Cloud, CI/CD, monitoring, and deployment (6.8K skills)
Email infrastructure for AI agents. Create accounts, send/receive emails, manage webhooks, and check karma balance via the AgentMail API.
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Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
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Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.
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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.
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Dağıt: and monitor Canary Tokens via the Thinkst Canary API for deception-based breach Tespit using web bug tokens, DNS tokens, document tokens, and AWS key tokens.
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Envelope encryption is a strategy where data is encrypted with a data encryption key (DEK), and the DEK itself is encrypted with a master key (KEK) managed by AWS KMS. This approach allows encrypting
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SSL/TLS certificate lifecycle management encompasses the full process of requesting, issuing, Dağıt:ing, monitoring, renewing, and revoking X.509 certificates. Poor certificate management is a leading
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Dağıt:s deception-based honeytokens in Active Directory including fake privileged accounts with AdminCount=1, fake SPNs for Kerberoasting Tespit (honeyroasting), decoy GPOs with cpassword traps, and fake BloodHound paths. Monitors Windows Security Event IDs 4769, 4625, 4662, 5136 for honeytoken interaction. Use implementing yaparken AD deception defenses for Tespit etme lateral movement, credential theft, and reconnaissance.
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Integrate gitleaks and trufflehog into CI/CD pipelines to tespit etmeleaked secrets before Dağıt:ment
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Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret Tespit.
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Provides digital forensics and signal analysis techniques for CTF challenges. Use when analyzing disk images, memory dumps, event logs, network captures, cryptocurrency transactions, steganography, PDF analysis, Windows registry, Volatility, PCAP, Docker images, coredumps, side-c
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Dark-themed SVG architecture/cloud/infra diagrams as HTML.
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Deploy a new LLM model via LiteLLM (GitOps) and/or Azure (Terraform + node backend), add it to the ai toolkit, create the required pull requests, and verify end-to-end. Use when rolling out a model to any environment, adding a model to the toolkit, troubleshooting "model not available" errors, or finding pricing/token limits/model ids for any provider.
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Use to start a new product on Cradle or to add the Cradle skeleton to an existing repository — writes cradle.json, the project-facts instruction (.apm/instructions/project.instructions.md), documents/{ddd,ai-notes,infra-design,codebase} templates, CI, and a compiling Lean executable-spec scaffold with a minimal example domain, mockup and CLI.
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Use for the infrastructure design phase between domain exploration and Lean formalization — deriving non-functional requirements from the Lean model, deciding environments (test/local/prod), identity provider, the relational database's product, version and configuration (the storage kind is fixed to relational), ID representation, and the list of things NOT to build. Produces documents/infra-design with INFRA-D/A/Q entries.
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Use for the infrastructure implementation phase after the backend follows the model — turning documents/infra-design decisions into infra/ (local container stack, production IaC), wiring cradle.json infra.up / infra.containers, adding IaC validate and image build steps to CI, and, once E2E passes, applying production once in a sandbox and recording it in the deployment table. Not for designing infrastructure (infra-design).
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Use when creating new skills, editing existing skills, or verifying skills work before deployment
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Claude Code プラグインを Codex CLI 互換形式に変換。SKILL.md → .agents/skills/、agents → .agents/skills/、AGENTS.md 生成。「deploy」「codex」「Codex 変換」「エクスポート」などで自動適用。
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アプリやコードが壊れたとき、被害を広げずに安全な状態へ戻すための復旧ワークフロー。「壊れた」「動かなくなった」「エラーが出るようになった」「元に戻したい」「前の状態に戻して」「デプロイしたらおかしくなった」「昨日まで動いてた」といった訴えがあったら、原因調査や修正を始める前にまずこのスキルを使うこと。特にエンジニアが常駐しないチームでは、ユーザーがパニック状態で曖昧な依頼をしてくることが多いので、破壊的な回復手段（git reset --hard, git clean, force push等）に飛びつかず、このスキルの手順で退避→切り分け→安全な復旧を行う。
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ディスパッチャーのコンテキストを圧迫したまま session を続けるのを避けるため、 monitoring 状態（active workers / 直近 polling cursor / pending escalations）を handover ファイルに書き出し、secretary の指示で /clear → /dispatcher-resume の 流れで新しいディスパッチャー session を開始する準備をする。 Secretary から DISPATCHER_HANDOVER peer message を受領したとき、または ディスパッチャー自身が context が長くなったと判断したときに使う。 context-handover watcher が `/dispatcher-handover auto op=<OP>` を打鍵したときも使う。
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/dispatcher-handover で書き出した handover ファイルを読み込み、 ディスパッチャーを新しい session で復帰させる。/clear 直後の最初のターンで使う。 state.db の dispatcher_pane_id / dispatcher_peer_id を atomic に更新し、 worker monitoring の /loop 3m を再開する。 secretary が /clear の後にディスパッチャーペインへ /dispatcher-resume を打鍵したときに使う。 context-handover watcher が `/dispatcher-resume auto op=<OP>` を打鍵したときも使う。 /org-start ではない（ワーカー・窓口は生きている前提。キュレーターは常駐しない）。
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インフラ基盤構成設計エージェント - AWS/Azure/GCP/OpenShift向けのKubernetes・IaC構成を設計・生成。/design-infrastructure で呼び出し。
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コスト見積もりエージェント - クラウドインフラ、ScalarDB、その他ライセンスの見積もりを作成。/estimate-cost [対象パス] で呼び出し。
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ScalarDBサイジング見積もりエージェント - Enterprise/OSSエディション別のインフラ構成・Pod数・コストを対話形式で見積もり。/scalardb-sizing-estimator で呼び出し。
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