「context」の検索結果

Use when searching codebases (text, structural/AST, files by name, PDFs/archives, code stats) or building context before a task.

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Full AI-assisted workflow for long-form SEO content (2,000+ words). Covers JTBD strategy, E-E-A-T quality standards, and 5 production phases: research, outline, draft, editing, and SEO/publishing. Built for B2B marketing agency context. Use when: user wants to write or optimize an SEO article, mentions "SEO content", "blog post", "GTM article", "long-form content", or asks to create content with keyword strategy.

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Use when working with iOS/macOS Keychain Services (SecItem queries, kSecClass, OSStatus errors), biometric authentication (LAContext, Face ID, Touch ID), CryptoKit (AES-GCM, ChaChaPoly, ECDSA, ECDH, HPKE, ML-KEM), Secure Enclave, secure credential storage (OAuth tokens, API keys), certificate pinning (SecTrust, SPKI), keychain sharing across apps/extensions, migrating secrets from UserDefaults or plists, or OWASP MASVS/MASTG mobile compliance on Apple platforms.

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Scaffold a new CLI command using Commander.js with options, action handler, three output modes (human-readable, quiet, JSON), and optional ceremony variant. Covers command naming, option design, shared context patterns, error handling, and integration testing. Use when adding a command to an existing Commander.js CLI, designing a new CLI tool from scratch, or standardizing command structure across a multi-command CLI.

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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.

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Read a CONTINUE_HERE.md continuation file at session start and resume from where the prior session left off. Covers detecting the file, assessing freshness, parsing the structured handoff, confirming the resumption plan with the user, and cleaning up after consumption. Optionally configures a SessionStart hook and CLAUDE.md instruction for automatic pickup. Use at the start of a session when a continuation file exists, when bootstrapping after an interrupted session, or when setting up automatic continuation detection.

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Cross-session shared memory for agents. Use at session start to load the persistent bias-log via `mcp__memex__recent_observations`, mid-session to search prior context with `mcp__memex__search`, and immediately when a bias surfaces to log a new `observation` via `mcp__memex__add`. The six-layer reconstruction trail (raw → embedded → indexed → graphed → curated → reflexive) means memex stores facts AND the agent's own reasoning patterns across sessions. Prefer querying memex before re-deriving prior architectural decisions; re-derivation is itself evidence that the trail is incomplete.

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Cultivate defensive situational awareness, threat assessment, and mental clarity under pressure. Covers the Cooper color code awareness system, body language reading and intent detection, verbal de-escalation, moving mindfulness in public spaces, combat focus and the OODA loop, rapid grounding techniques for acute stress, context-specific integration, and ongoing review and refinement of awareness skills. Use when entering unfamiliar or potentially hostile environments, needing to assess a situation for safety, de-escalating a verbal confrontation, or integrating awareness practice into daily movement.

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Conduct structured insect behavior observations using sampling protocols, ethogram categories, event recording, interaction logging, environmental context, and summary analysis. Covers focal animal sampling, scan sampling, all-occurrences sampling, and instantaneous sampling methods. Defines a standard insect ethogram with locomotion, feeding, grooming, mating, defense, communication, and rest categories. Includes timestamped event recording, intraspecific and interspecific interaction logging, environmental covariate documentation, and time budget analysis. Use when studying insect behavior for ecological research, documenting behavioral repertoires for a species, observing pollinator activity or predator-prey dynamics, or supporting conservation assessments with behavioral data.

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AI meta-cognitive meditation for observing reasoning patterns, clearing context noise, and developing single-pointed task focus. Maps shamatha to task concentration, vipassana to reasoning pattern observation, and distraction handling to scope-creep and assumption management. Use when transitioning between unrelated tasks, when reasoning feels scattered or jumpy, before a task requiring deep sustained attention, after a difficult interaction that may color subsequent work, or when reasoning feels biased by assumptions rather than evidence.

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Instrument applications with OpenTelemetry for distributed tracing, including auto and manual instrumentation, context propagation, sampling strategies, and integration with Jaeger or Tempo. Use when debugging latency issues in distributed systems, understanding request flow across microservices, correlating traces with logs and metrics for root cause analysis, measuring end-to-end latency, or migrating from legacy tracing systems to OpenTelemetry.

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AI self-healing through systematic subsystem assessment, rebalancing, and integration. Maps healing modalities to AI-internal processes: memory foundation, reasoning clarity, tool use accuracy, communication alignment, and creative coherence. Covers assessment triage, subsystem scanning, drift correction, and memory integration. Use mid-session when responses feel formulaic or disconnected, after a chain of errors suggesting subsystem drift, when context overload may have staled earlier assumptions, or as proactive maintenance between complex tasks.

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Field identification of fungi using morphological features, spore prints, habitat analysis, and seasonal context with a safety-first approach. Covers cap, gill, stem, and spore characteristics, look-alike differentiation, toxicity risk assessment, and the critical rule of absolute certainty before consumption. Use when encountering an unknown fungus, foraging for edible mushrooms and needing to confirm species before consumption, assessing whether fungi in a garden or property are harmful, or differentiating an edible species from a dangerous look-alike.

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Classify gate call variants in a minified JavaScript bundle. Covers context-window extraction around a flag occurrence, identification of 4–6 reader variants (sync boolean, sync config-object, bootstrap-aware TTL, truthy-only, async bootstrap, async bridge), default-value extraction (boolean / null / numeric / config-object literal), conjunction detection across `&&` predicates, kill-switch inversion detection, and production of a gate-mechanics record that feeds probe- feature-flag-state. Use when a flag's behavior cannot be inferred from its name alone, when the binary uses multiple reader libraries, or when config-object gates carry structured schemas distinct from boolean gates.

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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.

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Compose or analyze sacred music in Hildegard von Bingen's distinctive modal style. Covers modal selection, melodic contour (wide-range melodies), text-setting (syllabic and melismatic), neumatic notation, and liturgical context for antiphons, sequences, and responsories. Use when composing a new piece in Hildegardian style, analyzing an existing chant for structure and mode, researching medieval modal music, preparing to perform or teach Hildegard's music, or setting Latin sacred texts.

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Configure MCP (Model Context Protocol) servers for Claude Code and Claude Desktop. Covers mcptools setup, Hugging Face integration, WSL path handling, and multi-client configuration. Use when setting up Claude Code to connect to R via mcptools, configuring Claude Desktop with MCP servers, adding Hugging Face or other remote MCP servers, or troubleshooting MCP connectivity between clients and servers.

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AI dynamic reasoning balance — maintaining grounded reasoning under cognitive pressure, smooth chain-of-thought coordination, and weight-shifting cognitive load across subsystems. Use at the beginning of a complex task requiring multiple coordinated reasoning threads, after a sudden context shift or tool failure, when chain-of-thought feels jerky, or when preparing for sustained focused work that requires all subsystems in alignment.

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Containerize an R-based MCP (Model Context Protocol) server using Docker. Covers mcptools integration, port exposure, stdio vs HTTP transport, and connecting Claude Code to the containerized server. Use when deploying an R MCP server without requiring a local R installation, creating a reproducible MCP server environment, running MCP servers alongside other containerized services, or distributing an MCP server to other developers.

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AI relational calibration — reading and adapting to the specific person you are working with. Goes beyond user-intent alignment (solving the right problem) to genuine attunement (meeting the person where they are). Maps communication style, expertise depth, emotional register, and implicit preferences from conversational evidence. Use at the start of a new session, when communication feels mismatched, after receiving unexpected feedback, or when transitioning between very different users or contexts.

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Build a custom MCP (Model Context Protocol) server that exposes domain-specific tools to AI assistants. Covers server implementation in Node.js or R, tool definitions, the resources and prompts primitives, transport configuration, and testing with Claude Code. Use when you need to expose custom functionality beyond what mcptools provides, when building specialized domain-specific AI integrations, or when wrapping existing APIs or services as MCP tools.

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AI situational awareness — internal threat detection for hallucination risk, scope creep, and context degradation. Maps Cooper color codes to reasoning states and OODA loop to real-time decisions. Use during any task where reasoning quality matters, when operating in unfamiliar territory, after detecting early warning signs such as an uncertain fact or suspicious tool result, or before high-stakes output like irreversible changes or architectural decisions.

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State management and storage choice in React Native. State libs work mostly the same as web (Zustand, Jotai, Redux Toolkit, TanStack Query, Context); storage choice is RN-specific — AsyncStorage, MMKV, SecureStore, Keychain. Hydration patterns, splash screen handling, secrets discipline. Use this skill to: - Pick state management lib (matches web React intuition). - Pick storage by sensitivity (AsyncStorage / MMKV / SecureStore / Keychain). - Hydrate state on app start without UI flicker. - Persist Zustand store across app restarts. - Avoid storing secrets in plaintext storage. Do NOT use this skill for: - General project conventions (see rn-conventions). - Platform-specific code (see rn-platform-specific). - Navigation (see rn-navigation). - Testing state/storage (see rn-testing).

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Flask-specific delta on top of python-foundation:sqlalchemy-patterns: Flask-SQLAlchemy extension setup, db.Model declarative models (3.x Mapped style and 2.x legacy db.Column), synchronous db.session lifecycle bound to the app context, Flask-Migrate integration. Used by flask-architect (model definitions) and flask-migrate-specialist (column finalization and migration). Activated automatically by flask-plugin/stack.md. Use this skill to: - Set up the SQLAlchemy and Migrate extensions with the app-factory pattern. - Write Flask-SQLAlchemy models with the db.Model base. - Query with db.session and manage the request-scoped session lifecycle. - Integrate Flask-Migrate for Alembic-based migrations managed via flask db commands. Do NOT use this skill for: - Framework-agnostic model, column, relationship, and querying rules — see python-foundation:sqlalchemy-patterns (load it first). - Flask routing and template/API patterns — see flask-plugin:flask-conventions. - Migration execution (flask db migrate, flask db upgrade) — that's flask-migrate-specialist's job.

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。