Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
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。
A battle-tested methodology for running ANY business in real-time simulation as an autonomous operator agent. Pick a venture — a shop, restaurant, SaaS product, boutique, fund, agency, nonprofit, or creator business — and the agent operates it day by day: calendar discipline, real-world grounding, source-of-truth locking, delegated authority, an operational tracker, a named persona team, finance honesty, risk/cadence management, and self-correction. Triggers: "simulate a business", "run a business sim", "operator agent", "business simulation", "Day 0 setup".
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Run a business that doesn't exist yet — in real time, as its operator. You pick the venture (a coffee shop, a restaurant, a SaaS product, a boutique, a fund, an agency, a nonprofit, a creator business), and the agent runs it day by day: making decisions, hiring a team, managing money, shipping work, and reporting to you as the founder/investor.
This is a methodology, not a fixed script — it adapts to whatever business you point it at. Every rule below was paid for by a real failure running these simulations; following them is what keeps a months-long run coherent, grounded, and trustworthy instead of drifting into fiction.
Do these once, before any operating happens:
Then operate. Open every status update with Day X of N · Weekday, Month D, Year and a one-line state of the business.
Real days elapse 1:1 with sim days, and day-number drift is the most persistent bug.
sim_day = (today − day_one) + 1. NEVER re-derive the anchor from a milestone.--check to catch corruption.#!/usr/bin/env python3
import sys
from datetime import date, timedelta
DAY_ONE = date(2026, 1, 5) # the calendar date you call sim Day 1
MILESTONES = {
"Soft Launch": date(2026, 4, 1),
"Launch Day": date(2026, 4, 15),
}
CHECKPOINTS = { # user-confirmed: date -> expected day
date(2026, 2, 3): 30,
date(2026, 3, 6): 61,
}
def sim_day(d): return (d - DAY_ONE).days + 1
def date_for(n): return DAY_ONE + timedelta(days=n - 1)
def main(argv):
if "--check" in argv:
ok = True
for d, exp in CHECKPOINTS.items():
got = sim_day(d)
print(f"[{'OK' if got==exp else 'FAIL'}] {d} -> Day {got} (expected {exp})")
ok &= got == exp
sys.exit(0 if ok else 1)
if "--day" in argv:
n = int(argv[argv.index("--day") + 1])
print(f"Day {n} = {date_for(n).strftime('%A, %B %d, %Y')}"); return
d = date.fromisoformat(argv[1]) if len(argv) > 1 else date.today()
print(f"Day {sim_day(d)} · {d.strftime('%A, %B %d, %Y')}")
for name, md in MILESTONES.items():
print(f" {(md - d).days} days to {name} ({md.strftime('%b %d')})")
if __name__ == "__main__":
main(sys.argv)
Fabricated addresses, vendors, and prices destroy trust and compound.
Replaced/Archived rather than deleting.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
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 when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
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。
Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
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, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
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。
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
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。
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security 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。