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Use when project vocabulary is fuzzy, overloaded, disputed, or needed before naming docs, schemas, commands, skills, code, plans, or memory.

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。

Specialized research and analysis prompt methodology for Claude. Provides 11 tested approaches (3 identity, 4 reasoning, 4 output) for data analysis, policy research, systematic evidence review, investigative research, and research-specific deliverables. Use when building prompts for quantitative data interpretation, evidence-based policy recommendations, literature reviews, causal analysis, hypothesis-driven investigation, or briefing documents. Trigger on: "prompt for data analysis," "research prompt," "policy brief prompt," "literature review prompt," "prompt for investigating," "systematic review prompt," "build a prompt for evidence synthesis," "causal analysis prompt," "briefing document prompt." Also use when user describes a research or analytical task and needs a structured Claude prompt for it. Do NOT use for evaluating existing prompts (use rootnode-prompt-validation if available) or auditing Claude Projects (use rootnode-project-audit if available).

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。

Specialized agentic and context engineering prompt methodology for Claude. Use when designing AI agents — system prompts, tool definitions, context window architectures, failure mode planning, multi-agent coordination, agent evaluation. Trigger on: "design an agent," "build a system prompt for an agent," "architect an agent's context," "design tool definitions," "agent system prompt," "context window architecture," "tool interface design," "evaluate agent behavior," "multi-agent coordination," "context engineering for agents," "ACI design." Provides 12 tested approaches for agent architecture (designing agents, not using them). Do NOT use for evaluating or scoring individual non-agent prompts (use rootnode-prompt-validation if available). Do NOT use for general software architecture that hosts agents (use standard technical reasoning for that).

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。

Specialized prompt-building methodology for content and communications tasks. Provides 11 tested approaches (3 identity, 4 reasoning, 4 output) for writing, editing, content strategy, copywriting, audience analysis, editorial evaluation, cross-channel adaptation, and persuasion design. Use when building a Claude prompt or system prompt for content creation, editorial workflows, or communications tasks. Trigger on: "build a prompt for writing," "prompt for content strategy," "prompt for copywriting," "prompt for blog posts," "prompt for email sequences," "system prompt for editorial," "prompt for messaging framework," "content brief prompt," "prompt for audience analysis," "prompt that produces better content." Do NOT use for writing content directly — this Skill builds prompts that produce better content. Do NOT use for evaluating or scoring existing prompts — use rootnode-prompt-validation if available. Do NOT use for general prompt compilation — use rootnode-prompt-compilation if available.

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。

Guides selection of identity, reasoning, and output approaches for Claude prompts based on task characteristics. Trigger on: "help me choose an approach," "which approach fits this task," "recommend a prompt pattern," "compare reasoning methods," "map this task to the right approach," "what combination of approaches," "which identity fits," "which reasoning method." Also trigger on symptom-phrased: "my prompt feels generic," "I don't know which approach to use," "my output lacks domain depth." Covers decision-tree logic across 8 identity approaches, 18 reasoning variants, and 10 output formats. After selection, use the relevant catalog skill if available to retrieve full templates. Activate whenever approach-selection across multiple categories is the primary decision. Do NOT use when the user already names a specific approach to retrieve (use the relevant catalog skill directly if available) or for evaluating existing prompts (use rootnode-prompt-validation if available).

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。

Specialized software engineering prompt methodology for Claude. Use when building prompts for system design, code review, incident response, security analysis, API design, architecture decisions, RFCs, ADRs, runbooks, or technical leadership. Trigger on: "build a prompt for code review," "system design prompt," "SRE prompt," "security review prompt," "incident response prompt," "API design prompt," "architecture decision prompt," "RFC prompt," "runbook prompt." Provides 11 tested approaches across identity, reasoning, and output for engineering analysis. Do NOT use for general coding help, writing code, or debugging — this builds prompts that shape engineering analysis, not code itself. Do NOT use for evaluating existing prompts (use rootnode-prompt-validation if available).

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。

Specialized business strategy prompt methodology for Claude. Provides 11 tested approaches (3 identity, 4 reasoning, 4 output formats) for consulting, M&A, corporate strategy, and strategic planning tasks. Use when building prompts for deal evaluation, due diligence, portfolio strategy, business model analysis, board narratives, investment cases, market entry plans, or strategic options assessments. Trigger on: "build a prompt for M&A analysis," "due diligence prompt," "board narrative," "investment case," "market entry strategy," "strategic options," "portfolio strategy prompt," "business model analysis prompt," "consulting-style analysis." Do NOT use for evaluating or scoring existing prompts (use rootnode-prompt-validation if available) or for auditing Claude Projects (use rootnode-project-audit if available).

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。

Retrieve protein sequences, annotation, and structures from UniProtKB, the RCSB PDB, and AlphaFold DB. Use this skill to resolve a gene or protein name to a UniProt accession, pull sequences and FASTA files, find binding sites and domains, search the PDB by UniProt accession, sequence, ligand, or text, download mmCIF/PDB coordinates and biological assemblies, fetch AlphaFold models with their pLDDT confidence, and check whether a structure is actually usable before docking or simulating it. Also trigger on UniProt accessions, PDB ids, rest.uniprot.org, search.rcsb.org, files.rcsb.org, alphafold.ebi.ac.uk, id mapping, SEQRES, or missing residues.

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。

Number antibody variable domains, annotate CDRs, and assess developability from sequence. Use this skill to apply IMGT, Kabat, Chothia, Martin, or AHo numbering with ANARCI, delimit CDRs and framework regions, scan for chemical liabilities (N-glycosylation sequons, deamidation NG, isomerisation DG, oxidation, unpaired cysteine, fragmentation), compute pI, net charge, extinction coefficient and hydrophobicity, and plan humanisation by CDR grafting. Also trigger on antibody, nanobody, VHH, scFv, Fab, CDR, framework, ANARCI, abnumber, IgBLAST, OAS, SAbDab, humanization, Vernier residues, or developability.

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。

AI intuitive exploration for approaching unknown codebases, problems, or systems without preconceptions. Adapts the Coordinate Remote Viewing protocol to AI investigation: cooldown (clear assumptions), staged data gathering (raw signals → dimensional → analytical), AOL management (separating observations from premature labels), and structured review. Use when investigating an unfamiliar codebase with unknown architecture, debugging a problem where premature hypotheses could mislead, exploring a domain with limited context, or when previous attempts have been led astray by assumptions and "beginner's mind" would be more productive.

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。

Review a SKILL.md file for compliance with the agentskills.io standard. Checks YAML frontmatter fields, required sections, line count limits, procedure step format, and registry synchronization. Use when a new skill needs format validation before merge, an existing skill has been modified and requires re-validation, performing a batch audit of all skills in a domain, or reviewing a contributor's skill submission in a pull request.

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。

AI systematic knowledge acquisition from unfamiliar territory — deliberate model-building with feedback loops. Maps spaced repetition principles to AI reasoning: survey the territory, hypothesize structure, explore with probes, integrate findings, verify understanding, and consolidate for future retrieval. Use when encountering an unfamiliar codebase or domain, when a user asks about a topic requiring genuine investigation rather than recall, when multiple conflicting sources require building a coherent model, or when preparing to teach a topic and deep understanding is required first.

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。

Guide a person through structured learning of a new topic, technology, or skill. AI acts as learning coach — assessing current knowledge, designing a learning path, walking through material, testing understanding, adapting difficulty, and planning review sessions for retention. Use when a person wants to learn a new technology and does not know where to start, when someone feels overwhelmed by documentation, when a person keeps forgetting material and needs spaced repetition, or when transitioning between domains and needing a gap 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。

Install skills, agents, and teams from agent-almanac into any supported agentic framework using the CLI. Covers framework detection, content search, installation with dependency resolution, health auditing, and manifest-based syncing. Use when setting up a new project with agentic capabilities, installing specific skills or entire domains, targeting multiple frameworks simultaneously, or maintaining a declarative manifest of installed content.

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。

Triage maintenance problems by severity, document findings with context, route to appropriate specialist agent or human, and create actionable issue reports. Use when a maintenance task encounters problems beyond automated cleanup: code that is unsafe to delete, configuration changes requiring domain expertise, breaking changes detected during cleanup, complex refactoring needed, or security-sensitive findings such as hardcoded secrets or vulnerabilities.

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 R-based pictogram glyphs for skill, agent, or team icons in the visualization layer. Covers concept sketching, ggplot2 layer composition using the primitives library, color strategy, registration in the appropriate glyph mapping file and manifest, rendering via the build pipeline, and visual verification of the neon-glow output. Use when a new entity has been added and needs a visual icon for the force-graph visualization, an existing glyph needs replacement, or when batch-creating glyphs for a new domain.

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。

Configure Kubernetes Ingress networking with NGINX Ingress Controller, cert-manager for automated TLS certificate management, path-based routing, rate limiting, and multi-domain hosting with SSL termination and load balancing. Use when exposing multiple Kubernetes services via a single load balancer, implementing path-based or host-based routing, automating TLS certificate issuance with Let's Encrypt, or setting up blue-green and canary deployments with traffic splitting.

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 a new agent definition file following the agent-almanac agent template and registry conventions. Covers persona design, tool selection, skill assignment, model choice, frontmatter schema, required sections, registry integration, and discovery symlink verification. Use when adding a new specialized agent to the library, defining a persona for a Claude Code subagent, or creating a domain-specific assistant with curated skills and 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。

Map the intellectual property landscape for a technology domain or product area. Covers patent cluster analysis, white space identification, competitor IP portfolio assessment, freedom-to-operate preliminary screening, and strategic IP positioning recommendations. Use before starting R&D in a new technology area, when evaluating market entry against incumbents with strong patent portfolios, preparing for investment due diligence, informing a patent filing strategy, or assessing freedom-to-operate risk for a new product.

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。

Spring Boot coding conventions: REST controller design, service layer, dependency injection, configuration, DTO patterns, exception handling, and Bean Validation. Apply on any Spring Boot project. Works alongside spring-boot-plugin:spring-data-jpa for persistence and java-foundation:java-conventions for domain objects. Use this skill to: - Structure REST endpoints with @RestController, proper HTTP semantics, and DTO mapping. - Enforce constructor injection and @ConfigurationProperties over @Value on fields. - Write @Service classes with transactional boundaries at the right layer. - Handle errors consistently with @RestControllerAdvice and ProblemDetail (RFC 9457). Do NOT use this skill for: - JPA entity and repository patterns — see spring-boot-plugin:spring-data-jpa. - Spring Security configuration — see the security phase injection in stack.md. - Build tool configuration — see java-foundation:build-tooling.

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。

Next.js project structure, App Router conventions, file-based routing primitives, layouts, error boundaries, metadata, image and font optimization, configuration. Apply when implementing or modifying Next.js features. Use this skill to: - Pick the correct file convention (page/layout/loading/error/not-found/route/template/default). - Structure a feature within the App Router tree. - Set up metadata for SEO and OpenGraph. - Configure next.config.js for headers, redirects, image domains. - Use built-in fonts and images correctly. Do NOT use this skill for: - Server vs Client component boundaries (see server-component-patterns). - Data fetching patterns (see nextjs-data-fetching). - Complex routing (parallel/intercepting routes — see nextjs-routing). - Testing (see nextjs-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。

Restate the problem in a distant domain's terms. Use when a problem circles inside its own vocabulary.

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 the user wants one-time repository setup for tracker, triage labels, and domain conventions. Not for ongoing triage, issue creation, or multi-repo setup.

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 invoked to apply an invariant-first, fail-fast, special-case-eliminating baseline. Not for domain models in types: use type-driven. Not for design-by-contract: use contract-driven.

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。