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概要と使いどころ
Design a viable business model for a one-person company using Lean Canvas and a simplified Business Model Canvas. Use when Codex needs to explain the business-model concepts when needed, verify niche and value-proposition prerequisites, ask one question at a time, present multiple model choices, and write user-confirmed outputs into `opc-doc/`.
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。
Find and position a viable niche market for a one-person company by combining market mapping and customer segmentation. Use when Codex needs to explain niche concepts when needed, check founder-resource prerequisites, ask one question at a time, generate multiple niche options, and write user-confirmed positioning outputs into `opc-doc/`.
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 any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
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 any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use 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。
On-demand journal peer review simulation expert — supports 7 research paradigms (experimental/computational/empirical_survey/interpretive/mixed_methods/systematic_review/interdisciplinary) with 6-step review workflow, outputting targeted revision suggestions based on journal-specific review 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。
International journal matcher — performs L3 6-dimensional matching for SCI/SSCI/EI/Scopus journals, computes conditional acceptance probability with review cycle estimation, applies 4-layer weighted ranking, and outputs tiered submission strategy including CAS warning screening and Chinese scholar friendliness 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。
Chinese journal matcher — performs L3 6-dimensional matching (keywords, cited direction, trend, solicitation, institution, cross-discipline), calculates conditional acceptance probability with review cycle estimation, and outputs tiered submission strategy (aspiration-stable-safety) using 4-layer weighted ranking.
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。
Efficiently extract and convert the contents of any local file—such as PDF, DOCX, DOC, ODT, RTF, XLSX, XLS, or HTML—into clean, well-formatted markdown saved to disk. Use this skill whenever the user requests to parse, read, or extract information from a file on their computer, including phrases like “parse this PDF”, “convert this document”, “read this file”, “extract text from”, or when a local file path (not a URL) is provided. This skill offers advanced options like generating AI-powered summaries and answering questions based on the file's content. Prefer this tool over `scrape` when handling local files to deliver precise, structured outputs for downstream tasks.
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 to create, edit, rebuild, or refine editable diagrams in `.drawio` / diagrams.net format, especially for academic figures such as system architecture diagrams, technical roadmaps, workflow diagrams, method pipelines, module relationship diagrams, and experiment flowcharts. Use this skill when the user wants publication-ready outputs with both an editable source file and a PNG export, or when an existing figure image needs to be rebuilt into a clean editable academic-style diagram.
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 the strict-mode sprint contract review after Phase 2c. Spawns a fresh vcsdd-adversary instance to review `contracts/sprint-N.md` and writes a PASS/FAIL verdict under `reviews/contracts/sprint-N/output/`.
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 an end-to-end GEO visibility measurement through a real AI interface, persist the captures, and return a portable JSON run artifact plus optional PDF/dashboard outputs. Use automatically on an explicit request to measure a brand's AI-search visibility, and as a composable data-collection step inside another agent workflow; the user should not have to launch the pipeline or dashboard manually.
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 the hyalo CLI instead of read/edit/grep/write when working with markdown (.md) files that have YAML frontmatter. This skill MUST be consulted whenever pi is working with markdown documentation directories, knowledgebases, wikis, notes, Obsidian-compatible collections, Zettelkasten systems, iteration plans, or any collection of .md files with frontmatter. Trigger this skill when: searching or filtering markdown files by content, tags, or properties; reading or modifying YAML frontmatter; managing tags or metadata across documents; toggling task checkboxes in markdown; getting an overview of a documentation directory; querying document properties or status fields; bulk-updating metadata across many markdown files; or when you find yourself repeatedly using read/edit/grep/write on .md files. Even if the user does not mention "hyalo" by name, use this skill whenever the task involves structured markdown documents with frontmatter. For pi sessions, ALWAYS use `--format text` for compact, LLM-friendly output.
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。
Peer review checklist and quality standards for intelligence products, plus schema validation for graded evidence items and claim tables from /quality-of-information-check and /claim-extraction. Rejects outputs that break the evidence schema or the grading caps. Loaded by the quality-reviewer agent.
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 as the default entry point for any CTI request that doesn't name a specific skill. Activates when a user asks to investigate an indicator, profile a threat actor, write an assessment, enrich IOCs, or build detection rules, and when a user asks where a report or article comes from, how reliable it is, to grade a source, check a report, or split a report into claims, or pastes a bare article URL. Routes to the right investigation, provenance, grading or analysis skill, then auto-applies rigor skills (source rating, TLP, confidence, likelihood) on the output.
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 report or article needs to be split into individual claims before it is graded, cited or used as evidence — the user asks "what does this report actually claim?", "split this into claims", "separate the facts from the judgements", or another skill needs a claim list. Turns one document into five to twelve atomic claims, each typed (observation, attribution, assessment, actor claim, victim disclosure) and anchored to the verbatim sentence it rests on, so every extraction can be checked against the source. Preserves the source's own hedging. Does not grade. Invoked by /quality-of-information-check; its output feeds /ach, /key-assumptions-check, /intelligence-writing, /writing-assessments and /threat-actor-profiling.
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 and edit presentation slide decks (`.pptx`) with PptxGenJS, bundled layout helpers, and render/validation utilities. Use when tasks involve building a new PowerPoint deck, recreating slides from screenshots/PDFs/reference decks, modifying slide content while preserving editable output, adding charts/diagrams/visuals, or diagnosing layout issues such as overflow, overlaps, and font substitution.
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 about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
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。
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
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。
Advanced Agentic Coding framework providing mission briefs, guardrails, and integration hints for complex tasks. This skill ensures high-quality output through disciplined automation and systematic workflows.
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。
Design reliable, safe, and trustworthy agent systems that fail gracefully and operate within bounds. Use when building guardrails, handling edge cases, preventing harmful outputs, monitoring for failures, implementing safety constraints, or designing error recovery. Covers failure modes, constraint systems, oversight mechanisms, and safety validation.
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 Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool 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。
Terminal session manager for AI coding agents. Use when user mentions "agent-deck", "session", "sub-agent", "MCP attach", or needs to (1) create/start/stop/restart/fork sessions, (2) attach/detach MCPs, (3) manage groups/profiles, (4) get session output, (5) configure agent-deck, (6) troubleshoot issues, or (7) launch sub-agents. Covers CLI commands, TUI shortcuts, config.toml options, and automation.
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。
Master coordinator for the founder. Filters noise, owns cross-functional processes, enforces consistency, routes decisions, and positions outputs for impact so the founder can think clearly. Doesn't own any function owns the space between all of 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。
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
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。