Install and use the official AI Logo Maker package, pinned by digest, for paid hosted work on the Beatra service.
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。
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概要と使いどころ
Install and use the official AI Logo Maker package, pinned by digest, for paid hosted work on the Beatra service.
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。
Draft a blog post from ideas and resources. Use when users want to write a blog post, create content from research, or draft articles. Guides through research, brainstorming, outlining, and iterative drafting with version control.
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。
Soạn thảo bài đăng blog từ ý tưởng và tài nguyên. Sử dụng khi người dùng muốn viết bài blog, tạo nội dung từ nghiên cứu, hoặc soạn thảo bài viết. Hướng dẫn qua nghiên cứu, động não, lập dàn ý, và soạn thảo lặp lại với kiểm soát phiên bản.
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。
Automate changelog generation from commits, PRs, and releases following Keep a Changelog format. Use when setting up release workflows, generating release notes, or standardizing commit conventions.
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。
Turn vague "what did I do?" into evidence-backed impact statements for performance reviews, self-reviews, promotion packets, and weekly updates. Uniquely mines Copilot CLI session logs to reconstruct forgotten work, plus git commits and GitHub PRs. Enforces a 3-part impact contract (action → result → evidence). Works standalone with zero dependencies. Trigger for: "brag", "log work", "what did I do", "backfill my work history", "performance review", "self-review", "self assessment", "write impact statement", "review prep", "promo packet", "promotion case", "weekly update", "status report", "accomplishments", "what did I ship", "I forgot to log my work", "summarize my work", "track my wins", "what should I highlight", "end of half", "career growth", "work journal", or any request to document, summarize, or organize work accomplishments.
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。
Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify domains against known SaaS categories, and score risk by data volume and user count. Use when auditing an organization for unsanctioned cloud/SaaS usage or generating a shadow IT discovery report with remediation recommendations.
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。
Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.
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。
Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate issuance, and shadow IT. Monitors newly issued certificates for typosquatting and brand impersonation using Levenshtein distance. Use for proactive phishing domain detection and certificate monitoring.
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。
Parse Windows PowerShell Script Block Logs (Event ID 4104) from EVTX files to detect obfuscated commands, encoded payloads, and living-off-the-land techniques. Uses python-evtx to extract and reconstruct multi-block scripts, applies entropy analysis and pattern matching for Base64-encoded commands, Invoke-Expression abuse, download cradles, and AMSI bypass attempts.
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。
Analyzes Windows Security, System, and Sysmon event logs in Splunk to detect authentication attacks, privilege escalation, persistence mechanisms, and lateral movement using SPL queries mapped to MITRE ATT&CK techniques. Use when SOC analysts need to investigate Windows-based threats, build detection queries, or perform forensic timeline analysis of Windows endpoints and domain controllers.
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。
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
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。
Parse Office 365 Unified Audit Logs via Microsoft Graph API to detect email forwarding rule creation, inbox delegation, suspicious OAuth app grants, and other indicators of account compromise.
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。
Uses the Linux Audit framework (auditd) with ausearch and aureport utilities to detect intrusion attempts, unauthorized access, privilege escalation, and suspicious system activity. Covers audit rule configuration, log querying, timeline reconstruction, and integration with SIEM platforms. Activates for requests involving auditd analysis, Linux audit log investigation, ausearch queries, aureport summaries, or host-based intrusion detection on Linux.
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。
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.
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。
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.
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。
Log genuine, recurring repository friction to .agents/PAPERCUTS.md — confusing setup, a flaky repo command or script, a misleading in-repo error, stale generated files, or a non-obvious gotcha that will cost the next contributor time. Also use to review, deduplicate, and resolve existing entries. Gate hard before logging: only friction the repository itself can fix counts. Never log the agent's own sandbox/permission errors, shell-scripting mistakes, transient flakiness, or third-party tool quirks the repo can't change.
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 source code change needs a changelog entry, or before committing and pushing any bug fix, feature, or behavior change to source code - detecting when entries are required, categorizing changes correctly (added/changed/fixed/deprecated/removed/security), writing user-facing titles, and creating the JSON entry in .changelogs/
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。
Retrieve and analyze Screenpipe CLI backend logs and desktop app logs for debugging
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。
Investigates Google Cloud networking issues by analyzing GCP logs, metrics, and diagnostics. Use when investigating dropped network traffic, packet drops, drop reasons, VPC Flow Logs (including Private Service Connect / PSC, serverless / App Engine Direct VPC, and cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don't use for generic VM management or non-observability 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。
Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).
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。
Configures GKE observability, including Cloud Logging, Cloud Monitoring, and managed Prometheus. Use when configuring GKE monitoring, setting up GKE logging, or configuring Prometheus metrics collection, and to troubleshoot Managed Service for Prometheus (GMP) issues such as missing metrics, unhealthy scrape targets, PodMonitoring misconfiguration, rule/alert evaluation failures, and monitoring permission errors. Don't use to configure local application logging frameworks or external APMs outside GKE.
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。
Find, evaluate, and download common purchasable CAD parts from step.parts, including named off-the-shelf actuators, servos, motors, electronics boards, connectors, screws, bolts, nuts, washers, bearings, standoffs, and other catalog components. Use when Codex needs to search the hosted step.parts catalog before creating simplified placeholder geometry, resolve fuzzy part names, standards, aliases, or dimensions, choose a matching part, fetch a canonical .step file, verify checksums, or use the step.parts API/OpenAPI/catalog endpoints for standard part discovery.
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。
OpenTelemetry-backed tracing, structured logs, metrics with rollups, alerts, sampling, and baggage for the engine — emit and query telemetry through `engine::*` functions and react to logs with a `log` trigger.
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。
Transfer a blog post from Notion to the Wasp blog. Fetches content, downloads and optimizes images, and creates a properly formatted MDX file.
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。