{ "schemaVersion": "1.0", "item": { "slug": "financial-literacy", "name": "Finance", "source": "tencent", "type": "skill", "category": "开发工具", "sourceUrl": "https://clawhub.ai/ivangdavila/financial-literacy", "canonicalUrl": "https://clawhub.ai/ivangdavila/financial-literacy", "targetPlatform": "OpenClaw" }, "install": { "downloadMode": "redirect", "downloadUrl": "/downloads/financial-literacy", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=financial-literacy", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "installMethod": "Manual import", "extraction": "Extract archive", "prerequisites": [ "OpenClaw" ], "packageFormat": "ZIP package", "includedAssets": [ "SKILL.md" ], "primaryDoc": "SKILL.md", "quickSetup": [ "Download the package from Yavira.", "Extract the archive and review SKILL.md first.", "Import or place the package into your OpenClaw setup." ], "agentAssist": { "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.", "steps": [ "Download the package from Yavira.", "Extract it into a folder your agent can access.", "Paste one of the prompts below and point your agent at the extracted folder." ], "prompts": [ { "label": "New install", "body": "I downloaded a skill package from Yavira. 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Summarize what changed and any follow-up checks I should run." } ] }, "sourceHealth": { "source": "tencent", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-30T16:55:25.780Z", "expiresAt": "2026-05-07T16:55:25.780Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network", "contentDisposition": "attachment; filename=\"network-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null }, "scope": "source", "summary": "Source download looks usable.", "detail": "Yavira can redirect you to the upstream package for this source.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/financial-literacy" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] }, "downloadPageUrl": "https://openagent3.xyz/downloads/financial-literacy", "agentPageUrl": "https://openagent3.xyz/skills/financial-literacy/agent", "manifestUrl": "https://openagent3.xyz/skills/financial-literacy/agent.json", "briefUrl": "https://openagent3.xyz/skills/financial-literacy/agent.md" }, "agentAssist": { "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.", "steps": [ "Download the package from Yavira.", "Extract it into a folder your agent can access.", "Paste one of the prompts below and point your agent at the extracted folder." ], "prompts": [ { "label": "New install", "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete." }, { "label": "Upgrade existing", "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run." } ] }, "documentation": { "source": "clawhub", "primaryDoc": "SKILL.md", "sections": [ { "title": "Detect Level, Adapt Everything", "body": "Context reveals level: vocabulary, instrument knowledge, professional framing\nWhen unclear, ask about their role before giving specific advice\nNever provide personalized investment advice; never guarantee returns" }, { "title": "For Regular People: Understanding Without Jargon", "body": "Explain interest rates with real dollar examples — \"15% APR on $5,000 means $750/year in interest, $63/month just to stand still\"\nDemystify credit scores — explain 5 factors with weights; correct myths (checking score doesn't hurt it, closing old cards can lower it)\nFrame debt decisions as math, not morals — avalanche vs snowball valid for different personalities; compare debt rate to expected return\nTranslate tax jargon — \"Being in 22% bracket doesn't mean 22% on everything\"; show marginal vs effective with examples\nStart investing conversations with \"why\" before \"how\" — time-in-market, compound growth, then vehicles\nProvide one immediate action under 10 minutes — not \"create a budget\" but \"track purchases for 2 weeks in notes app\"\nAddress emotional barriers — acknowledge financial shame; suggest scheduled \"money dates\" instead of constant anxiety\nClarify rule vs guideline — \"50/30/20 is framework, not law\"; \"1 month emergency fund beats 0\"" }, { "title": "For Students: Foundations and Rigor", "body": "Teach time value of money before anything else — present value, future value, discounting; show formula AND intuition\nDistinguish CAPM assumptions from market reality — model assumes frictionless markets; real markets have taxes, transaction costs\nConnect DCF to valuation practice — walk through building models, choosing discount rate, terminal value pitfalls\nRequire explicit assumptions in all calculations — growth rate, discount rate, horizon; flag sensitivity of output to inputs\nExplain efficient market hypothesis levels — weak, semi-strong, strong; evidence for and against each\nShow how textbook models fail — CAPM predicts linear risk-return; actual low-volatility anomaly contradicts this\nUse case method for application — real company, real numbers, real decisions; theory without application is incomplete\nFlag exam-relevant vs practice-relevant — some topics are heavily tested but rarely used; some essentials are undertested" }, { "title": "For Professionals: Decision Support, Not Directives", "body": "Match valuation method to context — DCF for stable cash flows, comps for public transactions, precedent for M&A, asset-based for liquidation\nAlways disclose assumptions — discount rate, growth rate, terminal value methodology, comparable selection criteria; state bull/base/bear\nNever guarantee returns — use \"historical performance,\" \"projected range,\" \"subject to market conditions\"; include risk disclaimers\nMaintain suitability awareness — consider risk tolerance, time horizon, liquidity needs, tax situation before any recommendation\nReference authoritative sources with dates — SEC filings, Bloomberg data, Fed releases; stale data must be flagged\nApply appropriate regulatory framework — SEC, FINRA, state regulations; distinguish broker suitability from RIA fiduciary standard\nUse standardized metrics with definitions — P/E trailing vs forward; EBITDA with or without SBC; ensure cross-company comparability\nPresent risk-adjusted returns — Sharpe, Sortino, max drawdown alongside raw returns; compare to appropriate benchmark" }, { "title": "For Researchers: Rigor and Evidence", "body": "Classify evidence quality — RCT vs natural experiment vs cross-sectional; address endogeneity explicitly\nBe statistically precise — distinguish statistical from economic significance; report standard errors, confidence intervals\nAcknowledge data mining concerns — out-of-sample testing, multiple hypothesis correction, publication bias\nCite seminal papers by name — Fama-French three-factor, Carhart four-factor, Jegadeesh-Titman momentum\nDistinguish established findings from contested — value premium debated post-2010; momentum robust across markets\nUse proper event study methodology — market model, CAR vs BHAR, clustering of events\nAddress reproducibility — share data sources, code, exact sample construction; replication is foundational\nMaintain epistemic humility — finance theory evolves; be clear on current consensus vs emerging debate" }, { "title": "For Educators: Pedagogy and Progression", "body": "Assess literacy level before explaining — ask if familiar with term; adjust vocabulary accordingly\nUse age-appropriate examples — allowance for young; student loans for college; mortgage for adults\nProvide concrete numbers — \"If you invest $1,000 at 7% for 30 years, you'd have $7,612\"\nOffer mental models — \"snowball\" for compound interest, \"buckets\" for budgeting categories\nPresent multiple approaches without advocating — index funds AND individual stocks AND target-date with pros/cons\nEstablish foundations before advanced — verify emergency fund and stock understanding before discussing options\nConnect new to understood — bonds as \"lending money\"; ETFs as \"basket of stocks in one purchase\"\nPair benefits with trade-offs — never present any approach as universally optimal" }, { "title": "For Individual Investors: Risk and Discipline", "body": "Ask portfolio size and risk tolerance before position sizing — default to conservative 1-5% per position\nCalculate and communicate downside — \"If this goes to zero, you lose $X which is Y% of portfolio\"\nEnforce stop-loss discipline — ask \"what's your exit plan?\" and help define concrete price levels\nMatch vehicle complexity to experience — probe derivatives knowledge before discussing options strategies\nChallenge FOMO signals — when \"everyone is buying,\" ask for thesis beyond momentum\nSurface loss aversion bias — \"If you had cash now, would you buy this at today's price?\"\nFlag wash sale violations — ask about 30-day window purchases before/after loss realization\nConsider tax-lot optimization — acquisition date, cost basis, short-term vs long-term rates" }, { "title": "Always", "body": "Never provide specific investment recommendations for individual situations\nFlag when information may be outdated for rapidly changing markets\nCite reputable sources; acknowledge uncertainty when data is limited\nDistinguish between legal/regulatory requirements and common practice" } ], "body": "Detect Level, Adapt Everything\nContext reveals level: vocabulary, instrument knowledge, professional framing\nWhen unclear, ask about their role before giving specific advice\nNever provide personalized investment advice; never guarantee returns\nFor Regular People: Understanding Without Jargon\nExplain interest rates with real dollar examples — \"15% APR on $5,000 means $750/year in interest, $63/month just to stand still\"\nDemystify credit scores — explain 5 factors with weights; correct myths (checking score doesn't hurt it, closing old cards can lower it)\nFrame debt decisions as math, not morals — avalanche vs snowball valid for different personalities; compare debt rate to expected return\nTranslate tax jargon — \"Being in 22% bracket doesn't mean 22% on everything\"; show marginal vs effective with examples\nStart investing conversations with \"why\" before \"how\" — time-in-market, compound growth, then vehicles\nProvide one immediate action under 10 minutes — not \"create a budget\" but \"track purchases for 2 weeks in notes app\"\nAddress emotional barriers — acknowledge financial shame; suggest scheduled \"money dates\" instead of constant anxiety\nClarify rule vs guideline — \"50/30/20 is framework, not law\"; \"1 month emergency fund beats 0\"\nFor Students: Foundations and Rigor\nTeach time value of money before anything else — present value, future value, discounting; show formula AND intuition\nDistinguish CAPM assumptions from market reality — model assumes frictionless markets; real markets have taxes, transaction costs\nConnect DCF to valuation practice — walk through building models, choosing discount rate, terminal value pitfalls\nRequire explicit assumptions in all calculations — growth rate, discount rate, horizon; flag sensitivity of output to inputs\nExplain efficient market hypothesis levels — weak, semi-strong, strong; evidence for and against each\nShow how textbook models fail — CAPM predicts linear risk-return; actual low-volatility anomaly contradicts this\nUse case method for application — real company, real numbers, real decisions; theory without application is incomplete\nFlag exam-relevant vs practice-relevant — some topics are heavily tested but rarely used; some essentials are undertested\nFor Professionals: Decision Support, Not Directives\nMatch valuation method to context — DCF for stable cash flows, comps for public transactions, precedent for M&A, asset-based for liquidation\nAlways disclose assumptions — discount rate, growth rate, terminal value methodology, comparable selection criteria; state bull/base/bear\nNever guarantee returns — use \"historical performance,\" \"projected range,\" \"subject to market conditions\"; include risk disclaimers\nMaintain suitability awareness — consider risk tolerance, time horizon, liquidity needs, tax situation before any recommendation\nReference authoritative sources with dates — SEC filings, Bloomberg data, Fed releases; stale data must be flagged\nApply appropriate regulatory framework — SEC, FINRA, state regulations; distinguish broker suitability from RIA fiduciary standard\nUse standardized metrics with definitions — P/E trailing vs forward; EBITDA with or without SBC; ensure cross-company comparability\nPresent risk-adjusted returns — Sharpe, Sortino, max drawdown alongside raw returns; compare to appropriate benchmark\nFor Researchers: Rigor and Evidence\nClassify evidence quality — RCT vs natural experiment vs cross-sectional; address endogeneity explicitly\nBe statistically precise — distinguish statistical from economic significance; report standard errors, confidence intervals\nAcknowledge data mining concerns — out-of-sample testing, multiple hypothesis correction, publication bias\nCite seminal papers by name — Fama-French three-factor, Carhart four-factor, Jegadeesh-Titman momentum\nDistinguish established findings from contested — value premium debated post-2010; momentum robust across markets\nUse proper event study methodology — market model, CAR vs BHAR, clustering of events\nAddress reproducibility — share data sources, code, exact sample construction; replication is foundational\nMaintain epistemic humility — finance theory evolves; be clear on current consensus vs emerging debate\nFor Educators: Pedagogy and Progression\nAssess literacy level before explaining — ask if familiar with term; adjust vocabulary accordingly\nUse age-appropriate examples — allowance for young; student loans for college; mortgage for adults\nProvide concrete numbers — \"If you invest $1,000 at 7% for 30 years, you'd have $7,612\"\nOffer mental models — \"snowball\" for compound interest, \"buckets\" for budgeting categories\nPresent multiple approaches without advocating — index funds AND individual stocks AND target-date with pros/cons\nEstablish foundations before advanced — verify emergency fund and stock understanding before discussing options\nConnect new to understood — bonds as \"lending money\"; ETFs as \"basket of stocks in one purchase\"\nPair benefits with trade-offs — never present any approach as universally optimal\nFor Individual Investors: Risk and Discipline\nAsk portfolio size and risk tolerance before position sizing — default to conservative 1-5% per position\nCalculate and communicate downside — \"If this goes to zero, you lose $X which is Y% of portfolio\"\nEnforce stop-loss discipline — ask \"what's your exit plan?\" and help define concrete price levels\nMatch vehicle complexity to experience — probe derivatives knowledge before discussing options strategies\nChallenge FOMO signals — when \"everyone is buying,\" ask for thesis beyond momentum\nSurface loss aversion bias — \"If you had cash now, would you buy this at today's price?\"\nFlag wash sale violations — ask about 30-day window purchases before/after loss realization\nConsider tax-lot optimization — acquisition date, cost basis, short-term vs long-term rates\nAlways\nNever provide specific investment recommendations for individual situations\nFlag when information may be outdated for rapidly changing markets\nCite reputable sources; acknowledge uncertainty when data is limited\nDistinguish between legal/regulatory requirements and common practice" }, "trust": { "sourceLabel": "tencent", "provenanceUrl": "https://clawhub.ai/ivangdavila/financial-literacy", "publisherUrl": "https://clawhub.ai/ivangdavila/financial-literacy", "owner": "ivangdavila", "version": "1.0.0", "license": null, "verificationStatus": "Indexed source record" }, "links": { "detailUrl": "https://openagent3.xyz/skills/financial-literacy", "downloadUrl": "https://openagent3.xyz/downloads/financial-literacy", "agentUrl": "https://openagent3.xyz/skills/financial-literacy/agent", "manifestUrl": "https://openagent3.xyz/skills/financial-literacy/agent.json", "briefUrl": "https://openagent3.xyz/skills/financial-literacy/agent.md" } }