2,137 件 ・ 関連度順
概要と使いどころ
Use for any code, documentation, config, dependency, test, review, or maintenance task in the Nauthilus repository that must follow AGENTS.md, POLICY.md, focused reproducer-first debugging, strict DRY/OOP boundaries, English comments, GOEXPERIMENT=runtimesecret test discipline, Makefile-driven validation, prompt-sync checks, and dirty-tree preservation.
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 trail register: timestamp, user, module, record, action, field changed, old and new value, and the reason for the change. Use for change history and control evidence.
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。
Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.
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。
Serena MCP for project memory and code navigation. Use when managing Serena memories, navigating symbols, performing intelligent refactoring, or maintaining context/continuity across AI agent sessions.
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 and removes infostealer malware (credential stealers, data exfiltrators) via full-system file search, cryptographic hashing, and public threat-intelligence cross-checks (VirusTotal, MalwareBazaar). Primary method is always custom hash-based detection. Windows Defender (or any platform-native AV) is allowed **only when necessary** (e.g. inconclusive hashes or deep remediation) and **must never be the default option**. The agent must exhaust the custom workflow first. Works on Windows/macOS/Linux.
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。
Python research assistant with Context7 MCP. Use for Python library research, evaluating packages, enforcing strict Python coding standards, or fetching up-to-date library docs via Context7.
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。
Scope the real change surface before editing. Use when planning a feature, bugfix, refactor, or review and you need a concrete map of likely touch points, dependencies, tests, and nearby risks.
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。
Document Automator IA — Expert en automatisation documentaire (PDF generation, contract templates, e-signatures, DocuSign, Notion 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。
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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 and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
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。
Updates tdmcp docs and roadmap for newly shipped or newly merged capabilities. Use when asked to update docs, update the roadmap, reconcile release docs, document new features, sync docs with CHANGELOG/package release, refresh cookbook examples after a feature wave, re-run/continue/fix a docs-roadmap pass, or check whether docs/ROADMAP.md is current. Runs a sub-agent workflow: release audit -> roadmap/docs edit + cookbook sync -> QA.
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。
Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-review.
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。
Hostile self-review of recently written AI workflow code that then applies fixes (agents, tools, chat context, summarization, tokens, attachments). Use after generating AI systems code, or when asked to self-review and harden it. Not for PR peer review (code-review) or no-edit devil's-advocate attacks (adversarial-challenge). Prefer: adversarial-challenge → decide → this skill.
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。
checklist step of mspec workflow — produce checklist.md via subagent
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。
research step of mspec workflow — investigate via subagent and produce research.md
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。
self-review step of mspec workflow — sanity-check all artifacts via subagent
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: ticket lifecycle, state transitions, ready for QA, changes requested, QA passed, role-based workflow policy, Developer to QA handoff, or relay routing across delivery agents.
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 immediately after RBR confirms a root cause and a fix is scoped, before considering the finding complete. Checks whether the confirmed defect is one instance of a structurally identical pattern elsewhere in the same file family, workflow, or business-domain area, and folds in or explicitly defers every other instance found. Mandatory for Architect and CAO — not an optional lens the agent judges when to apply.
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: implement a scoped ticket, fix a bug, add tests, prepare a PR-ready code change, or reuse a standard builder workflow across software engineer agents.
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。
Workflow-state classification vocabulary for inter-team relay. Maps inbound signals from the remote agent to a routing decision. Intentionally narrow — states and destinations 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。
Orchestrates design workflows by routing work through brainstorming, multi-agent review, and execution readiness in the correct order. Prevents premature implementation, skipped validation, and unreviewed high-risk designs.
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。
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
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 and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
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。
Generate 3D models, textures, images, rig characters, and animate them using the Meshy AI API. Handles API key detection, setup, and all generation workflows via direct HTTP calls. Use when the user asks to create 3D models, convert text/images to 3D, texture models, rig or animate characters, or interact with the Meshy 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。