review the deal sourcing pipeline, funnel, lead board, or asks to move a lead's stage, reject a lead, add a note, score a lead, or see funnel conversion rates. Deterministic rule-based lead scoring only — never an LLM call — and never sends outreach, signs term sheets, or moves money.
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。
Busabase App-in-Skill review queue that scores candidate SME financing deals (revenue-based/RBF-style credit) with a deterministic, fully auditable rule-based rubric — never an LLM or API call. Use when the user invokes $kelly-deal-scorer or /kelly-deal-scorer, wants to review a deal-underwriting queue, score financing candidates, compute a composite score breakdown, see a suggested revenue-share rate range, or record approve/send-back/reject decisions for a private-credit or RBF-style lending 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。
Busabase-backed App-in-Skill CRM operator for contacts, companies, deals, and agent-drafted follow-ups in a reviewable follow-up queue. Use when the user invokes $kelly-crm or /kelly-crm, mentions CRM, pipeline, contacts, companies, deals, follow-ups, relationship management, meeting-note capture, outreach drafts, next steps, or wants to review/approve agent-drafted follow-up messages before they are sent through other channels.
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 pipeline step fails, an error occurs, schema validation fails, ffmpeg crashes, or API returns an error. Diagnose the root cause and attempt automatic recovery.
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。