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Research-backed hook refresh workflow for updating existing hooks with TDD checkpoints and settings.json registration validation.

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。

Rules pertaining to Composer dependency management, promoting best practices for declaring and updating dependencies.

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。

Specifies best practices, including following RESTful API design principles, implementing responsive design, using Zod for data validation, and regularly updating dependencies. This skill promotes modern coding standards and helps developers write consistent, maintainable 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。

Build MySQL queries, perform CRUD operations, and manage transactions using @axiosleo/orm-mysql. Use when writing database queries, building where conditions, inserting/updating/deleting rows, managing transactions, or working with the ORM query builder in this project.

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。

Semantic versioning and changelog formatting for software releases. Use when: preparing releases, updating version numbers, writing changelogs. Keywords: version, release, changelog, semver, major, minor, patch, 版本, 發布, 變更日誌.

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。

Bring every per-repo open-pr config below the current directory up to the schema this build expects. Use after updating the plugin, or when a command reports a config too old. Takes no URL.

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。

Check all external inputs for validity - garbage in, nothing out, never garbage out

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。

Plan and freeze workflow execution by creating an Execution Contract, setting PLAN_FROZEN/CURRENT_ROLE, and updating PROJECT_STATE decisions and Top 3. Use when starting workflow delivery, re-planning after unfreeze, or when scope/constraints change before execution.

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。

Perform an adversarial review of the current uncommitted changeset, validating it against project contracts and architectural intent.

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-First SDLC compliance rules and standards. Use when checking code quality, validating architecture, enforcing zero technical debt, or making any compliance decision.

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。

Add a satisfies link from a DES → REQ, TEST → REQ/DES, or CODE annotation → ID, validating that the target exists in the registry.

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 or update a CONTEXT.md domain glossary for the current project. Establishes shared vocabulary with term definitions, avoid-aliases, and relationships so agents use consistent, concise language. This skill should be used when starting a new project, when domain terminology is inconsistent across sessions, when the user says "build a glossary", "define our terms", "shared vocabulary", or "domain language", or when an existing CONTEXT.md needs updating after new domain concepts emerge.

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。

Agent Brain /brain-wiki: ingesting sources or updating durable project knowledge.

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 a local coding agent (Codex, Claude Code, Cursor, or similar) needs to operate Multica through the authenticated `multica` CLI: reading or updating issues, comments, metadata, labels, custom properties, subscribers, projects, agents, squads, runtimes, repos, skills, autopilots, attachments, or workspace state; searching issues; inspecting or cancelling agent runs; replying to a Multica issue from an external agent; creating or triaging issues; checking linked pull requests; or safely handling Multica mention/status side effects without relying on the Multica hosted agent runtime.

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 data analysis for quality, correctness, and reproducibility. Covers data quality assessment, assumption checking, model validation, data leakage detection, and reproducibility verification. Use when reviewing a colleague's analysis before publication, validating an ML pipeline before production deployment, auditing a report for regulatory or business decision-making, or performing a second-analyst review in a regulated environment.

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 and execute A/B tests for ML models in production using traffic splitting, statistical significance testing, and canary/shadow deployment strategies. Measure performance differences and make data-driven decisions about model rollout. Use when validating a new model version before full rollout, comparing candidate models trained with different algorithms, measuring business metric impact of model changes, or when regulatory requirements mandate gradual rollout.

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。

Manage R package dependencies using renv for reproducible environments. Covers initialization, snapshot/restore workflow, troubleshooting common issues, and CI/CD integration. Use when initializing dependency management for a new R project, adding or updating packages, restoring an environment on a new machine, troubleshooting restore failures, or integrating renv with CI/CD pipelines.

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。

Decommission a validated computerized system at end-of-life. Covers data retention assessment by regulation, data migration validation (mapping, transformation, reconciliation), archival strategy, access revocation, documentation archival, and stakeholder notification. Use when a validated system is being replaced, reaching end-of-life without replacement, vendor support is discontinued, multiple systems are consolidating, or regulatory changes render a system obsolete.

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。

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。

Set up centralized log aggregation with Loki and Promtail (or ELK stack), including log parsing, label extraction, retention policies, and integration with metrics for correlation. Use when consolidating logs from multiple services into a searchable system, replacing local log files with centralized queryable storage, correlating logs with metrics and traces, implementing structured logging with label extraction, or troubleshooting production incidents requiring cross-service log 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。

Analyze the dynamics of diffusion processes using stochastic differential equations, Fokker-Planck equations, first-passage time distributions, and parameter sensitivity analysis. Use when deriving probability density evolution for a continuous-time diffusion process, computing mean first-passage times for bounded diffusion, analyzing how drift and diffusion parameters affect process behavior, or validating closed-form solutions against stochastic 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。

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), RNAi DEMETER2 scores, PRISM compound sensitivity, and gene effect profiles across the cell-line panel. Use for identifying cancer-selective vulnerabilities, separating pan-essential genes from selective ones, finding synthetic lethal interactions, correlating dependency with mutation, expression and copy number, and validating oncology drug targets. Also trigger on DepMap, Chronos gene effect, CRISPRGeneEffect.csv, DEMETER2, PRISM repurposing, co-essentiality, pan-essential, or ACH- cell line 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。