「go」の検索結果

OpenHumanのコアから製品固有でない処理とテストをtiny*へ移し、責務の分離、移行先のリリース、参照バージョンと検証用ハッシュの更新まで進めるスキルです。

• コアから汎用処理を切り出したいとき
• 実装のテストを担当サブモジュールへ移行
• TinyBusの契約と接続処理の更新

Master Godot 4 GDScript patterns including signals, scenes, state machines, and optimization. Use when building Godot games, implementing game systems, or learning GDScript best practices.

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。

分散型金融のスマートコントラクトを、ステーキングやトークン交換の実装例から組み立てます。報酬の分配、流動性の追加・引き出し、交換額の計算を扱います。

• 報酬を分配するステーキングの実装
• 流動性プールを使うトークン交換の実装
• ガバナンストークンの仕組み作り

Generate a complete Go MCP server project with proper structure, dependencies, and implementation using the official github.com/modelcontextprotocol/go-sdk.

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Discover and inventory shadow API endpoints that operate outside documented OpenAPI/Swagger specs, using traffic analysis against API gateways (Kong, AWS API Gateway, Envoy), cloud configuration scanning, and source code repository mining for undocumented routes. Use when assessing API attack surface, auditing for forgotten test environments or deprecated API versions still running, or building an API registration governance policy.

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Detect RDP brute force attacks by parsing Windows Security Event Logs (EVTX files, via python-evtx) for failed logon patterns (Event ID 4625, Logon Type 10/3), correlating with successful logons (Event ID 4624), and analyzing NLA failures and source IP frequency. Use when investigating exposed RDP endpoints, building SIEM detection rules for credential guessing, or confirming whether a compromised account followed a brute-force pattern.

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Detect Kerberos Golden Ticket forgery (e.g. Mimikatz-forged tickets) by analyzing Windows Event ID 4769 for RC4 encryption downgrades (0x17), abnormal ticket lifetimes, and krbtgt account anomalies using Splunk and Elastic SIEM queries. Use when investigating suspected forged Kerberos tickets or krbtgt credential theft in Active Directory.

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Detect Golden Ticket attacks in Active Directory using Splunk and KQL queries against domain controller event logs, looking for Kerberos TGT anomalies such as mismatched encryption types, impossible ticket lifetimes, non-existent accounts, and forged PAC signatures. Use when hunting for Kerberos ticket forgery or krbtgt-based persistence (MITRE T1558.001) in AD environments.

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Run an evaluator-gated performance optimization workflow over Codex goal mode with durable OMX artifacts and safe goal handoffs.

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Create and execute durable repo-native multi-goal plans over Codex goal mode artifacts.

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Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning Use when: adding search to, algolia, instantsearch, search api, search functionality.

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Research market rates, build negotiation strategy, and create counter-offer scripts. Use when the user mentions salary negotiation, counter offer, compensation discussion, or pay raise conversation.

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。

Export Google Contacts directory to a Google Sheets spreadsheet.

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Create a Google Docs post-mortem, schedule a Google Calendar review, and notify via Chat.

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。

Share Google Drive files with all attendees of a Google Calendar event.

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。

Read data from a Google Sheet and create a formatted Google Docs report.

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。

Read event data from a Google Sheets spreadsheet and create Google Calendar entries for each row.

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。

Google Workflow: Convert a Gmail message into a Google Tasks entry.

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Watches what customers are saying in public and in private, then does something about it. Aggregates Google, Yelp, and Facebook reviews alongside disputes, tickets, and email into themes backed by verbatim quotes; drafts a reply to every review in the owner's own voice for approval; spots customers who have gone quiet or look likely to leave; and drafts win-back offers for the ones worth keeping. With Shopify connected, order and fulfillment patterns become a sentiment signal too. Works from pasted or exported reviews when nothing is connected. Use this whenever the owner asks about reviews, ratings, reputation, complaints, or repeat business — including "what are people saying about us," "did we get any bad reviews," "how do I respond to this one-star," "our rating dropped," "which customers have gone quiet," "who hasn't ordered in a while," "how do I win them back," or "are customers happy."

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Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named human owner (clinician / biostatistician / regulatory owner) — never clinical fact, never a finished protocol. Distinct from ra-qm-team, which handles the regulatory/QM submission (ISO 13485, EU MDR, FDA 510(k)/PMA/QSR), not the study design.

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Manage local SEO for service-area businesses — appliance repair, HVAC, plumbing, cleaning, and any business that serves customers at their location. Use when the user wants to: audit Google Business Profile, generate neighborhood service area pages, check NAP consistency across directories, create LocalBusiness schema, or write review responses. Triggers: 'local SEO', 'Google Business Profile', 'GBP', 'service area page', 'NAP consistency', 'local citations', 'LocalBusiness schema', 'review responses', 'Google Maps ranking'. NOT for national SEO (use seo-audit). NOT for general schema (use schema-markup). NOT for AI answer-engine visibility (use aeo).

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Use when designing or revising a company's commercial policy — the rules of engagement governing discounts off list price, approver thresholds, exception flows, and the deal framework that Deal Desk and AEs operate under. Covers discount matrix design (ARR band x term length x payment terms x strategic value), commercial policy design, exception policy, discount governance, approval thresholds, deal framework structure, and policy linting (contradictions, gaps, cliff edges, gaming surfaces). For Head of Commercial, Head of Deal Desk, VP Sales, or RevOps at the policy-design moment — NOT per-deal application (that is deal-desk) and NOT pricing model selection (that is pricing-strategist).

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Clones, analyzes, plans, and migrates legacy codebases (C++, Fortran, Java, Python, C, Shell) from a GitHub URL or local directory to a modern, high-performance, deterministic, 100% Safe Rust architecture, tracking live telemetry across every task bucket, test failure/fix cycle, and Profile-Guided Optimization (PGO) stage, and producing a first-person AI storytelling report and interactive HTML infographic. Use when migrating a GitHub repository or local codebase to Rust, porting legacy C++, Fortran, Python, or Java workloads to memory-safe Rust, designing Struct-of-Arrays (SoA) or SIMD Rust architectures, or optimizing Rust ports with LLVM PGO. Don't use for unrelated non-Rust refactoring or single-line syntax questions.

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Remediates Google Cloud Security Command Center findings, including IAM permission fixes, cloud resource misconfigurations, vulnerabilities, and Toxic Combinations. Use when asked to fix, remediate, or mitigate a Security Command Center finding or address attack paths. Don't use for general IAM policy querying without a Security Command Center finding. For runtime threat detections, this skill provides containment and investigation guidance rather than automated configuration fixes.

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。