「improve」の検索結果

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 design, review, or improve security in Micronaut applications — including micronaut-security authentication, @Secured and intercept-url-map rules, JWT/session strategies, SecurityService checks, CORS, CSRF awareness for browser apps, rejection handlers, and sensitive-data-safe logging. This should trigger for requests such as Add Micronaut security support; Review Micronaut security configuration; Improve API authorization in Micronaut; Add JWT security in Micronaut; Harden Micronaut route 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 review, improve, or refactor Java code for type design quality — including establishing clear type hierarchies, applying consistent naming conventions, eliminating primitive obsession with domain-specific value objects, leveraging generic type parameters, creating type-safe wrappers, designing fluent interfaces, ensuring precision-appropriate numeric types (BigDecimal for financial calculations), and improving type contrast through interfaces and method signature alignment. This should trigger for requests such as Review Java code for type design; Improve type design in Java code; Fix primitive obsession in Java code; Create value objects in Java code. 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 review, improve, or write Java unit tests — including migrating from JUnit 4 to JUnit 5, adopting AssertJ for fluent assertions, structuring tests with Given-When-Then, ensuring test independence, applying parameterized tests, mocking dependencies with Mockito, verifying boundary conditions (RIGHT-BICEP, CORRECT, A-TRIP), leveraging JSpecify null-safety annotations, or eliminating testing anti-patterns such as reflection-based tests or shared mutable state. This should trigger for requests such as Review Java code for unit tests; Apply best practices for unit tests in Java code; Write fast JUnit unit tests for Java code; Improve Mockito-based Java unit tests; Refactor Java tests to isolate collaborators. 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 you need to apply functional programming principles in Java — including writing immutable objects and Records, pure functions, functional interfaces, lambda expressions, Stream API pipelines, Optional for null safety, function composition, higher-order functions, pattern matching for instanceof and switch, sealed classes/interfaces for controlled hierarchies, Stream Gatherers for custom operations, currying/partial application, effect boundary separation, and concurrent-safe functional patterns. This should trigger for requests such as Improve the code with Functional Programming; Apply Functional Programming; Refactor the code with Functional Programming; Refactor Java code to use streams or Optionals safely; Improve immutability and pure functions in Java. 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 refactor Java code for high performance — including memory/allocation reduction, CPU hot-path optimization, and syntax/API/control-flow improvements. This should trigger for requests such as Review Java code for high performance; Optimize Java hot path; Reduce Java allocations; Improve Java latency/throughput. 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。

Build, run, and improve a Security Operations Center — alert prioritization, runbook authoring, escalation criteria, on-call structure, alert tuning workflow, MTTD / MTTR / fidelity KPIs, analyst tiering, and shift handoffs. Use when the user mentions 'SOC,' 'security operations,' 'SOC analyst,' 'alert triage workflow,' 'runbook,' 'escalation,' 'on-call,' 'SOC tiering,' 'tier 1 / tier 2,' 'MTTD,' 'MTTR,' 'alert fatigue,' 'alert tuning,' 'shift handoff,' 'SOAR,' or wants to design or improve a security operations team.

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 to write, structure, or revise academic paper sections, improve notation consistency, or refine figures and tables. Triggers on phrases like "write the abstract", "structure the methods", "improve this section", "notation consistency", "figure refinement", or "paper structure".

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 lessons from the current session, or sweep the project's past sessions when asked, and route them to the appropriate knowledge layer (project AGENTS.md, auto memory, existing skills, or new skills). Use when the user asks to "self-improve", "distill this session", "distill past sessions", "sweep past sessions", "extract lessons from all sessions", "save learnings", "update AGENTS.md with what we learned", "capture session insights", "remember this for next time", "extract lessons", "update skills from session", or "what did we learn".

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 lessons from the current session, or sweep the project's past sessions when asked, and route them to the appropriate knowledge layer (project AGENTS.md, auto memory, existing skills, or new skills). Use when the user asks to "self-improve", "distill this session", "distill past sessions", "sweep past sessions", "extract lessons from all sessions", "save learnings", "update CLAUDE.md with what we learned", "capture session insights", "remember this for next time", "extract lessons", "update skills from session", or "what did we learn".

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。

Propose a turbo skill improvement upstream by filing a GitHub issue against the turbo repo. Use when the user asks to "contribute to turbo", "submit turbo changes", "contribute back", "suggest a turbo improvement", or "upstream my changes".

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。

Audit the turbo skill lessons that /self-improve writes into this repo's .turbo/handoff/ from other projects, apply the ones the user approves, delete the consumed handoffs, commit and push, and update the installed Turbo skills. Use when the user asks to "read .turbo/handoff and let me know what you think", "read the handoff files and let me know what you think", "review the lesson handoffs", "apply the self-improve handoffs", or "process the turbo handoffs".

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。

Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.

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。

Edit and improve articles by restructuring sections, improving clarity, and tightening prose. Use when user wants to edit, revise, or improve an article draft.

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。

Provides comprehensive memory file management capabilities including auditing, quality assessment, and targeted improvements for files such as CLAUDE.md. Use when user asks to check, audit, update, improve, fix, maintain, or validate project memory files. Also triggers for "project memory optimization", "CLAUDE.md quality check", "documentation review", or when a project memory file needs to be created from scratch. This skill scans memory files, evaluates quality against standardized criteria, outputs detailed quality reports with scores and recommendations, then makes targeted updates with user approval.

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。

Improves a voice profile by learning from manual edits. Use after editing generated text to refine registers and close voice drift over time.

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。

Evaluates and improves skills, agents, commands, and hooks after a workflow slice. Use when execution felt slow, confusing, repetitive, or fragile.

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 and improve the improvement process. Use for detecting regressions and meta-optimization.

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 test coverage gaps and generate tests to improve coverage. Use when improving test coverage, finding untested code, or writing missing tests.

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。

Post-engagement knowledge harvest AND harness retrospective - after a box/bugbounty/pentest/CTF is completed, first diff how the engagement was EXECUTED against the skills/hooks that governed it (what discipline was skipped) and improve the harness, then sweep the whole engagement for GENERIC reusable knowledge NOT already in wiki/ and land it via the leak-gated stage->promote pipeline. Use at close-out or when asked to "extract learnings", "what did we learn", "harvest lessons into wiki", "distill this engagement", "post-mortem into the wiki", "what did we do wrong", "improve the harness from this box".

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。

Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

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。

Restructure and improve Isabelle or Coq proofs to enhance readability, modularity, and maintainability without changing semantics. Use when proofs are long and monolithic, have repeated patterns, use unclear naming, lack documentation, or when the user asks to refactor, clean up, improve, or reorganize their formal proofs.

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。

Analyzes and optimizes code for better performance, memory usage, and efficiency. Use when code is slow, memory-intensive, or inefficient. Supports Python and Java optimization including execution speed improvements, memory reduction, database query optimization, and I/O efficiency. Provides before/after examples with detailed explanations of why optimizations work, complexity analysis, and measurable performance improvements.

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。