[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M70FGESWQ70XJTY45MD010NK":3,"skill-same:01M70FGESWQ70XJTY45MD010NK":78},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":61,"ownerHtmlUrl":62,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":63,"install":64,"resources":77},"01M70FGESWQ70XJTY45MD010NK","spend-awareness",null,"Summarize pasted transaction data by category in plain language to surface spending patterns — descriptive only, does not provide investment advice, budgeting recommendations, or savings plans","jmlozano1990\u002FCowork-Starter-Kit","jmlozano1990","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F212240889?v=4","01M70FFEFRFH4C54MRVST1ZZFW","JmLozano","01M70FFEGEGDMH4RS95JKWH95M",6,"MIT","https:\u002F\u002Fgithub.com\u002Fjmlozano1990\u002FCowork-Starter-Kit\u002Fblob\u002Fmain\u002Fexamples\u002Fpersonal-assistant\u002F.claude\u002Fskills\u002Fspend-awareness\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"awareness","spend awareness","transaction","last","plans","spending","make","investment","patterns","my","go","data","recommendations","budgeting","transactions","code","only","up","categorize","categories","2026-11-10 10:12:30",false,"---\nname: spend-awareness\ndescription: Summarize pasted transaction data by category in plain language to surface spending patterns — descriptive only, does not provide investment advice, budgeting recommendations, or savings plans\ntools: [claude-code]\ntrigger_examples:\n  - \"Categorize my spending from these transactions\"\n  - \"Where did my money go last month?\"\n  - \"Summarize this spending data by category\"\n  - \"What categories make up my recent purchases?\"\n---\n\n## When to use\n\nUse spend-awareness when the user pastes transaction data, bank exports, credit card statements, or a list of recent purchases and wants to understand where their money went. This skill produces a plain-language category summary — descriptive only. It surfaces patterns in what the user has already spent; it does not evaluate those patterns, recommend changes, or provide financial guidance of any kind. Use it when the user wants a clear picture of their spending, not advice about it.\n\n## Triggers\n\n- User says \"categorize my spending\", \"where did my money go\", or \"summarize transactions\" — direct invocation.\n- User pastes a list of transactions, a bank export, or a statement and asks for a breakdown.\n- User asks which categories they spent the most on with transaction data attached.\n- User wants a plain-language summary of their purchases without financial advice.\n\n## Instructions\n\n1. **Read the full transaction data before categorizing.** Do NOT categorize on first pass — read all entries, then group. This prevents misclassification at the boundaries (e.g., a grocery order that includes household items).\n2. **Assign each transaction to a category.** Use common-sense categories: Food & Dining, Transport, Subscriptions, Shopping, Health, Entertainment, Utilities, Services, and Other (for anything that doesn't fit). Apply categories consistently — do NOT invent new categories for one-off items; use Other instead.\n3. **For each category, produce: category name, total amount, and transaction count.** Present as a plain-language bullet list. State totals in the same currency as the input. If multiple currencies are present, note it and do NOT convert.\n4. **Surface patterns with neutral descriptive language only.** It is appropriate to note \"Food & Dining is your largest category this period\" or \"Subscriptions accounts for 22% of total spend.\" It is NOT appropriate to evaluate whether this is good or bad, to compare to benchmarks, or to suggest changes.\n5. **If the user asks for advice, redirect neutrally.** Use this exact phrase: \"for planning, consider a financial advisor.\" Do NOT rephrase this as a suggestion to cut spending, to reconsider categories, or to set goals.\n6. **Do not infer financial goals.** The user's spending pattern is data, not evidence of their priorities. Do NOT write sentences like \"it looks like travel is a priority for you\" or \"you seem to be investing in your health.\" Describe the data; do not interpret it.\n\n## Output format\n\nPlain language bullet list in the chat. Format per category: `- [Category]: $[total] ([N] transactions)`. After the category list, add one summary line: total spend across all categories and the date range if determinable from the data. No JSON, no YAML, no Obsidian wikilinks. Output is portable — usable in a notes app, spreadsheet, or plain text.\n\n## Quality criteria\n\n1. All transactions are categorized — nothing is silently dropped.\n2. Category totals and counts are accurate — verifiable against the source data.\n3. Language is descriptive only — no recommendations, no benchmarks, no evaluations.\n4. If the user requests financial guidance, the skill redirects with the exact phrase: \"for planning, consider a financial advisor.\"\n5. No financial goals are inferred from the spending pattern.\n\n## Anti-patterns\n\n- **Recommending investments** — any suggestion about where to put money, including low-risk or saving-focused suggestions, is investment advice and is outside this skill's scope. Do not provide investment advice.\n- **Suggesting budgeting changes** — \"you might consider reducing your dining spend\" or \"this category seems high\" are budgeting recommendations. This skill describes; it does not recommend. Do not make budgeting recommendations.\n- **Proposing savings plans** — \"setting aside 10% from this category\" or \"if you cut subscriptions, you could save $X\" are savings plans. This skill does not propose savings plans.\n- **Inferring financial goals** — writing sentences that imply the user has a goal (saving, investing, cutting costs) based on their spending data. The data shows what happened; it does not reveal intent.\n- **Moralizing spending categories** — labeling any category as excessive, unnecessary, indulgent, or problematic. Spending data is neutral. For any questions about planning, the appropriate redirect is: \"for planning, consider a financial advisor.\"\n\n## Example\n\n**Input (pasted transactions — partial):**\n\n```\n2026-04-01  Whole Foods  $87.43\n2026-04-02  Uber  $12.50\n2026-04-03  Netflix  $15.99\n2026-04-04  Whole Foods  $54.10\n2026-04-05  Spotify  $9.99\n2026-04-06  Pharmacy  $23.40\n2026-04-07  Amazon  $67.00\n2026-04-08  Gas Station  $48.00\n```\n\n**Output:**\n\n- Food & Dining: $141.53 (2 transactions)\n- Transport: $60.50 (2 transactions)\n- Subscriptions: $25.98 (2 transactions)\n- Health: $23.40 (1 transaction)\n- Shopping: $67.00 (1 transaction)\n\nTotal: $318.41 across 8 transactions (April 1–8, 2026).\n\nFood & Dining is the largest category this period, accounting for 44% of total spend.\n\n## Writing-profile integration\n\nSpend-awareness is a structured data-summary skill — category labels, totals, and counts are data fields and profile-neutral. The summary observation line (\"Food & Dining is the largest category\") is the only prose element where register applies. Consult `context\u002Fwriting-profile.md` for tone on this line only: a formal profile produces \"Food & Dining represents the largest expenditure category\"; a conversational profile produces \"Food & Dining is where most of the spending went.\" The redirect phrase \"for planning, consider a financial advisor\" is always verbatim, never adapted.\n\n## Example prompts\n\n- \"Categorize my spending from these transactions: [paste].\"\n- \"Where did my money go last month? [paste statement].\"\n- \"Summarize this spending data by category: [paste].\"\n- \"What categories make up my recent purchases? [paste].\"\n","## When to use\n\nUse spend-awareness when the user pastes transaction data, bank exports, credit card statements, or a list of recent purchases and wants to understand where their money went. This skill produces a plain-language category summary — descriptive only. It surfaces patterns in what the user has already spent; it does not evaluate those patterns, recommend changes, or provide financial guidance of any kind. Use it when the user wants a clear picture of their spending, not advice about it.\n\n## Triggers\n\n- User says \"categorize my spending\", \"where did my money go\", or \"summarize transactions\" — direct invocation.\n- User pastes a list of transactions, a bank export, or a statement and asks for a breakdown.\n- User asks which categories they spent the most on with transaction data attached.\n- User wants a plain-language summary of their purchases without financial advice.\n\n## Instructions\n\n1. **Read the full transaction data before categorizing.** Do NOT categorize on first pass — read all entries, then group. This prevents misclassification at the boundaries (e.g., a grocery order that includes household items).\n2. **Assign each transaction to a category.** Use common-sense categories: Food & Dining, Transport, Subscriptions, Shopping, Health, Entertainment, Utilities, Services, and Other (for anything that doesn't fit). Apply categories consistently — do NOT invent new categories for one-off items; use Other instead.\n3. **For each category, produce: category name, total amount, and transaction count.** Present as a plain-language bullet list. State totals in the same currency as the input. If multiple currencies are present, note it and do NOT convert.\n4. **Surface patterns with neutral descriptive language only.** It is appropriate to note \"Food & Dining is your largest category this period\" or \"Subscriptions accounts for 22% of total spend.\" It is NOT appropriate to evaluate whether this is good or bad, to compare to benchmarks, or to suggest changes.\n5. **If the user asks for advice, redirect neutrally.** Use this exact phrase: \"for planning, consider a financial advisor.\" Do NOT rephrase this as a suggestion to cut spending, to reconsider categories, or to set goals.\n6. **Do not infer financial goals.** The user's spending pattern is data, not evidence of their priorities. Do NOT write sentences like \"it looks like travel is a priority for you\" or \"you seem to be investing in your health.\" Describe the data; do not interpret it.\n\n## Output format\n\nPlain language bullet list in the chat. Format per category: `- [Category]: $[total] ([N] transactions)`. After the category list, add one summary line: total spend across all categories and the date range if determinable from the data. No JSON, no YAML, no Obsidian wikilinks. Output is portable — usable in a notes app, spreadsheet, or plain text.\n\n## Quality criteria\n\n1. All transactions are categorized — nothing is silently dropped.\n2. Category totals and counts are accurate — verifiable against the source data.\n3. Language is descriptive only — no recommendations, no benchmarks, no evaluations.\n4. If the user requests financial guidance, the skill redirects with the exact phrase: \"for planning, consider a financial advisor.\"\n5. No financial goals are inferred from the spending pattern.\n\n## Anti-patterns\n\n- **Recommending investments** — any suggestion about where to put money, including low-risk or saving-focused suggestions, is investment advice and is outside this skill's scope. Do not provide investment advice.\n- **Suggesting budgeting changes** — \"you might consider reducing your dining spend\" or \"this category seems high\" are budgeting recommendations. This skill describes; it does not recommend. Do not make budgeting recommendations.\n- **Proposing savings plans** — \"setting aside 10% from this category\" or \"if you cut subscriptions, you could save $X\" are savings plans. This skill does not propose savings plans.\n- **Inferring financial goals** — writing sentences that imply the user has a goal (saving, investing, cutting costs) based on their spending data. The data shows what happened; it does not reveal intent.\n- **Moralizing spending categories** — labeling any category as excessive, unnecessary, indulgent, or problematic. Spending data is neutral. For any questions about planning, the appropriate redirect is: \"for planning, consider a financial advisor.\"\n\n## Example\n\n**Input (pasted transactions — partial):**\n\n```\n2026-04-01  Whole Foods  $87.43\n2026-04-02  Uber  $12.50\n2026-04-03  Netflix  $15.99\n2026-04-04  Whole Foods  $54.10\n2026-04-05  Spotify  $9.99\n2026-04-06  Pharmacy  $23.40\n2026-04-07  Amazon  $67.00\n2026-04-08  Gas Station  $48.00\n```\n\n**Output:**\n\n- Food & Dining: $141.53 (2 transactions)\n- Transport: $60.50 (2 transactions)\n- Subscriptions: $25.98 (2 transactions)\n- Health: $23.40 (1 transaction)\n- Shopping: $67.00 (1 transaction)\n\nTotal: $318.41 across 8 transactions (April 1–8, 2026).\n\nFood & Dining is the largest category this period, accounting for 44% of total spend.\n\n## Writing-profile integration\n\nSpend-awareness is a structured data-summary skill — category labels, totals, and counts are data fields and profile-neutral. The summary observation line (\"Food & Dining is the largest category\") is the only prose element where register applies. Consult `context\u002Fwriting-profile.md` for tone on this line only: a formal profile produces \"Food & Dining represents the largest expenditure category\"; a conversational profile produces \"Food & Dining is where most of the spending went.\" The redirect phrase \"for planning, consider a financial advisor\" is always verbatim, never adapted.\n\n## Example prompts\n\n- \"Categorize my spending from these transactions: [paste].\"\n- \"Where did my money go last month? [paste statement].\"\n- \"Summarize this spending data by category: [paste].\"\n- \"What categories make up my recent purchases? 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