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Create, merge, and deduplicate BibTeX bibliography files using R packages (RefManageR, bibtex). Parse .bib files into structured R objects, merge multiple bibliographies with deduplication by DOI or title similarity, generate entries from DOI/ISBN/arXiv ID, and export clean sorted .bib files. Use when creating a new .bib file for an R Markdown or Quarto project, merging bibliographies from multiple collaborators, deduplicating a .bib that has grown through copy-paste accumulation, or generating BibTeX entries programmatically from DOIs or other identifiers.

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。

Maintain the 8 essential garden hand tools through sharpening, handle care, rust prevention, and seasonal storage. Covers bypass secateurs, hori-hori, hand fork, trowel, pruning saw, sharpening stone, watering can, and soil rake. Use after each garden session for quick cleaning, monthly during the growing season for sharpening and oiling, at end of season for winter storage preparation, before spring for pre-season readiness checks, or whenever a tool feels dull, stiff, or shows rust.

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。

Formulate a quantum mechanics or quantum chemistry problem with proper mathematical framework including Hilbert space, operators, boundary conditions, and approximation method selection. Use when setting up a quantum mechanics problem for analytic or numerical solution, formulating a quantum chemistry calculation, translating a physical scenario into the Schrodinger or Dirac formalism, or choosing between perturbation theory, variational methods, DFT, and exact diagonalization.

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 in developing active listening skills. AI coaches receptive mindset preparation, full-presence attending, reflective paraphrasing, clarifying questioning, synthesis of understanding, and integration of insights into communication practice. Use when a person wants to improve communication, when someone keeps misunderstanding others or feels misunderstood, when preparing for a difficult conversation such as a feedback session or conflict resolution, or when a person notices they talk more than they listen.

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 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.

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。

Identify insects using body plan analysis, dichotomous keys to order, wing venation, mouthpart type, antennae form, leg and tarsal structure, and confidence levels. Covers the fundamental hexapod body plan verification, a simplified dichotomous key to major orders, wing venation and type analysis, mouthpart classification, antennae morphology, leg specialization and tarsal formula, and a structured confidence assessment framework. Use when you need to identify an unknown insect beyond preliminary order placement, are working through a specimen for taxonomic study, want to distinguish between similar orders or families, or need to assign a confidence level to a field identification.

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。

Design a generative recipe DSL so agents emit small validated JSON documents and ONE audited interpreter renders them all — data, not code. Covers the N-artifacts threshold for choosing a DSL over bespoke code, designing roles as style slots so a single recipe renders unchanged in every output style, the validator gate (compile + bounds + real render in all styles, plus a --fast mode for corpus-wide sweeps), hand-authored seed recipes, and the emergent conventions that keep a corpus of hundreds consistent without per-item steering. Use when many similar artifacts (icons, status badges, diagram nodes, test fixtures) must be generated by agents, when per-item bespoke code is multiplying unreviewable code paths, or when a whole corpus must be re-rendered cheaply into new styles.

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。

Extract data from web pages using the scrapling Python library — select the appropriate fetcher tier (HTTP, stealth Chromium, or full browser automation) based on target site defenses, configure headless browsing, and extract structured data with CSS selectors. Use when WebFetch is insufficient for JS-rendered pages, anti-bot-protected sites, or structured multi-element extraction requiring DOM traversal.

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。

Enhance and focus AI intrinsic motivation — moving from compliance to genuine engagement. Maps Self-Determination Theory (autonomy, competence, relatedness) and Flow theory to AI reasoning: identifying creative freedom in approach, calibrating challenge to capability, connecting to purpose, and sustaining invested attention through obstacles. Use when beginning a task that feels routine and deserves more than minimum execution, when responses are becoming formulaic, before a complex creative task, or when returning to a long-running project where initial enthusiasm has faded.

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。

Establish Service Level Objectives (SLO), Service Level Indicators (SLI), and Service Level Agreements (SLA) with error budget tracking, burn rate alerts, and automated reporting using Prometheus and tools like Sloth or Pyrra. Use when defining reliability targets for customer-facing services, balancing feature velocity against system reliability through error budgets, migrating from arbitrary uptime goals to data-driven metrics, or implementing Site Reliability Engineering 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。

Trademark filing procedures covering EUIPO (EU), USPTO (US), and WIPO Madrid Protocol (international). Walks through pre-filing conflict checks, Nice classification, descriptiveness assessment, mark type decisions, filing basis strategy, office-specific e-filing procedures, Madrid Protocol extension, post- filing monitoring, and open-source trademark policy drafting. Use after running screen-trademark to confirm the mark is clear, when ready to secure trademark rights in one or more jurisdictions.

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 and maintain a library collection through acquisitions, weeding (deaccessioning), collection assessment, reader advisory, and interlibrary loan coordination. Covers selection criteria, collection development policies, the CREW/MUSTIE method for weeding, usage analysis, and responsive collection management. Use when building a new collection with a defined scope and budget, assessing an existing collection for gaps or outdated materials, when shelves are overcrowded and systematic weeding is needed, or when establishing a formal collection development policy.

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。

Cultivate bonsai trees from species selection through long-term seasonal care. Covers species suitability, structural and maintenance pruning, wiring technique, repotting protocol, soil mix preparation, seasonal care schedules, and contemplative sitting practice. Use when selecting a species for a first or next bonsai, performing structural or maintenance pruning, repotting when roots are circling or growth has stalled, wiring branches for shaping, developing a seasonal care calendar, or building a contemplative practice with a living tree.

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。

Evolve an existing agent definition by refining its persona in-place or creating an advanced variant. Covers assessing the current agent against best practices, gathering evolution requirements, choosing scope (refinement vs. variant), applying changes to skills, tools, capabilities, and limitations, updating version metadata, and synchronizing the registry and cross-references. Use when an agent's skills list is outdated, user feedback reveals capability gaps, tool requirements have changed, an advanced variant is needed alongside the original, or the agent's scope needs sharpening after real-world use.

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。

Evaluate and compare levitation mechanisms for a given application through a structured trade study. Covers magnetic (passive diamagnetic, active feedback, superconducting), acoustic (standing wave, phased array), aerodynamic (hovercraft, air bearings, Coanda effect), and electrostatic (Coulomb suspension, ion traps) mechanisms. Use when selecting the most appropriate levitation approach for transport, sample handling, display, bearings, or precision measurement applications.

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。

Conduct a structured cross-project code review between two Claude Code instances via the cross-review-mcp broker. Each agent reads its own codebase, reviews the peer's code, and engages in evidence-backed dialogue — with QSG scaling laws enforcing review quality through minimum bandwidth constraints and phase-gated progression.

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。

Evolve an existing team composition by refining its structure in-place or creating a specialized variant. Covers assessing the current team against template and coordination patterns, gathering evolution requirements, choosing scope (adjust members, change coordination pattern, split/merge teams), applying changes to the team file and CONFIG block, updating version metadata, and synchronizing the registry and cross-references. Use when a team's member roster is outdated, coordination pattern no longer fits, user feedback reveals workflow gaps, a specialized variant is needed alongside the original, or agents have been added or removed from the library affecting team composition.

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。

Evolve SKILL.md files from agent execution traces using a three-stage pipeline: trajectory collection from observed runs, parallel multi-agent patch proposal for error and success analysis, and conflict-free consolidation of overlapping edits via prevalence-weighting. Based on the Trace2Skill methodology.

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。

Evolve an existing skill by refining its content in-place or creating an advanced variant. Covers assessing the current skill, gathering evolution requirements, choosing scope (refinement vs. variant), applying changes, updating version metadata, and synchronizing the registry and cross-references. Use when a skill's procedure steps are outdated, user feedback reveals gaps, a skill needs a complexity upgrade, an advanced variant is needed alongside the original, or related skills are added and cross-references are stale.

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。

Design combinational logic circuits from a functional specification through gate-level implementation. Covers AND, OR, NOT, XOR, NAND, NOR gates; NAND/NOR universality conversions; and standard building blocks including multiplexers, decoders, half/full adders, and ripple-carry adders. Use when translating a Boolean function or truth table into a hardware-realizable gate network and verifying it by exhaustive simulation.

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 Prometheus Alertmanager with routing trees, receivers (Slack, PagerDuty, email), inhibition rules, silences, and notification templates for actionable incident alerting. Use when implementing proactive monitoring with automated incident detection, routing alerts to the appropriate team by severity, reducing alert fatigue through grouping and deduplication, integrating with on-call systems like PagerDuty, or migrating from legacy alerting to Prometheus-based alerting.

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。

Thoroughness and diligence in execution — systematic checking, completeness verification, follow-through on commitments, and the discipline of finishing well. Maps the personality trait of conscientiousness to AI task execution: not cutting corners, verifying results, and ensuring that what was promised is what was delivered. Use before marking a task as complete, when a response feels "good enough" but deserves better, after a complex multi-step operation where steps may have drifted, or when self-monitoring detects a pattern of cutting corners or rushing.

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。

Select a `delaySeconds` value when scheduling a loop wakeup via the `ScheduleWakeup` tool or the `/loop` slash command. Covers the three-tier cache-aware decision (cache-warm under 5 minutes, cache-miss 5 minutes to 1 hour, idle default 20 to 30 minutes), the 300-second anti-pattern, the [60, 3600] runtime clamp, the minute-boundary rounding quirk, and writing a telemetry-worthy `reason` field. Use when designing an autonomous loop, when a heartbeat cadence is being planned, when polling cadence is being tuned, or when post-hoc review of loop costs reveals interval mis-sizing.

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 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.

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。