「case」の検索結果

GraphQL queries, mutations, and code generation patterns. Use when creating GraphQL operations, working with Apollo Client, or generating types.

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。

Jest testing patterns, factory functions, mocking strategies, and TDD workflow. Use when writing unit tests, creating test factories, or following TDD red-green-refactor cycle.

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。

Modern React UI patterns for loading states, error handling, and data fetching. Use when building UI components, handling async data, or managing UI states.

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 and maintain Nexent's repository-owned feature catalog, D1-D5 case-local contracts and fixed scripts, change records, generated execution registry and Excel view. Use for requirements, bug regressions, post-development test backfill, test implementation, and formal asset migration. Traditional UT uses nexent-python-tests.

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。

ALWAYS USE when asked to fix, rewrite, update, improve, modernize, show corrected code for, or explain existing MSTest tests or MSTest-specific configuration. Use for "review" when corrected code or edits are wanted, even for one pasted assertion or passing tests with bad failure output. Covers expected/actual labels; generic Boolean, collection, string, numeric, null, identity, exception, hard-cast, and object[] checks; TestContext/lifecycle; timeout/cancellation; OS/CI conditions, retry, cleanup, parallelization, MSTest.Sdk project setup, and MSTESTxxxx. Honor the installed MSTest version. DO NOT USE to design new test cases (code-testing), perform report-only audits, create project files rather than explain MSTest setup, run tests, migrate frameworks, or handle non-MSTest/non-.NET code.

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 this skill before answering, planning, or editing any MSTest 3.x-to-4.x upgrade or post-upgrade failure. Triggers include "MSTest v4 breaking changes"; CS0507/CS0103/CS1061/CS1615; ExecuteAsync, CallerInfo, DisplayName, or custom TestMethodAttribute; ClassCleanupBehavior; ContainsKey; ThrowsExactly or ExpectedException; IsInstanceOfType out parameters; TestTimeout.Infinite; ManagedType; net6/net7 compatibility; TestCase.Id history; TestName in ClassInitialize; TreatDiscoveryWarningsAsErrors; discovery errors after a clean build; and MSTest.Sdk/MTP or vstest.console discovery changes. Do not use for v1/v2-to-v3 leftovers, framework conversion, runner-only migration, or a general .NET upgrade.

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。

Analyze assertion quality, depth, variety, and false confidence in existing tests. ALWAYS USE when asked about weak, shallow, trivial, always-true, self-referential, assertion-free, presence/truthiness-only, or insufficiently diverse assertions, including MSTest, Jest, pytest, and Go. DO NOT USE for direct fixes: writing-mstest-tests owns supplied MSTest assertions; code-testing owns new cases. Use test-gap-analysis when asked whether tests would catch a production change, and test-anti-patterns for general severity-ranked audits.

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。

Detects duplicate boilerplate, copy-paste tests, and structural maintainability issues across .NET test suites. Use when the user asks to reduce repetition, consolidate similar test methods, convert copy-paste tests to data-driven parameterized tests, suggest a better test structure, or identify refactoring opportunities. Identifies repeated construction, assertion patterns, copy-paste methods convertible to DataRow/Theory/TestCase, redundant setup/teardown, and shared infrastructure. Produces an analysis report with concrete before/after suggestions. Works with MSTest, xUnit, NUnit, and TUnit. DO NOT USE FOR: writing new tests (use writing-mstest-tests), reviewing test quality or anti-patterns (use test-anti-patterns), or deep mock auditing (use exp-mock-usage-analysis).

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。

Learning capture system that extracts HIGH/MED/LOW confidence patterns from conversations to prevent repeating mistakes. Use after user corrections ("no", "wrong"), praise ("perfect", "exactly"), or when discovering edge cases. Complements .squad/agents/{agent}/history.md and .squad/decisions.md.

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。

Hunting skill for xxe vulnerabilities. Built from 10 public bug bounty reports including SVG-upload XXE, Office-doc (PPTX/DOCX) XXE, SOAP XXE, SAML AssertionConsumer XXE, blind OOB XXE via DTD callback, parameter-entity XXE, XXE-to-LFI, XXE-to-SSRF, and XXE-to-RCE chains (Adobe Commerce CosmicSting CVE-2024-34102). Use when hunting XXE on any target — emphasis on OOB-Or-It-Didn't-Happen Gate for blind cases.

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。

Hunting skill for ssrf vulnerabilities. Built from 15 public bug bounty reports including AWS metadata SSRF (HackerOne $25k Analytics PDF, Shopify Exchange $25k, Capital One 106M-record breach, Dropbox/HelloSign $4,913), GCP metadata SSRF (Snapchat $4k), Azure IMDS SSRF (Azure DevOps $15k chain, ChatGPT Custom Actions MSRC), DNS rebinding SSRF (Concrete CMS, GitLab UrlBlocker), gopher-protocol-to-Redis-RCE (Yahoo Mail $15k), link-preview SSRF (Reddit Matrix $6k), and headless-browser PDF-generator SSRF chains. Use when hunting SSRF on any target — OOB Collaborator confirmation mandatory for blind cases.

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。

Hunt file upload bugs — RCE via webshell, XSS via SVG/HTML, SSRF via XXE in DOCX, path traversal via filename. Bypass tables (10 techniques): double extension (shell.php.jpg if server checks last ext only), magic bytes spoofing (PNG header on PHP), null byte (shell.php.jpg), case (PHP, .Php, .pHP), .htaccess upload to enable execution, SVG with <script>, HTML/SVG XSS, DOCX with embedded XXE, ZIP slip (../../../etc/passwd in archive), polyglot files. Detection: any /upload, /avatar, /profile-picture, /attachment, /import endpoint. Test: upload PHP/JSP/ASPX shells, request via direct URL, check response. Validate: actual code execution (whoami output) for RCE; reflected XSS in profile-photo URL. Use when testing file upload features, avatar/attachment endpoints, import/export functions, XML/DOCX/ZIP processors. Real paid examples.

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。

Cloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.

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。

Hunting skill for race condition vulnerabilities. Built from 12 public bug bounty reports including modern HTTP/2 single-packet attack cases (James Kettle DEF CON 2023 "Smashing the State Machine"; RyotaK / Flatt Security 10,000-request first-sequence-sync expansion 2024). Covers coupon double-redemption, gift-card double-spend, MFA-OTP-validate race, account-create race, faucet/crypto token double-mint, email-activation race, vote/upvote inflation, password-reset token race, rate-limit bypass via concurrent requests. Use when hunting race conditions, TOCTOU bugs, MFA-bypass-via-timing.

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。

Hunting skill for business logic vulnerabilities. Built from 12 public bug bounty reports. Covers coupon-race-stacking (Instacart, Stripe, Reverb), negative-quantity-in-cart price tampering (Upserve, Eternal/Zomato), decimal/fraction price-field overflow (Shipt), client-side checkout amount trust on PayPal redirect (WordPress.org), price-per-unit mass-assignment (Krisp), and archived-price swap / cart-TOCTOU (Stripe). Use when hunting business logic — heavy emphasis on financial-impact-demonstrated cases.

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。

Hunting skill for cache poison vulnerabilities. Built from 10 public bug bounty reports including X-Forwarded-Host poisoning, X-HTTP-Method-Override / GCS cache, reflected→stored XSS via cache, classic Omer-Gil Web Cache Deception, Cloudflare Cache Deception Armor bypass, session-token cache deception, Akamai hop-by-hop smuggling → server-side edge poisoning, and Kettle's 2024 path-normalization WCD against Cloudflare/Fastly/GCP. Host/X-Forwarded-Host injection that reaches app logic (reset-link poisoning, routing SSRF, OAuth issuer) is owned by hunt-host-header; this skill owns the case where the poisoned response is CACHED and served to other users. Use when hunting cache poisoning, Web Cache Deception, CDN-fronted apps.

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, revise, evaluate, publish, and improve Open-Science Skills through the native JavaScript host.skills composer. Use when the user wants a reusable workflow, an existing Skill changed, test cases or benchmarks for a Skill, or better Skill triggering.

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。

Submit feedback about the TRES Claude plugin — bug reports, feature requests, skill improvements, new skill ideas, MCP issues, workflow friction, or positive feedback about what's working well. Use this skill whenever the user wants to share any kind of feedback about the plugin, its skills, or the TRES MCP. Trigger phrases include: "submit feedback", "report a bug", "request a feature", "suggest an improvement", "I have an idea", "something is broken", "the skill isn't working", "I love this skill", "this worked great", "the MCP is returning wrong data", "the flow is confusing", "can you fix the skill", "file a skill request", "give feedback", "this could be better". Also trigger proactively when the conversation appears to be wrapping up — e.g. the user says "thanks", "that's all", "looks good", "we're done", "nothing else", or any other signal that the task is complete. In that case, offer a brief feedback prompt instead of launching the full guided flow. Do NOT trigger for general questions about how a skill works — only when the user wants to submit feedback or the conversation is ending.

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。

Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.

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。

Academic paper writing skill with 12-agent pipeline. v2.5: Style Calibration (learn author's writing voice from past papers) + Writing Quality Check (writing quality checklist for natural prose). Supports IMRaD, literature review, theoretical, case study, policy brief, and conference paper structures. APA 7.0 (default), Chicago, MLA, IEEE, Vancouver citation formats. Bilingual abstracts (zh-TW + EN). Multi-format output (LaTeX, DOCX, PDF, Markdown). Triggers on: write paper, academic paper, paper outline, write abstract, revise paper, check citations, convert to LaTeX, guide my paper, parse reviews, revision roadmap, 寫論文, 學術論文, 論文大綱, 寫摘要, 修改論文, 檢查引用, 引導我寫論文, 帶我規劃論文, 逐章規劃, 論文架構, 審查意見, 修訂路線圖.

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。

Manually-invoked skill that renames the current thread or session to 2-5 lowercase descriptive words. Use when the user says "rename", "rename this", "rename thread", or "rename session".

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。

⚠️ CRITICAL USER EXPERIENCE-BASED SKILL - ALWAYS CONSULT BEFORE DATA PREPROCESSING ⚠️ Prevents catastrophic errors (88.9% error rate in V1.0 case study) through multi-level feature analysis, data leakage detection, and semantic validation. MANDATORY for: data preprocessing, feature engineering, standardization, normalization, interpolation, missing value handling, feature selection, or ANY data transformation task. Covers grouped time-series, cross-sectional, panel data. Detects: time travel leakage, causal inversion, ID misuse, semantic-numeric fallacies, distribution blindness. User's hard-won lessons from real project failures.

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。

Property-based testing with Hypothesis for discovering edge cases and validating invariants. Use when implementing comprehensive test coverage, testing complex logic with many inputs, or validating mathematical properties and invariants across input domains. Triggered by: hypothesis, property-based testing, @given, strategies, generative testing.

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。

Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.

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。