2,362 件 ・ 関連度順
概要と使いどころ
Prepare a many-file, single-turn transform (translate, rewrite, extract) as a plan and submit it to the asynchronous, half-price DashScope Batch API; results are delivered as new files hours later. Invoke explicitly with /batch-api.
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 indexed codebases via graph database (neug) and vector index (zvec). Covers call graphs, dependencies, dead code, hotspots, module coupling, architecture reports, semantic search, impact analysis, bug root cause from GitHub issues, class diagrams (UML), and PR review (risk scoring, conflict detection, auto-merge candidates, labeling). Also covers creating, inspecting, and repairing a CodeScope index. Use for: code structure, who calls what, why something changed, similar functions, module boundaries, bug tracing, class relationships, PR risk/conflicts, or any question benefiting from a code knowledge graph. Applies when a `.codegraph` index exists in the workspace, or when the user wants to create one.
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。
/cs:iso27001-audit-prep <scope> — ISO 27001 ISMS audit readiness 6-question forcing interrogation. Use before annual Clause 9.2 internal audit, surveillance audit prep, or stage 1 certification readiness.
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。
/cs:soc2-audit-prep <scope> — SOC 2 Type II readiness 6-question forcing interrogation. Observation-period focused. Use before Type II observation begins, mid-period checkpoint, or pre-field-test month-10 readiness.
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。
/cs:gdpr-audit-prep <scope> — GDPR audit 6-question Article-cited forcing interrogation. Use before annual internal GDPR review, post-breach internal audit, DPA investigation readiness, or acquisition due diligence.
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。
/cs:fda-qsr-audit-prep <scope> — FDA 21 CFR 820 (QSR / QMSR) audit 6-question forcing interrogation. Post-Feb 2026 substantially harmonized with ISO 13485. Use before annual internal QSR audit, pre-FDA-inspection readiness, or Form 483 response.
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。
Compliance OS — meta-orchestrator that lets compliance teams CONFIGURE which frameworks apply, COMPUTE cross-framework control overlap, SIMULATE internal audits, and CONSOLIDATE evidence across multiple frameworks. Four decisions: (1) Given a company profile, which of the 12 supported frameworks apply (ISO 27001/13485/42001/14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR, NIST CSF 2.0, NIS2, HIPAA)? (2) Across selected frameworks, which controls overlap and how much evidence reuses? (3) For a given framework + scope, what does a realistic mock audit produce — drawing from the 205-scenario library? (4) Across selected frameworks, what's the unified evidence checklist with reuse map? Use when standing up a multi-framework program, planning the annual audit calendar, or preparing for certification stage 1. Does NOT replace per-framework skills (it orchestrates them).
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。
/cs:iso13485-audit-prep <scope> — ISO 13485 QMS audit 6-question forcing interrogation. Design controls + CAPA + post-market focused. Use before Clause 8.2.4 internal audit, MDR / FDA QSR alignment review, or product-launch DHF closure audit.
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。
/cs:aims-audit <scope> — ISO/IEC 42001 AIMS internal-audit 6-question forcing interrogation. Use before certification stage 1, before annual internal audit cycles, or when onboarding a new AI system into an existing AIMS.
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。
Phase 1 of building a Claude Managed Agent — interview the founder about the one job the agent should do, then produce a build sheet (CMA primitives table + v1/v2 deferrals + eval plan) WITHOUT needing their API key yet. Use when the user says "help me scope an agent", "I have an idea for an agent", "what should this agent be", or when the orchestrator routes phase=interview. Drives the six intake slots (job, trigger, inputs, actions, definition-of-done, recurrence) via AskUserQuestion, maps them to primitives with interview_planner.py, assembles build-sheet.json with build_sheet_builder.py, and validates limits with primitives_validator.py. Connectors are mockable in v0 (schema-true custom tools); real MCP servers become v1 deferrals. Distinct from stage-launch (which turns the sheet into payloads).
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。
Choose scoped cmux verification, add behavioral tests, and validate Swift test targets and wiring. Use when adding tests or deciding what local/CI evidence a change needs.
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 user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details 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。
Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.
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 adding or moving code across shared/frontend/backend modules in packages/kilo-jetbrains/ — split-mode RPC contracts, serialization classloader pitfall, threading/EDT annotations, services and coroutine scopes, EDT test rules, dependency bundling, and the CLI server protocol.
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 creating, triaging, or commenting on GitHub issues for the Kilo VS Code extension or JetBrains plugin via `gh`. Covers issue templates, project board assignment, title conventions, and required `gh` scopes.
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。
Prioritize a backlog of feature ideas based on impact, effort, risk, and strategic alignment with top 5 recommendations. Use when prioritizing a feature backlog, making scope decisions, or ranking product ideas.
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 a sprint with capacity estimation, story selection, dependency mapping, and risk identification. Use when preparing for sprint planning, estimating team capacity, selecting stories, or balancing sprint scope against velocity.
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 image generation with OpenAI GPT Image 2.5, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
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。
QA test plan for a sprint — classifies stories by Logic/Integration/Visual/UI, covers automated tests, manual cases, smoke scope.
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。
Explore vague or ambitious ideas into a right-sized requirements-only unified plan. Use when the user wants to brainstorm or scope what to build. Not for executing already-specified work. Use ce-pov for a verdict on adopting a named external technology.
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。
Hands-off, diff-scoped browser QA of the active branch: maps user flows, drives a real browser, autonomously fixes small breakages with regression tests and commits, judges experience against product personas, and writes a durable dogfood report. Manual invocation only.
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。
Populate a project's shared OpenSEO context — site scope, goals, positioning, competitors, key pages, and preferences — plus MCP checks and Search Console intake.
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 reviewing changed or staged code, a branch, or a PR in the Handsontable monorepo across architecture, code quality, performance, accessibility, and tests. Covers SOLID / Law of Demeter / plugin decoupling / breaking-changes policy, custom ESLint rules / JSDoc / naming / cognitive complexity, large-array and render-batching performance, WCAG 2.1 AA + keyboard navigation, and the tests a change ships (a named exercising test per new path, scoped mutation, a ticket on every weakened assertion). Trigger when asked to review changes, check a diff against Handsontable conventions, assess architectural correctness, spot performance regressions, verify accessibility, or judge whether a change's tests prove it, and as the design lens before or while implementing any core change.
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。
Queries and retrieves active security findings, external exposures, toxic combinations, vulnerabilities, threats, and sensitive data risks from Security Command Center on Google Cloud. Use when retrieving details for a security finding by its name, validating finding scope (e.g., verifying findingClass is TOXIC_COMBINATION, VULNERABILITY, EXTERNAL_EXPOSURE, or THREAT), or fetching finding details for triage. Don't use to draft remediations, apply patches, or execute 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。