'general' 검색 결과

Use whenever the user wants to find, rank, or shortlist directories and registries where they can submit or list an MCP server (Model Context Protocol server) — to get backlinks, referral traffic, and discovery by agent builders. Triggers on "where do I list my MCP server", "best MCP directories", "MCP registries to submit to", "get my MCP server discovered", or "pull submission details for these MCP-directory domains", even when described indirectly (we built an MCP server, where do we publish it). Drives the ServiceGraph API (api.servicegraph.co) — a catalog of 1,000+ product directories enriched with Domain Rating, backlinks, and organic traffic. Defer to find-ai-directories for general AI-tool / AI-agent / agent-skill listings, and to find-product-directories for general SaaS/software launches. Skip building an MCP server or asking how MCP works (DIY), finding a firm to build one (use find-ai-consultancy / find-software-developer), and MCP link-building *services*.

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General rules for developing desktop applications using Tauri with Svelte and TypeScript for the frontend.

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General guidelines for TALL stack development, emphasizing Laravel and PHP best practices.

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Applies general rules for Convex development, emphasizing schema design, validator usage, index-first query patterns, function registration, and correct handling of system fields.

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Calculates CRAP (Change Risk Anti-Patterns) score for .NET methods, classes, or files. Use when the user asks to assess test quality, identify risky untested code, compute CRAP scores, or evaluate whether complex methods have sufficient test coverage. Requires code coverage data (Cobertura XML) and cyclomatic complexity analysis. DO NOT USE FOR: writing tests, general test execution unrelated to coverage/CRAP analysis, or general code coverage reporting without CRAP context.

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Use this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing.

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Use when configuring Slack-specific Agentforce capabilities AFTER the basic Slack deployment is complete: enabling Slack-native actions, managing public vs. private action scope, mapping Salesforce-to-Slack user identity, or troubleshooting Slack action failures. Triggers: 'add General Slack Actions topic to agent', 'configure canvas creation for Agentforce in Slack', 'Agentforce private action requires user identity mapping', 'Slack agent cannot send DMs after deployment', 'Agentforce Look Up User action not working in Slack', 'how to map Slack users to Salesforce identities for private actions'. NOT for the initial Slack OAuth install, DM vs channel-mention mode, or core agent setup — use agentforce/agent-channel-deployment. NOT for sending a Slack message or creating a channel from a Flow — use flow/flow-for-slack.

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Expert-level general relativity knowledge. Use when working with curved spacetime, Einstein field equations, geodesics, black holes, gravitational waves, cosmology, Schwarzschild metric, or tensor calculus. Also use when the user mentions 'Einstein field equations', 'curved spacetime', 'geodesic', 'black hole', 'event horizon', 'Schwarzschild', 'gravitational waves', 'spacetime curvature', 'Riemann tensor', 'metric tensor', 'cosmological constant', or 'gravitational lensing'.

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Load when configuring GitBook documentation sites, authoring GitBook-flavored markdown pages and custom blocks, integrating OpenAPI/Swagger specs, driving GitBook Change Request workflows (create, review, comment, resolve), or building GitBook platform integrations. Do not use for general repository code reviews, general .NET OpenAPI schema generation, or non-GitBook markdown.

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Knowledge base from the OUSD(R&E) guidebook Implementing a MOSA in DoD Programs (Feb 2025). Use for the Modular Open Systems Approach as a DoD acquisition + design discipline: the statutory/regulatory basis (10 U.S.C. 4401–4403, FY2017/FY2021 NDAA, DFARS), the five OUSD(R&E) pillars, the plan→modularize→identify→define→standardize interface lifecycle, technical levers (WBS/MIL-STD-881F taxonomy, standards profiling, API-first software, COTS/cybersecurity), MOSA assessment metrics and tools (PART/OAAT/KOSS/SEAM/MAUT), technology-change and DMSMS management, roadmaps, MOSA across the six AAF pathways, and contracting/IP/data-rights mechanics. SCOPE LIMITS: this is U.S. DoD weapon-system acquisition policy, not a general open-architecture or interface-standards reference — it names standards (FACE, OMS, DISR) without reproducing them, is light on detailed engineering of any specific standard, and does not cover the underlying SE processes (use dau-se-guidebook / nasa-npr-7123) or general systems-engineering theory (use sebok).

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Knowledge base from the DoD Risk, Issue, and Opportunity (RIO) Management Guide for Defense Acquisition Programs (OUSD R&E, Sep 2023 incl. Change 2.2). Use for the defense-acquisition mechanics of program risk management: the RIO definitions (risk/issue/opportunity), the five-step risk process (plan-identify-analyze-mitigate-monitor), 1-5 likelihood/consequence scoring and the 5x5 risk matrix, the four mitigation options (accept/avoid/transfer/control), burn-down plans, issue management (probability=1), opportunity management toward should-cost, cross-program/interface risk, tailoring RIO to the six AAF acquisition pathways (UCA/MTA/MCA/Software/DBS/Services), specialized methods (RMF, MBCRA/Cyber Table Top, Agile metrics, FMECA, ITRA/DTRAM), and institutionalizing RIO via the PRMP, boards (RMB/JRMB/ROMB/RWG), tools, tiered roles, and WBS/IMP/IMS/EVM/TPM integration. This is the DoD-acquisition complement to nasa-risk (general CRM/RIDM theory) and dau-se-guidebook (the SE process frame). Does NOT teach general risk theory from scratch, and defers specialized risk regimes (system safety/ESOH, HSI, detailed cyber/RMF, spectrum) to their own DoD instructions and the relevant packs.

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Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability analysis.

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リファクタリングを「更新されたチームの理解と、コードが表現する過去の理解の差分同期」と捉え、今回得た新知識（要求・ドメイン知識・制約）が naming と responsibility へ反映されているか、boundary が現在の understanding を表現しているか、diff の削除行やコメントに現れる過去の design history と constraint を失っていないかを diff-time で確認する。Knowledge Delta の signal は diff（追加/削除された hunk・コメント・ADR 参照）を一次情報とし、PR 本文が供給されるときは補助に用い、不確実なら question に留める。ドメイン用語の一貫性は ubiquitous-language-naming、集約/コンテキスト境界の設計判断は bounded-context-language、投機的抽象化・caller special-case は altitude-generalization、スコープ逸脱/前提破壊は fix-scope-integrity、振る舞い変更と構造変更の分離は behavior-structure-separation、完了主張の反証は refactor-claim-audit へ委譲する

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リファクタリング（構造変更）と機能変更（behavior change）が同一 diff に混在していないかを識別し、structural change に対する external behavior preservation の証拠（テスト・型・静的解析）が揃っているかを diff-time で確認する。証拠不足のときは Characterization Test 追加を促すか question とする。DTO/公開 API の破壊的変更検出は api-compatibility、完了主張の反証や抽出リファクタの性能特性退行は refactor-claim-audit、新知識の命名・責務・境界への反映は knowledge-to-code-alignment、投機的抽象化・スコープ逸脱は altitude-generalization / fix-scope-integrity へ委譲する

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General-purpose guidance when no specialized skill applies.

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Extract structured fields from t1 general documents.

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調査（Explore）・設計（Plan）・実装（general-purpose）・レビュー（review-* スキル群）のサブエージェントをオーケストレーションして開発タスクを遂行するスキル。依頼文からゴール（調査のみ / 設計まで / 実装まで / レビュー）を判定し、必要なフェーズだけ実行する。親は自分でコードを読み書きせず、分解・dispatch・検収・機械検証に徹する。Use when starting any non-trivial development task（複数ファイル・複数層にまたがる調査/設計/実装/レビュー）, when user says 'オーケストレート', 'orchestrate', '調べて', '設計して', '実装して', '調べて直して', or 'レビューして'.

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Use this skill to understand the FMCSA cargo securement standards. Covers § 393.100-§ 393.136 general rules, tiedown requirements, working load limits.

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Skill for general tasks.

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반복하는 LLM API 요청에서 공통 지시와 자료를 캐시로 재사용하기 쉽게 배치합니다. 캐시 사용량, 읽기·쓰기·저장 비용과 응답 시간을 확인해 구성을 검토합니다.

• 반복 API 요청의 공통 지시를 재배치합니다
• 캐시 읽기·쓰기·저장 비용을 계산합니다
• 캐시 사용률과 응답 시간을 측정합니다

AI 에이전트가 외부 정보를 읽고 도구나 파일을 조작할 때의 보안 대책을 정리합니다. 권한, 저장 경로, 접속 대상, 인증 정보 처리를 검토하고 실제 동작으로 검증합니다.

• 에이전트의 보안 대책 검토
• 사용자와 작업 영역 간 데이터 격리 확인
• 인증 정보 정리와 출력 제한 검증

Claude Code 작업에서 수정 사항과 반복 절차를 찾아 근거와 신뢰도가 있는 행동 규칙으로 저장합니다. 프로젝트별로 정리하고 관련 규칙을 스킬, 명령, 에이전트로 발전시킵니다.

• 작업 선호도와 절차 학습
• 프로젝트별 개발 규칙 정리
• 학습한 규칙을 스킬로 전환

PubMed에서 의학·생명과학 문헌을 찾고, 표준 주제어와 조건으로 검색식을 구성합니다. 초록과 서지 정보를 가져오며, 재현 가능한 검색 기록과 API를 통한 지속적인 문헌 확인을 돕습니다.

• 연구 주제와 관련된 의학 논문 찾기
• 주제어와 기간으로 검색식 구성하기
• PMID로 초록과 서지 정보 가져오기

Write, review, and refactor C# and .NET code using practical conventions for asynchronous work, configuration, and dependency injection—passing services into classes. Includes examples for data access and APIs to support maintainable applications.

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• Reviewing C# implementation conventions
• Improving asynchronous code and cancellation handling
• Organizing service dependencies and configuration