Governance, risk, and compliance — risk assessment and scoring, control mapping across NIST CSF 2.0 / ISO 27001:2022 / SOC 2 / CIS Controls v8, gap analysis, audit evidence preparation, and security policy generation
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Governance, risk, and compliance — risk assessment and scoring, control mapping across NIST CSF 2.0 / ISO 27001:2022 / SOC 2 / CIS Controls v8, gap analysis, audit evidence preparation, and security policy generation
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。
IOC extraction, threat intelligence correlation, MITRE ATT&CK mapping, hunt hypothesis generation, and detection rule creation
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 design, review, or improve validation in Micronaut applications — including Bean Validation on @Controller methods, @Body @Valid, query/path parameter validation, @ConfigurationProperties validation, custom constraints, nested DTO validation, and ExceptionHandler mapping for constraint violations. This should trigger for requests such as Add validation support in Micronaut; Review Micronaut validation rules; Improve request validation in Micronaut REST APIs; Add custom validation constraints in Micronaut; Validate Micronaut configuration properties. 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 write or review programmatic JDBC with Spring — including JdbcClient (Spring Framework 7+) as the default API, JdbcTemplate only where batch/streaming APIs require JdbcOperations, NamedParameterJdbcTemplate for legacy named-param code, parameterized SQL, RowMapper mapping to records, batch operations, transactions, safe handling of generated keys, DataAccessException handling, read-only transactions, streaming large result sets, and @JdbcTest slice testing. This should trigger for requests such as Review Java code for Spring JDBC (JdbcTemplate, JdbcClient, NamedParameterJdbcTemplate); Apply best practices for Spring JDBC data access in Java code; Detect and fix SQL injection risks in JDBC code; Improve transaction boundaries or exception handling for JDBC operations; Review JdbcClient usage in Spring Framework 7. 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 design, review, or improve security in Quarkus applications — including Quarkus Security with JWT/OIDC, basic auth, @RolesAllowed / @Authenticated / @PermitAll, SecurityIdentity, permission checks, path-based authorization in configuration, exception mapping for auth failures, and sensitive-data-safe logging. This should trigger for requests such as Add Quarkus security support; Review Quarkus security configuration; Improve API authorization in Quarkus; Add JWT/OIDC security in Quarkus; Harden Quarkus authorization rules. 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 set up, review, or improve Java integration tests — including generating a BaseIntegrationTest.java with WireMock for HTTP stubs, detecting HTTP client infrastructure from import signals, injecting service coordinates dynamically via System.setProperty(), creating WireMock JSON mapping files with bodyFileName, isolating stubs per test method, verifying HTTP interactions, or eliminating anti-patterns such as Mockito-mocked HTTP clients or globally registered WireMock stubs. This should trigger for requests such as Review Java code for integration tests; Apply best practices for integration tests in Java code; Write Java integration tests with real infrastructure boundaries; Improve Testcontainers integration tests for Java code; Review integration test setup and teardown in Java projects. 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 first encountering an unknown binary, ELF file, executable, or firmware blob. Fast fingerprinting via rabin2 - architecture detection (ARM, x86, MIPS), ABI identification, dependency mapping, string extraction. Keywords - "what is this binary", "identify architecture", "check file type", "rabin2", "file analysis", "quick scan"
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Translate a complete mathematical modeling contest problem sentence by sentence into precise modeling language, preserve every substantive condition and definition, expose hidden constraints, draw a mandatory Mermaid cross-question flowchart, audit omissions, and deliver one easy-to-open Markdown report. For Huawei Cup (CPGMCM) graduate-contest problems, additionally prepend a plain-language layer that rewrites the background and questions as a primary-school word problem with a mandatory term-mapping table. Optionally render the finished report as one standalone HTML page on request. Use whenever a user supplies a CUMCM, CPGMCM, or other modeling problem and asks to interpret, translate, unpack, read closely, identify requirements, or avoid missing details before modeling.
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Enhancement overlay for multi-agent / tool-using coder agents. Encodes the per-agent tool- scoping discipline that role-based frameworks (CrewAI, LangChain) document only as a passing best-practice: which agent gets which tool, and why blanket-sharing every tool to every agent is a correctness and blast-radius risk. Activates when an agent system has tools AND there is more than one agent (or one agent holding many tools). Treat a tool as a capability grant; scope by least-privilege. ENHANCE overlay — read alongside [[crewai]], [[agentsop-http-tool-wrapping]], [[agentsop-llm-tool-idempotency]]. Search keywords: which tools per agent, least-privilege agent, agent tool access, tool permissions, limit agent tools, scope tools to roles.overlay_type: enhancement
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Routes heterogeneous queries to the appropriate index, tool, or answering engine before retrieval. Use when one endpoint serves multiple handlers, such as summary, vector retrieval, text-to-SQL, or tools, and query types require different paths. Covers LLM, semantic, and rule-based routers, confidence thresholds, fallbacks, and framework mappings. Do not use when one handler serves all queries or branching is fixed.
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Pick an LM output format per (task x consumer x model) rather than by reflex: different formats carry different cognitive load (e.g. code-in-JSON makes the same model write worse code than plain-text+diff, while asking for prose when you need a typed object fails the other way). Use when designing or debugging an LM's output schema, choosing between plain text / diff / JSON / tool-call / grammar-constrained output, or when a model's quality drops after wrapping its output in a structured format.
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Use when managing multiple initiatives across time horizons (now/next/later, H1/H2/H3), balancing risk vs return across portfolio, sizing and sequencing bets with dependencies, setting exit/scale criteria for experiments, allocating resources across innovation types (core/adjacent/transformational), or when user mentions portfolio planning, roadmap horizons, betting framework, initiative prioritization, innovation portfolio, or resource allocation across horizons.
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Create 600x600 Instagram-style card news series automatically with optional background images. User provides topic, colors, and optional images - Claude generates content and creates multiple cards with proper text wrapping.
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Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database).
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Complete Product Owner / Product Manager capability — a wiki-style knowledge map of product practice in active software development: the role and its boundaries, strategy cascade (vision → OKRs → roadmap → backlog), continuous discovery, backlog craft (epics, INVEST stories, acceptance criteria), prioritization frameworks (RICE, MoSCoW, Kano, WSJF), sprint delivery, metrics (North Star, AARRR), stakeholder management, and anti-patterns. The PO/PM owns what gets built, in what order, and why — including the end-to-end user flows and user journeys. Use when scoping a product or feature, decomposing an idea into outcomes/epics/stories, prioritizing a backlog, defining an MVP, mapping user journeys, measuring success, or saying no to a stakeholder. Pairs with super-ui-ux-design, which owns how each screen looks and behaves.
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Step-by-step migration guides for moving to Playwright from Cypress or Selenium/WebDriver — command mappings, architecture changes, and incremental adoption strategies.
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Set up Tailwind v4 with shadcn/ui using @theme inline pattern and CSS variable architecture. Four-step pattern: CSS variables, Tailwind mapping, base styles, automatic dark mode. Prevents 8 documented errors. Use when initializing React projects with Tailwind v4, or fixing colors not working, tw-animate-css errors, @theme inline dark mode conflicts, @apply breaking, v3 migration 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。
Step-by-step migration guides for moving to Playwright from Cypress or Selenium/WebDriver — command mappings, architecture changes, and incremental adoption strategies.
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。
Build responsive, readable charts with Recharts using correct data mapping and composition. Use whenever creating charts with Recharts — LineChart, BarChart, AreaChart, PieChart, wrapped in ResponsiveContainer with a fixed-height parent. Not for charts built with other libraries.
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Focuses on type scale, spacing, sizing, variable fonts, OpenType features, wrapping, truncation and other details that make typography feel great across your product.
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Unified Python interface to 40+ bioinformatics web services: UniProt proteins, KEGG pathways, ChEMBL/ChEBI/PubChem, BLAST, cross-database ID mapping, GO annotations, PPI. For deep single-DB queries use dedicated tools (gget for Ensembl, pubchempy for PubChem); bioservices excels at cross-database workflows.
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Query ReMap 2022 TF ChIP-seq peak database via REST API and BED downloads. Retrieve TF peaks overlapping a region (chr:start-end), peaks near a gene, TFs by species, peaks filtered by biotype (promoter, enhancer), and BED files for a TF-cell type pair. Use for TF co-occupancy, regulatory annotation, and TF binding atlases. Use jaspar-database for PWM motifs; encode-database for ENCODE tracks.
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Counts RNA-seq reads overlapping GTF gene features. Takes sorted STAR BAMs plus GTF; outputs a per-gene tab-delimited matrix across samples. Handles strandedness (0/1/2), paired-end, multi-sample batch counting in one command, and outputs assignment statistics. Use Salmon for alignment-free quantification; use featureCounts when STAR BAMs already exist.
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Ultra-fast RNA-seq transcript/gene quantification via quasi-mapping (no BAM). Builds a k-mer index from transcriptome FASTA, quantifies in minutes. Outputs TPM/count tables (quant.sf) with optional GC- and sequence-bias correction. Integrates with tximeta/tximport for DESeq2/edgeR. Use STAR when a genome-aligned BAM is needed.
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。