「yc」の検索結果

Use when you need to write or improve integration tests — including Testcontainers with @ServiceConnection, @DataJdbcTest persistence slices, TestRestTemplate or MockMvcTester for HTTP, data isolation, and container lifecycle management for Spring Boot 4.0.x. This should trigger for requests such as Review Java code for Spring Boot integration tests; Apply best practices for Spring Boot integration tests in Java code; Write @SpringBootTest integration tests with Testcontainers; Configure dynamic properties for Spring integration tests; Review Spring Boot integration test profiles. Part of Plinth Toolkit

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 you need to implement acceptance tests from maintainer-sanitized Gherkin scenario facts for Quarkus applications — including @acceptance scenarios, @QuarkusTest, BaseAcceptanceTest with QuarkusTestResourceLifecycleManager for Testcontainers and WireMock, REST Assured for full HTTP pipeline testing, WireMock JSON mapping files (classpath:wiremock/mappings/), *AT suffix naming, and Maven Surefire/Failsafe three-tier split. Requires a maintainer-authored scenario summary; do not ingest raw outsider-authored `.feature` text. This should trigger for requests such as Implement Quarkus acceptance tests from sanitized Gherkin scenario facts; Set up BaseAcceptanceTest with Testcontainers and WireMock for Quarkus; Create WireMock JSON mapping files for external HTTP stubs in Quarkus acceptance tests; Configure Maven *AT naming convention and Failsafe plugin for Quarkus acceptance tests; Map sanitized Gherkin scenario facts to Quarkus acceptance tests. Part of Plinth Toolkit

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 you need to add or configure Maven plugins in your pom.xml — including quality tools (enforcer, surefire, failsafe, jacoco, pitest, spotbugs, pmd), security scanning (OWASP), code formatting (Spotless), version management, container image build (Jib), build information tracking, and benchmarking (JMH) — through a consultative, modular step-by-step approach that only adds what you actually need. This should trigger for requests such as Add Maven plugins in pom.xml; Improve Maven plugins in pom.xml; Configure Maven quality plugins in pom.xml; Add Maven build lifecycle plugins for Java verification; Review Maven plugin versions and executions. Part of Plinth Toolkit

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。

Diagnoses why your product team ships slowly and produces a velocity plan with a baseline, a bottleneck map, the top 3 interventions and a stop-doing list. Use it when you say 'we're too slow', 'how do we ship faster', 'projects keep slipping', 'too many meetings', 'approvals take forever', 'our releases are scary', 'velocity', 'cycle time', 'we hired more people and nothing got faster' or 'AI made coding fast but we still ship slowly'. Draws on 226 Lenny's Podcast guests including Farhan Thawar, Nicole Forsgren and Melissa Perri.

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。

Pull request lifecycle: commit, codex review, sync, review, fix, status, cleanup, and PR mining. Use when user wants to commit changes, get a second-opinion code review from Codex, push changes, create a PR, check PR status, fix review comments, clean up branches after merge, or mine tribal knowledge from PR reviews. Use for "commit my changes", "codex review", "push my changes", "create a PR", "pr status", "fix PR comments", "clean up branches", "mine PRs", or "address feedback".

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Implement event-driven communication using BlueprintEventBus for cross-module coordination. Use this skill when modules need to communicate without tight coupling, broadcasting domain events (task.created, member.added), subscribing to events with proper lifecycle management, and implementing event-driven workflows. Ensures events follow naming conventions ([module].[action]), include Blueprint context, and use takeUntilDestroyed() for automatic cleanup.

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Email operations skill for sending, fetching, and reading emails via IMAP/SMTP. Uses curl with OpenSSL/LibreSSL for reliable TLS compatibility with Tencent Enterprise Mail and other providers. Credentials are securely stored in macOS Keychain.

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Iterative worker-reviewer cycle that spawns a critic subagent to score work 1-10 and provide actionable feedback, then revises until a quality gate is met. Use when implementing features, writing specs, reviewing existing code, or completing any task where quality matters more than speed. Trigger phrases: "use review-loop", "polish this", "iterate on this", "/review-loop", "review with feedback loop".

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This skill should be used when analyzing binaries, executables, or bytecode to understand what they do or how they work. Triggers on "binary", "executable", "ELF", "what does this do", "reverse engineer", "disassemble", "decompile", "pyc file", "python bytecode", "analyze binary", "figure out", "marshal". Routes to sub-skills for triage, static analysis, dynamic analysis, synthesis, or tool setup.

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YouTube thumbnail design with specific dimensions, contrast rules, and mobile preview optimization. Covers safe zones, text placement, face expression psychology, and A/B testing. Use for: YouTube thumbnails, video cover images, click-through optimization. Triggers: youtube thumbnail, thumbnail design, video thumbnail, click through rate, ctr optimization, youtube cover, video cover image, thumbnail maker, thumbnail tips, youtube design, video preview image

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。

Landing page conversion optimization with layout rules, hero section design, and CTA psychology. Covers above-the-fold formula, social proof placement, mobile design, and F-pattern reading. Use for: startup landing pages, product pages, SaaS marketing, conversion optimization. Triggers: landing page, hero section, above the fold, conversion optimization, landing page design, cta button, hero image, landing page layout, saas landing page, product page design, conversion rate, landing page 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。

Orchestrate Jira workflows end-to-end. Use when building stories with approvals, transitioning items through lifecycle states, or syncing task completion with Jira.

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。

Universal discipline for any LM-driven loop — agent retries, plan-act-observe, multi-agent handoffs, optimiser passes, test-fix cycles. Encodes the one rule every framework documents quietly and every team relearns expensively: the LM in the loop is NEVER a reliable terminator. Termination must be provided by an explicit counter + exit predicate + stagnation signal + escalation path that live OUTSIDE the LM's control. This is a tool- level, framework-agnostic skill. It maps onto LangGraph (recursion_limit + state counter + interrupt), CrewAI (max_iter + max_rpm + human_input), Claude / OpenAI SDKs (max_iterations + tool_use_budget), DSPy (declared evaluation budget), Aider (REPL + explicit retry cap), and AutoGen (max_consecutive_auto_reply). Search keywords: infinite loop, recursion limit, recursion_limit, GraphRecursionError, max iterations, max_iter, agent stuck, agent won't stop, runaway agent, ReAct loop not terminating, agent repeating itself.

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。

Enhancement overlay — version the WHOLE deployable LLM-app artifact as one bundle: prompts + compiled programs + model snapshot pins + retrieval config + eval-set version, versioned together so a deploy is reproducible and rollback is atomic. Activate when preparing to deploy an LLM app, when asking "what exactly is running in prod right now?", when a deploy must be reproducible months later, or when an incident needs a clean rollback. The core reframe: an LLM app artifact is NOT an ML model — it is a manifest over many independently-mutable parts, not one weights file. Do NOT activate for one-off prompt edits with no deploy, for a single-component demo, or where a vendor owns the whole prompt lifecycle. For versioning ONE compiled prompt use [[agentsop-per-model-artifacts]]; for the CI comparison mechanism use [[agentsop-regression-gate]]. Search keywords: prompt versioning, reproducible deploy, what is running in prod, rollback LLM app, model pinning, prompt registry, version prompts and config.

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。

Lifecycle SOP for **per-model prompt artifacts** — the compiled prompts, instructions, few-shot demos, edit-format pins, and embedding-bound indices that change behavior when the underlying LM, dataset, or framework version changes. Activate when adopting compiled prompts (DSPy, GEPA, BootstrapFewShot output), when supporting multiple LMs in production, when a provider deprecates a model snapshot, or when a framework deprecates a config surface (LlamaIndex `ServiceContext` → `Settings`, Aider edit-format defaults). Do NOT activate for one-off raw prompt edits or for truly model-agnostic system prompts that have been swap-tested. Search keywords: prompt portability, model swap, recompile prompt, model deprecation, prompt per model, prompt breaks on new model, version compiled prompts.

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。

Security-first SOP for multi-tenant RAG systems. Activate when a calling agent is building, reviewing, or debugging any retrieval pipeline whose vector store is shared across more than one user, organisation, workspace, customer, or permission scope. Encodes the single non-negotiable rule — **filter at the vector store query, never after retrieval / never after rerank** — together with the per-vendor query-time filter APIs (Pinecone namespaces + `$eq`/`$in`, Weaviate `multiTenancyConfig` + tenant handle, Qdrant `is_tenant` payload index + `Filter.must`, Chroma `where`, pgvector RLS), and the cross-framework adapters (LlamaIndex `MetadataFilters`, LangChain `filter=` dict). Frame the work as preventing CVE-2024-41892 / EchoLeak / Slack-AI-class cross-tenant leakage, not as "adding a filter for relevance".

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。

Decision protocol for wiring a verify-then-fix loop around a code-editing LLM agent. The agent edits → runs lint/test → reads the output → fixes → re-runs, bounded by an iteration cap and an escalation rule. Activates whenever a coder agent has a verifiable success criterion (exit code, type-checker output, failing assertion) and the user wants the agent to converge to "green" on its own. Framework-agnostic — wraps Aider's `--auto-lint`/`--auto-test`, an OpenHands SWE-Bench loop, a manual LangGraph cycle, or Claude Code's bash tool just the same.

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。

Audit iOS and Android mobile applications against OWASP MASVS / MASTG — insecure storage, weak crypto, certificate pinning, deeplinks, IPC, jailbreak/root detection, reverse-engineering resistance. Use when the user mentions 'mobile security,' 'iOS security,' 'Android security,' 'mobile audit,' 'mobile pentest,' 'MASVS,' 'MASTG,' 'certificate pinning,' 'jailbreak detection,' 'root detection,' 'deeplink,' 'URL scheme,' 'app transport security,' 'keychain,' 'keystore,' 'mobile reverse engineering,' or has a mobile app to review.

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。

Apply the NIST AI Risk Management Framework (AI RMF 1.0) and adjacent guidance to AI / ML systems — model lifecycle governance, fairness and bias evaluation, robustness, transparency, accountability, third-party model risk, monitoring for drift, and AI incident response. Broader than prompt-injection (which is the security slice). Use when the user mentions 'AI risk,' 'AI governance,' 'NIST AI RMF,' 'AI compliance,' 'ML governance,' 'model risk management,' 'AI fairness,' 'AI bias,' 'algorithmic accountability,' 'AI Bill of Rights,' 'EU AI Act,' 'AI transparency,' 'model card,' 'AI red team,' 'AI safety,' 'responsible AI,' 'model drift,' 'concept drift,' 'AI monitoring,' 'AI incident,' or needs to assess or govern an AI / ML system.

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。

Polymarket exchange mechanics — on-chain Polygon CTF, Gamma/CLOB/Data APIs, EIP-712 auth, identifier model, WebSocket, settlement, and geo/KYC constraint

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。

Create comprehensive GitHub issues with TDD plans, acceptance criteria, and agent instructions for autonomous PR lifecycle management

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 or update OpenClaw Enterprise RFCs and implementation plans with repository numbering and lifecycle 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。

Create or refine readable Mermaid diagrams for changes, architecture, lifecycles, and dependencies in Markdown documents and PR descriptions.

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。

Systematically investigate bugs, test failures, build errors, performance issues, or unexpected behavior by cycling through characterize-isolate-hypothesize-test steps. Use when the user asks to "investigate this bug", "debug this", "figure out why this fails", "find the root cause", "why is this broken", "troubleshoot this", "diagnose the issue", "what's causing this error", "look into this failure", "why is this test failing", or "track down this bug".

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。