「review」の検索結果

Pick among candidate outputs (code, configs, plans) by running them on diverse inputs and clustering by behavioural fingerprint, rather than by textual aggregation or log-probability. Activates when an executor returns multiple plausible candidates that need disambiguation, when output-majority voting would be the default choice, or when reviewing generated code that has not yet been validated. The 2026 evidence (Semantic Voting, arxiv 2605.08680v1) is that any execution-based selector dominates output-majority voting by 19-52pp; sketch-generated inputs beat random fuzz by 11.3pp. Triggers: "pick the best candidate", "majority vote on code", "select from N samples", "validate the generated output", "behavioural verification".

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 a skill by running a paired probe — the same task once with the skill loaded and once without — segment both traces into goal-directed phases, align phases, and emit a SIP report (surface anchoring, template copy, excess planning, task recovery, off-task artifact). Use whenever a skill is created, modified, or proposed for retirement. Pass-rate is BLIND to most skill effects: CTA (arxiv 2605.11946v1) shows a single skill can produce 522 measurable behavioural changes across 49 tasks while pass-rate moves only +0.3%. Triggers: "audit this skill", "is this skill helping", "retire skill", "before shipping skill", "behavioural impact of skill X", or any skill review event.

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 authoring or reviewing a SKILL.md or agent .md and you need to detect and fix the four most common frontmatter defects — echoed or truncated triggers, tools written as a YAML array instead of a comma-separated string, a description outside the 1-1024 character bound, and a missing "Use when..." clause.

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 at write time to vector/embedding memory — Grove content-addressed insertion, chroma/pgvector upserts, memory-consolidation promoting session traces to MEMORY.md, or embedding externally-ingested content. Scores each candidate record against a fixed panel of sentinel queries and quarantines any record that would become the nearest neighbor of too many unrelated queries — a hub — whether from adversarial poisoning or accidental over-generality. This is the memory-record-side sibling of skill-injection-guardian (file-side) and the write-side complement of memory-use-warrant (read-side). Quarantine, never silently drop; a human reviews. Backed by the admission-time hubness gate (arxiv 2606.19692v1). Triggers on inserting into vector memory, consolidating memory, and embedding stranger 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。

Manages skill-creator integration with GSD workflows including skill loading, session observation, bounded learning guardrails, and pattern detection. Use this skill whenever: executing any GSD phase (to ensure relevant skills are loaded first), starting or resuming a work session (to check for pending suggestions), the user asks about skills, patterns, or skill-creator status, performing code changes that might represent repeating patterns, the user corrects Claude's output (highest-signal observation), or when skill refinement, creation, or suggestion review is discussed. Critical for maintaining the adaptive learning layer.

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。

Deploy and operate apps on Prisma Compute with the Prisma 8 CLI. Use whenever the user mentions Prisma Compute, deploying or hosting a Prisma app, `prisma deploy`, `prisma dev module.ts`, Prisma Composer apps (`module.ts`, `compute()`, the `composer` section of `prisma.config.ts`), preview stages, deploy on push (`prisma git connect`, `prisma/cloud-deploy-action`), `prisma service` logs, versions, rollback, or custom domains, `project env`, `PRISMA_SERVICE_TOKEN`, regions, 504s, sleeping instances, or `waitUntil`; also when a project still uses the removed `@prisma/cli app deploy`, `prisma.compute.ts`, `defineComputeConfig`, `compute:deploy`, or `build logs` surface.

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。

Apply Docker and Docker Compose best practices for containerising services. Use when writing or reviewing Dockerfiles and compose configs.

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 STRIDE threat modeling for each component and trust boundary and produce a threat register. Use when reviewing a feature for security.

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。

Invoke the rubber duck reviewer for a second opinion. Use after planning, after complex multi-file implementations, or after writing tests. Produces a focused CRITICAL/WARN/INFO list and a APPROVE/REQUEST_CHANGES verdict.

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。

Apply Kubernetes and Kustomize patterns for deployments, services, and overlays. Use when writing or reviewing k8s manifests.

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。

用户在帖子没爆时感到焦虑、怀疑自己是否适合做 X,或连发一批内容后评估整体表现、设定增长目标时使用。核心认知:公共平台传播是长尾分布(3861 帖均值 188/中位数 42),一条没爆是预期的中位数而非失败;目标不是让每条都爆,而是系统性提高进前 10% 的概率。Trigger signals: "我连发20条只2条过百该放弃吗""怎么让每条都爆""发了这么多没水花""一条没爆就怀疑人生""是不是我不适合做X" / "only 2 out of 20 hit 100, should I quit" "how to make every post go viral" "my posts get no engagement"。不适用于:单条内容生产(用 x-short-content-craft)、数据复盘操作(用 x-data-review)、理解推荐算法机制(用 x-foryou-algorithm)。

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 a MaaFramework/Maa-series project's Git history to learn how Pipeline JSON, interface options, Python AgentServer CustomAction code, and related data tables evolved. Use when asked to review a Maa project from initial commit through a target commit, map `action: Custom` pipeline nodes to `@AgentServer.custom_action(...)` implementations, find pipeline/custom/option patterns or breakages, and produce a report plus skill-improvement recommendations.

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 runtime UI options (select/checkbox/switch/input) to MaaFramework option surfaces such as `assets/interface.json` or `assets/resource/tasks/**/*.json`. Use when adding a user-facing toggle, selector, checkbox, or input; wiring options to `pipeline_override`; aligning option paths with Python `context.get_node_data()` or CustomAction params; or reviewing option behavior across Pipeline JSON and Python.

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。

Apply modern web development best practices for security, compatibility, and code quality. Use when the task involves `apply best practices`, `security audit`, `modernize code`, `code quality review`, or `check for 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。

Review a design artifact (spec, plan, PR packet) with fresh, memoryless subagents. Invoke when the user asks — "goldfish this", "fresh eyes", "tear this apart" — or after suggesting it for a spec that has grown load-bearing and the user agrees.

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 code changes for security vulnerabilities using LLM reasoning and threat model patterns. Use for PR reviews, pre-commit checks, or branch comparisons.

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。

Detects timing side-channel vulnerabilities in cryptographic code. Use when implementing or reviewing crypto code, encountering division on secrets, secret-dependent branches, or constant-time programming questions in C, C++, Go, Rust, Swift, Java, Kotlin, C#, PHP, JavaScript, TypeScript, Python, or Ruby.

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。

Track Claude's best and worst questions in DuckDB. Use when Claude asks a notably good or bad question, or to review question quality. Triggers: leaderboard, bad question, good question, question quality.

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。

Interactive assistant for intercepting, debugging, analyzing and reviewing Claude Code API requests using mitmproxy. Guides setup, certificate configuration, and active traffic inspection via web or CLI interface. Supports learning Claude Code internals, debugging issues, and optimizing API usage.

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。

Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.

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。

Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.

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。

Search academic papers across arXiv, PubMed, Semantic Scholar, bioRxiv, medRxiv, Google Scholar, and more. Get BibTeX citations, download PDFs, analyze citation networks. Use for literature reviews, finding papers, and academic research.

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。

字コンテやネームの没入感、無言コマ、感情の間、情報密度をレビューするときに使う。

日本語漫画のネームや文字入れについて、コマ・フキダシの読む順と文字配置を相談・レビューするときに使う。