Back up / restore openInvest's local state — memory/ (holdings, strategy, user profile, committee records, dream logs) + db/ (trade ledger, job run history, market-data cache) + .env (SMTP/API credentials) + userprofile.json. All of this data is .gitignore'd with no historical versions in git, so a single accidental overwrite (e.g. slipping and running some one-off migration/init script) means real data loss — no git revert available. Proactive trigger scenarios — "backup invest data / 备份一下 openInvest 的数据", "my holdings/strategy look wiped / 我的持仓/策略好像被清空了", "invest data is lost / invest 数据丢了", "restore invest backup / 恢复一下 invest 的备份", before any reinstall/migration of the openInvest deployment on this machine, or right before running an unfamiliar migration/init script (back up first, then act).
EnglishFirst-time openInvest installation and onboarding. ONLY use when user explicitly says "set up invest" / "init invest" / "帮我初始化 invest", OR when invest skill's doctor returns status="needssetup". NOT for daily usage — once onboarding is done, the invest skill takes over (portfolio viewing, committee analysis, buy/sell tracking). Wraps run.sh init --from-stdin with the canonical 5-question flow.
EnglishMaintain openInvest's docs (docs/wiki chapters + docs/wiki/adr) under Google's Open Knowledge Format (OKF). Two jobs. (1) Teach agents to maintain docs the OKF way — every doc carries a small YAML frontmatter block as the single source of truth (type, title, tags, intent, schemasource, documents); schema details link to the authoritative code instead of being copied into prose; no more hand-maintained thousand-line markdown. (2) Look docs up fast — grep the literal term FIRST; only when grep is ambiguous (hits scattered across files / synonym mismatch / zero hits) run finddocs.py to rank the owning doc by frontmatter intent, or resolve a doc's schemasource to the real code. Trigger phrases — "which doc covers X", "find the schema for PortfolioResponse", "where is GET /api/holdings documented", "docs for verdict.riskprofile", "add OKF frontmatter to this doc", "lint the wiki", "scaffold a new ADR/chapter". Run: scripts/run.sh find|schema|index|lint|new (or python3 scripts/finddocs.py --repo ...).
English
AGENT SKILLS ATLASIncludes Invest Backup, Invest Setup, and Okf Frontmatter.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLISupported by the Atlas install prompt. Skill-specific requirements vary.
Pack stats
What’s included
Invest Backup
Back up / restore openInvest's local state — memory/ (holdings, strategy, user profile, committee records, dream logs) + db/ (trade ledger, job run history, market-data cache) + .env (SMTP/API credentials) + userprofile.json. All of this data is .gitignore'd with no historical versions in git, so a single accidental overwrite (e.g. slipping and running some one-off migration/init script) means real data loss — no git revert available. Proactive trigger scenarios — "backup invest data / 备份一下 openInvest 的数据", "my holdings/strategy look wiped / 我的持仓/策略好像被清空了", "invest data is lost / invest 数据丢了", "restore invest backup / 恢复一下 invest 的备份", before any reinstall/migration of the openInvest deployment on this machine, or right before running an unfamiliar migration/init script (back up first, then act).
Invest Setup
First-time openInvest installation and onboarding. ONLY use when user explicitly says "set up invest" / "init invest" / "帮我初始化 invest", OR when invest skill's doctor returns status="needssetup". NOT for daily usage — once onboarding is done, the invest skill takes over (portfolio viewing, committee analysis, buy/sell tracking). Wraps run.sh init --from-stdin with the canonical 5-question flow.
Okf Frontmatter
Maintain openInvest's docs (docs/wiki chapters + docs/wiki/adr) under Google's Open Knowledge Format (OKF). Two jobs. (1) Teach agents to maintain docs the OKF way — every doc carries a small YAML frontmatter block as the single source of truth (type, title, tags, intent, schemasource, documents); schema details link to the authoritative code instead of being copied into prose; no more hand-maintained thousand-line markdown. (2) Look docs up fast — grep the literal term FIRST; only when grep is ambiguous (hits scattered across files / synonym mismatch / zero hits) run finddocs.py to rank the owning doc by frontmatter intent, or resolve a doc's schemasource to the real code. Trigger phrases — "which doc covers X", "find the schema for PortfolioResponse", "where is GET /api/holdings documented", "docs for verdict.riskprofile", "add OKF frontmatter to this doc", "lint the wiki", "scaffold a new ADR/chapter". Run: scripts/run.sh find|schema|index|lint|new (or python3 scripts/finddocs.py --repo ...).
Quick start
- Choose your skills. Select individual skills above, or choose the entire pack.
- Copy the install prompt. Use Copy install prompt above the list.
- Send it to your agent. Paste into your coding agent’s chat. Your agent reviews the source and guides the setup.
Try it with your agent
After installation, start with a request like:
Use the Invest Backup skill to help with my task.
Ask me for the context you need before getting started.Requirements & license
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