5,400 件 ・ 関連度順
概要と使いどころ
For authorized security review of code, auth, or APIs you control, model the attacker, map the attack surface, and report only findings with a reproducible exploit path and verified mitigation.
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。
dontbesilent AI 写作特征识别。扫描文案中的 AI 生成痕迹，输出检测报告。默认只诊断不改。 触发方式：/dbs-ai-check、/AI检测、「帮我看看有没有 AI 味」「检测一下 AI 特征」 AI writing fingerprint detection. Scans copy for AI-generated patterns and outputs a diagnostic report. Diagnosis only by default. Trigger: /dbs-ai-check, "check for AI writing", "does this sound like AI"
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 Jev-powered decision and release gate after an office assistant generates a report, proposal, spreadsheet, document, or slide deck. Use for claim-to-evidence checks, narrow requirement decisions, risk triage, and human-review routing; do not use it to generate the deliverable or claim that Jev browsed or verified a 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。
AI DevKit · Enforce evidence-based completion claims — require fresh command output before reporting success. Use when completing any task, fixing a bug, finishing a phase, running tests, building, deploying, or making any "it works" claim.
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Use when the user types /hep-storm, mentions @Hephaestus storm, or asks to force-robustly drive a loop-worthy goal (apps, sites, agents, automations, debugging, multi-step research, data/report generation) to a verified finish. Stormbreaker routes the goal to real Agentlas specialists, materializes a dependency-ordered pipeline fabric, and runs a verifier-first loop that does not stall, run away, or claim false success. Trivial questions are answered directly, not stormed.
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 types /hep-storm or /agentlas-storm, says @Hephaestus storm <goal>, or asks to drive a goal to verified completion through a force-robust Stormbreaker loop. Stormbreaker routes the goal to real Agentlas specialists, materializes a dependency-ordered pipeline fabric, and runs each work packet as a verifier-first hardened loop that does not stall, run away, or claim false success. Use it for loop-worthy work — apps, sites, agents, automations, debugging, multi-step research, data/report generation. Trivial questions are answered directly, not stormed.
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 Codex feels slow or bloated, when local sessions/logs/worktrees/config have grown over time, or when a user wants safe maintenance for Codex Desktop/CLI state. Provides a read-only report by default, backs up before applying changes, archives instead of deleting, normalizes Windows extended paths, prunes dead config projects, rotates large logs, and moves stale worktrees.
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。
Run DeepSec against a Vercel project checkout from dev3000. Use for one-click DeepSec setup, project context bootstrapping, bounded first-pass processing, and report generation.
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。
Assess and migrate cross-cloud workloads to Azure with reports and code conversion. Supports Lambda→Functions, Beanstalk/Heroku/App Engine→App Service, Fargate/Kubernetes/Cloud Run/Spring Boot→Container Apps. WHEN: migrate Lambda to Functions, AWS to Azure, migrate Beanstalk, migrate Heroku, migrate App Engine, Cloud Run migration, Fargate to ACA, ECS/Kubernetes/GKE/EKS to Container Apps, Spring Boot to Container Apps, cross-cloud migration.
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 a product walkthrough, bug report video, Loom, or ScreenPal using Minutes transcription plus visual review. Use when the user wants a recorded demo or bug clip turned into a durable brief with transcript, key frames, issues, and next steps.
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。
Turn a user-owned coverage CSV and reviewed press-clip captures into an honest, source-linked earned-media dashboard and a motion-designed highlight reel (MP4) that scrolls each real article to the client's sentence and highlights it. Use for coverage reports, earned-media dashboards, campaign recaps, or coverage videos; requires local files and composes press-clip instead of scraping articles itself.
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。
Performs systematic root cause analysis to identify the true source of bugs, errors, and unexpected behavior through structured investigation phases — not just treating symptoms. Use when a user reports a bug, crash, error, or broken behavior and needs to debug, troubleshoot, or investigate why something is not working; especially for complex or intermittent issues across multiple components. Applies the Five Whys method, hypothesis-driven testing, stack trace analysis, git blame/log evidence gathering, and causal chain documentation to isolate and confirm root causes before applying any fix.
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。
Coordinates parallel investigation threads to simultaneously explore multiple hypotheses or root causes across different system areas. Use when debugging production incidents, slow API performance, multi-system integration failures, or complex bugs where the root cause is unclear and multiple plausible theories exist; when serial troubleshooting is too slow; or when multiple investigators can divide root-cause analysis work. Provides structured phases for problem decomposition, thread assignment, sync points with Continue/Pivot/Converge decisions, and final report synthesis.
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。
Full-sweep mode: runs a unified analysis across all quality dimensions — code decay, architecture, tech debt, and test quality — then applies fixes directly to the codebase. Safe changes are auto-applied; risky changes are confirmed before execution. Drawing on twelve classic engineering books. Triggers when: user wants to "fix everything", "sweep the codebase", "auto-fix all issues", "clean up the whole project", or asks for a single command that both diagnoses and remediates quality problems. Do NOT trigger for: read-only audits or health reports where the user only wants findings without code changes; single-dimension reviews (use the focused skill instead: brooks-review / brooks-audit / brooks-debt / brooks-test); server health checks, HTTP /health endpoints, Kubernetes probes, database health, or application uptime.
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, refresh, report, or probe an accessibility coverage matrix across criteria, surfaces, and evidence methods. Use when assessing coverage with the accessibility runtime harness and generated evidence bundle.
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Land the winning experiment from an evo run as a clean, mergeable change -- open a PR when the repo has a remote, otherwise merge into the working branch. Distills the best-scoring experiment down to the minimal diff that reproduces its behaviour, shaped for the qualities a maintainer merges on (scope discipline, test integrity, style adherence), then attaches an advisory mergeability report. Use when the user invokes /evo:ship, asks to land/merge/ship the best result, or wants to turn a finished optimization into a pull request.
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。
Gangtise (岗底斯投研) OpenAPI skill suite installer and diagnostic tool. One-click install 19 official skills (data, research, utility), configure accessKey/secretAccessKey, run health diagnostics. Trigger when user mentions Gangtise, 岗底斯, any gangtise-* skill, credential setup, or reports errors like 'token is invalid' / '接口地址错误'.
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。
Routes finance: Bigdata/RavenPack, US fundamentals/yfinance, A-share news/policy, sector Top N/公告, Gangtise/岗底斯 setup. Reads one bundled specialist. Pharma reporting and general argument review keep their own direct entries.
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。
Optimizes or restructures CLAUDE.md/AGENTS.md with progressive disclosure and zero information loss. Use when the user asks to optimize, audit, 精简/瘦身/重构, or split instruction files, asks for their best practices (最佳实践), sees Memory files taking a large share of /context, reports rules in instruction files being ignored, or a task starts moving instruction sections. Not for generic task drift unless instruction files are in scope; not for moving memory entries into docs (use claude-code-ops-router).
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。
Migrates Claude Code personal memory (the per-project memory/ directory) into tool-agnostic reference docs so other AI CLIs that auto-load AGENTS.md (Codex primarily) can read the same user profile and preferences. Use when the user says "migrate my memory", "my memory is locked to Claude Code", "make Codex/Cursor read my profile", or reports memory has grown bloated with content that should be shared across tools. Also use it to retire a project's auto memory entirely (turn it off, move everything into documents, archive the directory).
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。
Converts a PDF into one self-contained, readable HTML file that preserves images, tables, charts and reading order — optionally translating it into another language while keeping every figure. Uses structured extraction (PyMuPDF), font-size-driven layout, compressed base64-inlined images (a single portable file), and mandatory headless-Chrome visual verification. Use whenever someone wants to READ a PDF as a web page or clean document, turn a PDF into HTML, or translate a PDF into another language while keeping its images/tables/charts intact — e.g. "PDF 转 HTML", "把这个 PDF 转成中文网页版", "make this report readable", "translate this PDF but don't lose the charts", "I just want to read this PDF on my phone". Distinct from doc-to-markdown (plain Markdown text) and pdf-creator (Markdown→PDF) — this one produces a styled, image-faithful HTML reading experience.
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。
Creates formatted Excel reports with openpyxl, parses complex xlsm financial models with stdlib zipfile+xml when openpyxl fails, and controls Excel windows on macOS via AppleScript. Reconstructs images or scans of paper forms as editable XLSX files with printable layouts.
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。
Gated checklist to choose or review a library, framework, storage, data format, model, build-vs-buy or architecture. Run favorites-search before external research when installed. Compare candidates and trade-offs; select within authorization or return user-owned choices. Use for 用哪个 / 选什么框架 / 要不要自建 / A 还是 B / 这个方案行不行 and before committing to one. Research reports → deep-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。
Creates reusable, source-traced research reports and coordinates provider/mode lanes with original exports. Use for 深度研究, 调研报告, literature reviews, market or company research, and ChatGPT/Kimi/UniFuncs research routes. Technology choice uses tech-selection; competitor code uses competitors-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。