Uses Cowork-style multi-step analysis to process deal room documents -- contracts, financials, org charts. Outputs risk assessment, term comparison, key findings, and negotiation 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。
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概要と使いどころ
Uses Cowork-style multi-step analysis to process deal room documents -- contracts, financials, org charts. Outputs risk assessment, term comparison, key findings, and negotiation 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。
Generates a comprehensive client health overview across all accounts. Reads CRM data, support tickets, usage metrics, billing, and engagement logs. Calculates health scores, trend direction, and RAG status per client. Outputs a sorted risk report with recommended actions.
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。
Generates full consulting proposals from a brief. Input client name, problem description, and rough scope. Outputs proposal.md with executive summary, problem statement, proposed approach, timeline, team, pricing tiers, and terms. Researches client company for personalization. Multiple pricing models. Professional formatting matching consulting standards.
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。
Generates terminal recordings using VHS tape scripts and produces GIF outputs. Use when creating demo GIFs or documenting CLI workflows for tutorials.
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 ColabFold for protein structure prediction workflows: validate FASTA/CSV/A3M inputs, generate MSAs, plan batch predictions, inspect outputs, and troubleshoot optional AlphaFold, MMseqs2, JAX, GPU, and OpenMM dependencies.
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 ColBERT/colbert-ai for late-interaction retrieval: prepare data, inspect configs, train/fine-tune, index collections, search rankings, update indexes, serve search, evaluate MS MARCO/LoTTE outputs, or reason about Baleen multi-hop retrieval.
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 this skill for AlphaFold 3 input preparation, prediction command planning, output interpretation, and Python API inspection. Covers the local AlphaFold 3 inference package, its JSON dialect, run_alphafold workflow, outputs, troubleshooting, and safe helper scripts.
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。
External recon and OSINT pipeline - subdomain enum, live host discovery, URL crawl, JS analysis, nuclei scan. Outputs to Attack-surface.md and scope/. Queries wiki before each phase. Use when starting recon on any target.
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 diff for what Honey would cut — over-engineering (speculative generality, hand-rolled stdlib, single-caller abstractions) and over-verbosity (dead code, narration, redundant comments). Outputs a terse delete-list, one line per finding, with the line count each cut saves. Use when asked to review, trim, or de-bloat a change, or before opening a PR. Quality lever only — it finds waste, not correctness bugs.
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。
Create, generate, write, or scaffold Terraform .tf HCL — resources, modules, providers, variables, outputs.
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。
Assessing privacy risks in large language model outputs including training data memorisation, PII leakage in generated text, prompt injection leading to data extraction, and hallucinated personal data. Covers output filtering, guardrails, and monitoring. Keywords: LLM privacy, output risk, memorisation, PII leakage, prompt injection, hallucinated PII.
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。
Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset.
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。
This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.
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。
Blender compositor workflows for beauty stacks, render passes, color grade, glare, and delivery outputs via MCP.
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 scanning code for security vulnerabilities. Use when user says "scan security", "kiểm tra bảo mật", "security audit", "review security", or invokes `/vbs-scan-security`. For large scans (>20 main-language files OR >30 total OR >14 days) processes chunks sequentially. Outputs bilingual reports (vi/en). Optional `--auto-fix` (agentic patch + verify loop) and `--sca` (live CVE lookup via OSV.dev).
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 scanning code for security vulnerabilities. Use when user says "scan security", "kiểm tra bảo mật", "security audit", "review security", or invokes `/vbs-scan-security`. Auto-delegates to sub-agents for large scans (>20 main-language files OR >30 total OR >14 days). Outputs bilingual reports (vi/en). Optional `--auto-fix` (agentic patch + verify loop) and `--sca` (live CVE lookup via OSV.dev).
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 interactive HTML presentations with neobrutalism styling, ASCII art decorations, and Agency brand colors. Outputs HTML (interactive with navigation), PNG (individual slides via Playwright), and PDF. References brand-agency skill for colors and typography. Use when creating presentations, slide decks, pitch materials, or visual summaries.
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。
Define go-to-market strategy including launch plan, messaging, channels, and timing during PRD v0.9 Go-to-Market. Triggers on requests to plan launch, define GTM strategy, or when user asks "how do we launch?", "go-to-market", "launch plan", "marketing strategy", "messaging", "launch channels", "GTM". Outputs GTM- entries with launch plan components.
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。
Write idiomatic DSPy 3.2.x programs — typed Signatures, dspy.Module subclasses, Predict/ChainOfThought/ReAct/ProgramOfThought, and save/load. Use this when starting any new DSPy project or when fixing non-idiomatic DSPy code (hard-coded prompts, ad-hoc string templates, untyped outputs, non-serializable classes).
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 a PR description following the project's pull_request_template.md. Analyzes all commits on the current branch vs main, summarizes changes, and outputs a ready-to-paste PR body. Invoke with /pr-summary.
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。
Investigate a GitHub issue and produce a structured implementation plan. Fetches issue details, explores the codebase, identifies affected layers (UI, BLoC, Repository, Client), and outputs a step-by-step plan with files to modify, testing strategy, and risk assessment. Works for bugs, features, and tasks. Invoke with /plan.
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。
Reverse weekly review for turning inbox noise, daily plans, diaries, calendars, annual plans, and long-range life plans into one happiness-and-peace-centered weekly plan. Use when the user asks for 週檢視, 反向週計劃, 8 Big Rocks, Inbox Zero weekly review, 幸福寧靜週, or wants to synthesize Todoist/inbox notes, daily diaries, calendars, yearly plans, and life plans into iMandalArt/FIRE/JSON outputs.
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。
Convert FIRE analysis cards, Chinese knowledge notes, or project-note JSON into validated EPUB books with directory cards, chapter cards, keyword index cards, backlinks, and GitHub-shareable ebook assets. Use when Codex needs to teach or automate the path from `fire-analysis-card` outputs to `project-note-json-to-epub` style EPUB files, including sample JSON manuscripts and attached `.epub` deliverables.
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。
Builds traceability matrices connecting requirements to design documents to source code implementation, tracking the complete development lifecycle. Use when you need to verify implementation completeness, ensure all requirements are implemented in code, generate compliance documentation, audit requirement coverage, identify orphaned code, or create traceability reports for stakeholders. Supports parsing requirements from Markdown, Word, and PDFs; extracting design from architecture docs and API specs; and scanning source code for implementations. Outputs to Markdown tables, Excel/CSV, and HTML visualizations.
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。