「final」の検索結果

Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.

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GDPR and German DSGVO compliance automation. Scans codebases for privacy risks, generates DPIA documentation, tracks data subject rights requests with Art. 12(3) one-month deadlines. Use when running GDPR compliance assessments, privacy audits, data protection planning, DPIA generation, or data subject rights (DSAR) management (e.g., 'check this service for GDPR risks', 'track an access request deadline'). Final compliance determinations route to the DPO or legal counsel.

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Phase 4 of building a Claude Managed Agent — make it run without you. Turn a graded agent into a recurring scheduled deployment (POSIX-cron), an event-driven curl trigger, or confirmed on-demand use, then finalize the versioned roadmap. Use when the user says "run it every morning", "put it on a schedule", "nightly", "weekly", "automate this", "make it recurring", or when the orchestrator routes phase=run-without-you. deployment_builder.py builds the POST /v1/deployments payload (initial_events must include user.message; optionally nests a user.define_outcome so each firing self-grades); cron_validator.py validates the 5-field cron + IANA timezone and prints the wall-clock DST note; next_directions_writer.py writes NEXT-DIRECTIONS.md. No tool makes API calls — the deployment is created via BYOK curl. Distinct from grade-iterate (the in-session loop) and wrap-up (closeout).

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Create a well-formed git commit from current changes using session history for rationale and summary; use when asked to commit, prepare a commit message, or finalize staged work.

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Document a solved problem as a durable repo learning. Use when verified work produced non-obvious reasoning absent from its final code, tests, or existing docs; avoid routine fixes whose artifacts already explain the lesson.

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Get a branch ready for the maintainer's final review: review it for security, simplicity, and billing abuse, fix what's real, get checks passing, and open or update the PR. Use whenever the user says a feature, fix, or branch should be "merge ready", asks to get changes ready for review, or appends this to a build request ("build X and make it merge-ready").

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Mounts Cloud Storage buckets on Google Cloud as a POSIX file system using Cloud Storage FUSE (and the gcsfuse CLI tool). Use when interacting with the gcsfuse CLI or Cloud Storage FUSE mounts: decide whether FUSE, native gs:// reads, or Filestore/Managed Lustre fits a workload, deploy tuned mounts on GKE, Compute Engine, or Cloud Run, enable and size file, stat, and list caches, tune mount flags (--implicit-dirs) or config-file settings, apply workload profiles, keep ML checkpointing safe (rename atomicity, hierarchical namespace/HNS, close-time finalization, concurrent writers), or diagnose slow training, low throughput, or bill spikes with gcsfuse metrics. Covers mount semantics, gcsfuse CLI and config files, GKE gcsfuse CSI driver (Workload Identity principal:// bindings, profile StorageClasses, sidecar sizing), and Cloud Run volume mounts. Don't use for bucket administration or data management without a mount (google-cloud-storage-basics) or fully POSIX-compliant shared file systems (Filestore, Managed Lustre; use gke-storage).

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。

Monitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or safely patching stuck finalizers and disabling the slice controller. Don't use for generic GKE cluster node pool creation or standard non-TPU workload management (use gke-basics or gke-cluster-creation instead).

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Periodic sweep that finds incidents marked resolved in {{incident_channel}}, correlates the channel timeline against GitHub deploys/merges and Datadog log spikes over the incident window, and drafts a structured postmortem as a PR under {{postmortem_path}} in {{target_repo}} — root cause and action items proposed, never finalized.

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。

How to CONNECT Microsoft Teams (`kortix channels connect --platform teams`, prints a tenant-admin consent URL) and how to answer in Teams as a teammate. Covers the live Adaptive Card stream (`teams step` with --detail/--output/--source, `teams send` to finalize the answer), sending and downloading files (the consent-card upload flow + `teams download`), reading teams/channels/members through connector calls, asking the user, and the tone the bot should use. Load this when the turn is triggered from Teams (the prompt mentions a Teams tenant/conversation, or `$MS_TEAMS_CONVERSATION_ID` is set in the env), or when the user asks how to do anything in Teams.

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。

Per-subscription dunning ladder for recovering failed Stripe payments — smart retry, payment reminder, update-your-card notice, final notice — with minimum wait times between rungs, the ledger format that carries state across hourly runs, and the stop-for-human line at cancellation, credits, and refunds.

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How to CONNECT Slack (one command — `kortix channels connect`, prints a one-click install link) and how to answer in Slack as a teammate. Covers the live plan-block stream (`slack step` with --detail/--output, `slack send` to finalize the answer), file uploads, posting to other channels/threads, reactions, search, message editing/deletion, and the tone the bot should use. Load this when the user asks to connect/set up Slack, when the turn is triggered from Slack (the prompt mentions a Slack workspace/channel/thread, or `$SLACK_CHANNEL_ID` is set in the env), when this session messages someone in Slack and needs their reply to come back (thread binding, `slack bind-thread`), or when the user asks how to do anything in Slack.

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。

Per-page Codex review + targeted python-pptx / Beamer fixes for academic talk slides. Use AFTER /paper-slides (or any externally generated PPTX/Beamer) when the deck looks 'mostly OK' but the user wants a final pass that aligns visual weight with a reference, bumps PPTX fonts to projector-readable size, kills italic style leaks, fixes text-frame overflow, and catches per-slide layout drift. Trigger phrases: "polish slides", "slides 排版不对", "PPTX 字体太小", "和 Beamer 比一下", "per-page review", "和 codex 一页一页过".

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 an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.

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End-to-end conference talk pipeline: paper → slide outline → Beamer + PPTX → per-page polish → assurance checks (claim / citation / anonymity) → final export and report. Default-good for academic conference talks (NeurIPS / ICML / ICLR / VALSE / 投稿 talks). Trigger phrases: "做 talk", "做 PPT 全流程", "talk pipeline", "end-to-end slides", "做演讲", "conference talk full workflow". Use when the user wants the complete talk artifact, not just a slide deck.

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。

Ambient Memori long-term memory for Claude Code via local Bash. MUST TRIGGER on essentially every non-trivial user turn: run recall before drafting any substantive response, whether or not the user mentioned memory, a prior session, or past work. The default is to check memory first; do not wait to be asked. Always fire before external lookups (WebSearch/WebFetch) and before answering any question about preferences, prior decisions, constraints, project history, status, past work, or any non-trivial coding/research task. Skip only for trivial acknowledgements/closings, purely self-contained turns where prior context cannot possibly help, or when the user explicitly opts out. Use Advanced Augmentation after drafting the final response for every non-trivial turn, as the last memory step. Use recall.summary only for broad session summaries/orientation, compaction after context loss, feedback for memory quality, quota for limits, and signup only when explicitly requested.

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Create a SageMaker endpoint (real-time, real-time scale-to-zero, or async) with autoscaling, CloudWatch alarms, and tagging enabled by default. Use this skill whenever about to create a SageMaker endpoint, write deployment code that calls `create_endpoint`, or finalize a deployment after the image URI and IAM role are known. Provides deploy.py for real-time endpoints, deploy_ic.py for real-time endpoints that scale to zero instances via inference components, and deploy_async.py for async endpoints (also scale-to-zero). This is the last step in the SageMaker deployment workflow. Never generate a bare `create_endpoint` call without these defaults — endpoints without autoscaling or alarms are demos, not deployments.

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Develop evidence-backed structural and architectural security hardening proposals from vulnerability disclosures, supplied findings, incident or assessment documents, source code, or a completed Codex Security scan. Use when a user asks for systemic improvements, alternatives beyond per-finding patches, before-and-after security architecture views, engineering tradeoff analysis, or an implementation-ready plan for a selected hardening option. Also use automatically after a Codex Security scan with reportable findings when the top-level scan workflow requests final-report hardening guidance.

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Close a matter — capture outcome, final exposure, and lessons, then archive it out of the active portfolio without deleting the record. Use when the user wants to close a matter, says "[matter] is done", or needs to record a settlement, dismissal, judgment, withdrawal, or consolidation outcome.

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Jurisdiction-aware wage/hour and employment Q&A — classification, overtime, meal/rest breaks, leave, final pay — answered for the specific state/country with the controlling rule researched and cited rather than stated from memory. Use when the user asks any employment law question, or says "what's the rule in [state]", "is this exempt", "do we have to pay overtime for", or "can we classify this as".

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Termination review — high-risk flag detection, severance + release, and final pay timing by jurisdiction. Jurisdiction-specific rules and release consideration periods are researched per review, not stored. Use when the user says "reviewing a termination", "can we fire this person", "term review", or describes a termination scenario.

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Reference: shared framework for managing internal investigations from intake through final memo — privileged investigation log, document processing with needle-finding, source coverage tracking, Q&A against the log, memo drafting, and audience summaries. Loaded by /investigation-open, /investigation-add, /investigation-query, /investigation-memo, and /investigation-summary; not invoked directly.

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。

Ensures codebase deliverables are properly exported as ZIP archives through a dedicated finalization step

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Edit Excel workbooks only after anchored preflight audit, then require deterministic Python/openpyxl post-write proof that every requested criterion is satisfied or explicitly reconciled before finalizing.

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。