435 件 ・ 関連度順
概要と使いどころ
Analyzes a deal in progress and generates a comprehensive closing strategy. Researches the target company, maps the buying committee, builds objection responses, creates competitive positioning, and outputs a tactical deal-playbook.md with next-best-actions and a mutual close plan.
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。
Implement bounded, idempotency-aware API throttling, backoff, and retry handling for 429 and transient 5xx responses.
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。
Eliminate sycophantic agreement patterns in AI responses. Load via /skill anti-sycophancy.
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 implementing exception mapping or RFC 9457 error responses in Spring Boot 4. Preserve an existing legacy error contract unless migration is requested.
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 adding hypermedia links to REST responses, building self-describing APIs, or implementing Spring HATEOAS. Use when you see EntityModel, CollectionModel, or RepresentationModel in the project.
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 implementing exception mapping or RFC 9457 error responses in Spring Boot 3. Preserve an existing legacy error contract unless migration is requested.
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。
Manages responses to regulatory complaints lodged with supervisory authorities under GDPR Article 77, covering internal escalation procedures, DPA response coordination, remediation tracking, and compliance documentation. Activate for regulatory complaint, supervisory authority complaint, Art. 77, DPA response, ICO complaint queries.
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。
Generate cold email templates, LinkedIn messages, follow-up sequences, and value propositions tailored to specific industries that actually get responses and book discovery calls.
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。
Fix JSON parse errors when fetching archived API responses from Wayback Machine. Use when: (1) Getting "Expecting value: line 1 column 1 (char 0)" JSON decode errors from archived URLs, (2) Wayback returns HTML instead of expected JSON/raw content, (3) Crawling archived REST APIs or JSON endpoints from web.archive.org. The `id_` modifier returns raw content without the Wayback toolbar wrapper.
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。
Fix features broken by REST API responses that flatten Nostr events, losing tag data. Use when: (1) A feature works for WebSocket-loaded events but not REST API-loaded ones, (2) A model field (like sha256, textTrackRef) is null for REST API data but set for WebSocket data, (3) REST API returns denormalized fields (d_tag, video_url) but omits raw tags array, (4) hasSubtitles/hasFeature returns false for REST-loaded videos. Common in Nostr clients that use both REST APIs (for analytics/bulk queries) and WebSocket (for real-time events).
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。
Select appropriate Ollama models for processing sensitive but legal content. Use when: (1) llama3.2 or deepseek-r1 refuses to process content with "I cannot assist" responses, (2) Local LLM returns generic safety disclaimers instead of following instructions, (3) Need to process adult content, sex work data, or other legal-but-sensitive material through a local LLM. Also covers using /api/chat vs /api/generate for system prompt support, and structuring prompts for consistent format compliance.
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。
Fix wildcard subdomain routing for Fastly Compute@Edge services when subdomains resolve but return 500 "Domain Not Found" or empty responses. Use when: (1) TLS subscription "issued" but edge serves default certificate (CN=j.sni-644-default), (2) Fastly domain-v1 create succeeds but subdomain returns 500, (3) Static publisher/PublisherServer returns empty content for subdomain requests, (4) DNS wildcard CNAME resolves to wrong target. Covers TLS configuration SNI endpoint selection (x.sni vs j.sni vs w.sni), DNS trailing dot issues, Fastly domain-v1 activation, and reading from KV store directly when PublisherServer fails for subdomains.
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。
Debug Fastly Compute services where code changes don't affect behavior due to multi-service routing architecture. Use when: (1) deployed changes have no effect, (2) unexpected redirects persist after code updates, (3) DNS resolves to Fastly but responses don't match deployed code, (4) `fastly service list` shows multiple related services. The root cause is often a routing/gateway service intercepting requests before they reach your content 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。
Use when implementing feedback mechanisms for AI responses.
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。
Iteratively enhance user requirements into clear, complete, actionable specifications through analysis and clarification. Use when: (1) Users provide initial requirements that need refinement, (2) Requirements are vague, incomplete, or ambiguous, (3) Creating formal specifications from informal descriptions, (4) Identifying missing constraints, edge cases, or acceptance criteria, (5) Clarifying assumptions and implicit dependencies, or (6) Preparing requirements for design, implementation, or verification. Operates interactively: analyze → ask clarifying questions → refine based on responses.
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。
Compare runtime behavior between original and migrated repositories to detect behavioral differences, regressions, and semantic changes. Use when validating code migrations, refactorings, language ports, framework upgrades, or any transformation that should preserve behavior. Automatically compares test results, execution traces, API responses, and observable outputs between two repository versions. Provides actionable guidance for fixing deviations and ensuring behavioral equivalence.
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 professional, empathetic customer-facing responses adapted to the situation, urgency, and channel. Use when responding to customer tickets, escalations, outage notifications, bug reports, feature requests, or any customer-facing communication.
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。
TypeScript-first schema validation and type inference. Use for validating API requests/responses, form data, env vars, configs, defining type-safe schemas with runtime validation, transforming data, generating JSON Schema for OpenAPI/AI, or encountering missing validation errors, type inference issues, validation error handling problems. Zero dependencies, compact core (~5kb gzipped; zod/mini ~1.9kb).
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 building HTTP servers with Bun.serve, handling requests/responses, implementing routing, creating REST APIs, or configuring fetch handlers.
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。
Implements standardized API error responses with proper status codes, logging, and user-friendly messages. Use when building production APIs, implementing error recovery patterns, or integrating error monitoring services.
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。
Verification guide for citations added during rebuttal writing. Use when Stage 2 responses introduce new references, when the Area Chair asks about a cited paper, or when any citation in the rebuttal might have been AI-generated. Prevents the serious credibility damage of fabricated references in reviewer-facing documents.
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。
Break down full ICLR reviewer responses into structured rebuttal units. Use when input contains reviewer summary/presentation/contribution/strength/weakness/question text and the goal is to split weaknesses/questions into granular R-style response items while preserving original wording for quoted issues.
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。
Break down full NeurIPS reviewer responses into structured rebuttal units. Use when input contains NeurIPS reviewer fields (Summary, Strengths and Weaknesses, Questions, Limitations) and numeric scores (Rating, Confidence, Quality, Clarity, Significance, Originality). Splits questions and limitations into granular response items while preserving original wording for quoted issues.
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。
Break down full ARR (ACL Rolling Review) reviewer responses into structured rebuttal units. Use when input contains ARR reviewer fields (Paper Summary, Strengths, Weaknesses, Comments/Suggestions) and numeric scores (Confidence, Soundness, Excitement, Overall Assessment, Reproducibility). Splits weaknesses and comments/suggestions into granular response items while preserving original wording for quoted issues.
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。