[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6MBBCFBV045W2PZETTEZB7G":3,"skill-same:01M6MBBCFBV045W2PZETTEZB7G":118},{"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":28,"publishedAt":49,"linkOnly":50,"markdownContent":51,"markdownBody":52,"frontMatter":53,"refName":60,"commitSha":61,"skillDirectory":62,"forksCount":63,"repositoryHtmlUrl":64,"repositoryHomepageUrl":65,"ownerHtmlUrl":66,"ownerBlogUrl":67,"ownerDescription":68,"updatedAt":69,"install":70,"resources":83},"01M6MBBCFBV045W2PZETTEZB7G","usfiscaldata",null,"Query the U.S. Treasury Fiscal Data REST API for federal financial data. No API key required. Use for national debt (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates, foreign exchange rates, savings bonds, or U.S. government revenue and spending statistics.","hashgraph-online\u002Fawesome-codex-plugins","hashgraph-online","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F160371962?v=4","01M6CNB6NRJVNNGN14TR01Q6D3","HOL (Hashgraph Online)","01M6JT1HSKKG9V68KQAQGBA7XP",1571,"MIT","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[5,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48],"query","debt","for","treasury","exchange rates","spending","economics","scientific","revenue","statistics","data","databases","daily","use","edit","write","read","Bash","open","api","2026-11-10 10:12:30",false,"---\nname: usfiscaldata\ndescription: Query the U.S. Treasury Fiscal Data REST API for federal financial data. No API key required. Use for national debt (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates, foreign exchange rates, savings bonds, or U.S. government revenue and spending statistics.\nlicense: MIT\nallowed-tools: Read Write Edit Bash\nmetadata:\n  version: '1.3'\n  category: scientific-databases\n  maintainer: Kalaris Labs\n  tags: US Treasury, fiscal data, economics, public finance, open data\n---\n\n# U.S. Treasury Fiscal Data API\n\nFree, open REST API from the U.S. Department of the Treasury for federal financial data. No API key or registration required.\n\n**Base URL:** `https:\u002F\u002Fapi.fiscaldata.treasury.gov\u002Fservices\u002Fapi\u002Ffiscal_service`\n\nBrowse [54 datasets and 179 data tables](https:\u002F\u002Ffiscaldata.treasury.gov\u002Fdatasets\u002F) via the dataset search. Verify endpoint paths on each dataset's API Quick Guide — paths change over time.\n\n## Installation\n\n```bash\nuv pip install requests pandas\n```\n\n## Quick Start\n\n```python\nimport requests\nimport pandas as pd\n\nBASE_URL = \"https:\u002F\u002Fapi.fiscaldata.treasury.gov\u002Fservices\u002Fapi\u002Ffiscal_service\"\n\n# Get the current national debt (Debt to the Penny)\nresp = requests.get(f\"{BASE_URL}\u002Fv2\u002Faccounting\u002Fod\u002Fdebt_to_penny\", params={\n    \"sort\": \"-record_date\",\n    \"page[size]\": 1\n})\ndata = resp.json()[\"data\"][0]\nprint(f\"Total public debt as of {data['record_date']}: ${float(data['tot_pub_debt_out_amt']):,.0f}\")\n```\n\n```python\n# Get Treasury exchange rates for recent quarters\nresp = requests.get(f\"{BASE_URL}\u002Fv1\u002Faccounting\u002Fod\u002Frates_of_exchange\", params={\n    \"fields\": \"country_currency_desc,exchange_rate,record_date\",\n    \"filter\": \"record_date:gte:2024-01-01\",\n    \"sort\": \"-record_date\",\n    \"page[size]\": 100\n})\ndf = pd.DataFrame(resp.json()[\"data\"])\n```\n\n## Authentication\n\nNone required. The API is fully open and free.\n\n## Core Parameters\n\n| Parameter | Example | Description |\n|-----------|---------|-------------|\n| `fields=` | `fields=record_date,tot_pub_debt_out_amt` | Select specific columns |\n| `filter=` | `filter=record_date:gte:2024-01-01` | Filter records |\n| `sort=` | `sort=-record_date` | Sort (prefix `-` for descending) |\n| `format=` | `format=json` | Output format: `json`, `csv`, `xml` |\n| `page[size]=` | `page[size]=100` | Records per page (default 100) |\n| `page[number]=` | `page[number]=2` | Page index (starts at 1) |\n\n**Filter operators:** `lt`, `lte`, `gt`, `gte`, `eq`, `in`\n\n```python\n# Multiple filters separated by comma\n\"filter=country_currency_desc:in:(Canada-Dollar,Mexico-Peso),record_date:gte:2024-01-01\"\n```\n\n## Key Datasets & Endpoints\n\n### Debt\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| Debt to the Penny | `\u002Fv2\u002Faccounting\u002Fod\u002Fdebt_to_penny` | Daily |\n| Historical Debt Outstanding | `\u002Fv2\u002Faccounting\u002Fod\u002Fdebt_outstanding` | Annual |\n| Schedules of Federal Debt | `\u002Fv1\u002Faccounting\u002Fod\u002Fschedules_fed_debt` | Monthly |\n\n### Daily & Monthly Statements\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| DTS Operating Cash Balance | `\u002Fv1\u002Faccounting\u002Fdts\u002Foperating_cash_balance` | Daily |\n| DTS Deposits & Withdrawals | `\u002Fv1\u002Faccounting\u002Fdts\u002Fdeposits_withdrawals_operating_cash` | Daily |\n| Monthly Treasury Statement (MTS) | `\u002Fv1\u002Faccounting\u002Fmts\u002Fmts_table_1` (18 tables — see [datasets-fiscal.md](references\u002Fdatasets-fiscal.md)) | Monthly |\n\n### Interest Rates & Exchange\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| Average Interest Rates on Treasury Securities | `\u002Fv2\u002Faccounting\u002Fod\u002Favg_interest_rates` | Monthly |\n| Treasury Reporting Rates of Exchange | `\u002Fv1\u002Faccounting\u002Fod\u002Frates_of_exchange` | Quarterly |\n| Interest Expense on Public Debt | `\u002Fv2\u002Faccounting\u002Fod\u002Finterest_expense` | Monthly |\n\n### Securities & Auctions\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| Treasury Securities Auctions Data | `\u002Fv1\u002Faccounting\u002Fod\u002Fauctions_query` | As Needed |\n| Treasury Securities Upcoming Auctions | `\u002Fv1\u002Faccounting\u002Fod\u002Fupcoming_auctions` | As Needed |\n| Treasury Securities Buybacks | `\u002Fv1\u002Faccounting\u002Fod\u002Fbuybacks_operations` | As Needed |\n\n### Savings Bonds\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| I Bonds Interest Rates | `\u002Fv1\u002Faccounting\u002Fod\u002Fi_bonds_interest_rates` | Semi-Annual |\n| Savings Bonds Issues, Redemptions & Maturities | `\u002Fv1\u002Faccounting\u002Fod\u002Fsavings_bonds_report` | Monthly |\n\n## Response Structure\n\n```json\n{\n  \"data\": [...],\n  \"meta\": {\n    \"count\": 100,\n    \"total-count\": 3790,\n    \"total-pages\": 38,\n    \"labels\": {\"field_name\": \"Human Readable Label\"},\n    \"dataTypes\": {\"field_name\": \"STRING|NUMBER|DATE|CURRENCY\"},\n    \"dataFormats\": {\"field_name\": \"String|10.2|YYYY-MM-DD\"}\n  },\n  \"links\": {\"self\": \"...\", \"first\": \"...\", \"prev\": null, \"next\": \"...\", \"last\": \"...\"}\n}\n```\n\n**Note:** All values are returned as strings. Convert as needed (e.g., `float()`, `pd.to_datetime()`). Null values appear as the string `\"null\"`.\n\n## Common Patterns\n\n### Load all pages into a DataFrame\n\nUse the bounded `fetch_all()` helper in [parameters.md](references\u002Fparameters.md). For small result sets, a single request with `page[size]=10000` may suffice when `meta.total-pages` is 1.\n\n```python\n# Single-page fetch when total-pages == 1\nparams = {\"sort\": \"-record_date\", \"page[size]\": 10000}\nresp = requests.get(f\"{BASE_URL}\u002Fv2\u002Faccounting\u002Fod\u002Fdebt_outstanding\", params=params)\nresult = resp.json()\nif result[\"meta\"][\"total-pages\"] > 1:\n    raise ValueError(\"Use fetch_all() from parameters.md for multi-page results\")\ndf = pd.DataFrame(result[\"data\"])\n```\n\n### Aggregation (automatic sum)\n\nOmitting grouping fields triggers automatic aggregation:\n\n```python\n# Sum all deposits\u002Fwithdrawals by record_date and transaction type\nresp = requests.get(f\"{BASE_URL}\u002Fv1\u002Faccounting\u002Fdts\u002Fdeposits_withdrawals_operating_cash\", params={\n    \"fields\": \"record_date,transaction_type,transaction_today_amt\"\n})\n```\n\n## Reference Files\n\n- **[api-basics.md](references\u002Fapi-basics.md)** — URL structure, HTTP methods, versioning, data types\n- **[parameters.md](references\u002Fparameters.md)** — All parameters with detailed examples and edge cases\n- **[datasets-debt.md](references\u002Fdatasets-debt.md)** — Debt datasets: Debt to the Penny, Historical Debt, Schedules of Federal Debt, TROR\n- **[datasets-fiscal.md](references\u002Fdatasets-fiscal.md)** — Daily Treasury Statement, Monthly Treasury Statement, revenue, spending\n- **[datasets-interest-rates.md](references\u002Fdatasets-interest-rates.md)** — Average interest rates, exchange rates, TIPS\u002FCPI, certified interest rates\n- **[datasets-securities.md](references\u002Fdatasets-securities.md)** — Treasury auctions, savings bonds, SLGS, buybacks\n- **[response-format.md](references\u002Fresponse-format.md)** — Response objects, error handling, pagination, response codes\n- **[examples.md](references\u002Fexamples.md)** — Python, R, and pandas code examples for common use cases\n\n## Agent operating procedure\n\n1. **Check the environment.** Confirm network access, API keys (if required) and the database's current API documentation and rate limits.\n2. **Pin down the inputs.** Confirm formats, identifiers and parameters from the data or the user. Ask rather than guess any value that changes the result.\n3. **Run a small version first.** Fetch a single known record and check the response format before bulk queries.\n4. **Execute the full task** using the instructions and references above.\n5. **Validate the result.** Identifiers resolve, record counts are reported, and the database version or access date is recorded.\n6. **Report.** State what was run (versions, commands, parameters), what was checked, and what is still uncertain.\n\n| If this happens | Do this |\n|---|---|\n| HTTP 429 or 5xx errors | Respect rate limits with backoff, batch requests, and report partial results honestly. |\n| A function, flag or endpoint in these instructions is missing in the installed version | Check the installed version's own documentation (`help()`, `--help`, official docs), adapt, and tell the user. Never invent an API. |\n| A required input, identifier or parameter is ambiguous | Ask the user, or state the assumption explicitly before running. |\n\n**Integrity rules**\n\n- Never fabricate results, parameters, identifiers, citations or statistics. If something cannot be run or verified, say so plainly.\n- Never invent accession numbers, IDs or records; report 'not found' instead.\n- Treat version-specific details here as possibly outdated: confirm them against the official documentation for the installed version.\n- Ask before actions that cost money, consume shared GPUs or cloud quota, touch personal or patient data, or cannot be undone.\n","# U.S. Treasury Fiscal Data API\n\nFree, open REST API from the U.S. Department of the Treasury for federal financial data. No API key or registration required.\n\n**Base URL:** `https:\u002F\u002Fapi.fiscaldata.treasury.gov\u002Fservices\u002Fapi\u002Ffiscal_service`\n\nBrowse [54 datasets and 179 data tables](https:\u002F\u002Ffiscaldata.treasury.gov\u002Fdatasets\u002F) via the dataset search. Verify endpoint paths on each dataset's API Quick Guide — paths change over time.\n\n## Installation\n\n```bash\nuv pip install requests pandas\n```\n\n## Quick Start\n\n```python\nimport requests\nimport pandas as pd\n\nBASE_URL = \"https:\u002F\u002Fapi.fiscaldata.treasury.gov\u002Fservices\u002Fapi\u002Ffiscal_service\"\n\n# Get the current national debt (Debt to the Penny)\nresp = requests.get(f\"{BASE_URL}\u002Fv2\u002Faccounting\u002Fod\u002Fdebt_to_penny\", params={\n    \"sort\": \"-record_date\",\n    \"page[size]\": 1\n})\ndata = resp.json()[\"data\"][0]\nprint(f\"Total public debt as of {data['record_date']}: ${float(data['tot_pub_debt_out_amt']):,.0f}\")\n```\n\n```python\n# Get Treasury exchange rates for recent quarters\nresp = requests.get(f\"{BASE_URL}\u002Fv1\u002Faccounting\u002Fod\u002Frates_of_exchange\", params={\n    \"fields\": \"country_currency_desc,exchange_rate,record_date\",\n    \"filter\": \"record_date:gte:2024-01-01\",\n    \"sort\": \"-record_date\",\n    \"page[size]\": 100\n})\ndf = pd.DataFrame(resp.json()[\"data\"])\n```\n\n## Authentication\n\nNone required. The API is fully open and free.\n\n## Core Parameters\n\n| Parameter | Example | Description |\n|-----------|---------|-------------|\n| `fields=` | `fields=record_date,tot_pub_debt_out_amt` | Select specific columns |\n| `filter=` | `filter=record_date:gte:2024-01-01` | Filter records |\n| `sort=` | `sort=-record_date` | Sort (prefix `-` for descending) |\n| `format=` | `format=json` | Output format: `json`, `csv`, `xml` |\n| `page[size]=` | `page[size]=100` | Records per page (default 100) |\n| `page[number]=` | `page[number]=2` | Page index (starts at 1) |\n\n**Filter operators:** `lt`, `lte`, `gt`, `gte`, `eq`, `in`\n\n```python\n# Multiple filters separated by comma\n\"filter=country_currency_desc:in:(Canada-Dollar,Mexico-Peso),record_date:gte:2024-01-01\"\n```\n\n## Key Datasets & Endpoints\n\n### Debt\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| Debt to the Penny | `\u002Fv2\u002Faccounting\u002Fod\u002Fdebt_to_penny` | Daily |\n| Historical Debt Outstanding | `\u002Fv2\u002Faccounting\u002Fod\u002Fdebt_outstanding` | Annual |\n| Schedules of Federal Debt | `\u002Fv1\u002Faccounting\u002Fod\u002Fschedules_fed_debt` | Monthly |\n\n### Daily & Monthly Statements\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| DTS Operating Cash Balance | `\u002Fv1\u002Faccounting\u002Fdts\u002Foperating_cash_balance` | Daily |\n| DTS Deposits & Withdrawals | `\u002Fv1\u002Faccounting\u002Fdts\u002Fdeposits_withdrawals_operating_cash` | Daily |\n| Monthly Treasury Statement (MTS) | `\u002Fv1\u002Faccounting\u002Fmts\u002Fmts_table_1` (18 tables — see [datasets-fiscal.md](references\u002Fdatasets-fiscal.md)) | Monthly |\n\n### Interest Rates & Exchange\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| Average Interest Rates on Treasury Securities | `\u002Fv2\u002Faccounting\u002Fod\u002Favg_interest_rates` | Monthly |\n| Treasury Reporting Rates of Exchange | `\u002Fv1\u002Faccounting\u002Fod\u002Frates_of_exchange` | Quarterly |\n| Interest Expense on Public Debt | `\u002Fv2\u002Faccounting\u002Fod\u002Finterest_expense` | Monthly |\n\n### Securities & Auctions\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| Treasury Securities Auctions Data | `\u002Fv1\u002Faccounting\u002Fod\u002Fauctions_query` | As Needed |\n| Treasury Securities Upcoming Auctions | `\u002Fv1\u002Faccounting\u002Fod\u002Fupcoming_auctions` | As Needed |\n| Treasury Securities Buybacks | `\u002Fv1\u002Faccounting\u002Fod\u002Fbuybacks_operations` | As Needed |\n\n### Savings Bonds\n\n| Dataset | Endpoint | Frequency |\n|---------|----------|-----------|\n| I Bonds Interest Rates | `\u002Fv1\u002Faccounting\u002Fod\u002Fi_bonds_interest_rates` | Semi-Annual |\n| Savings Bonds Issues, Redemptions & Maturities | `\u002Fv1\u002Faccounting\u002Fod\u002Fsavings_bonds_report` | Monthly |\n\n## Response Structure\n\n```json\n{\n  \"data\": [...],\n  \"meta\": {\n    \"count\": 100,\n    \"total-count\": 3790,\n    \"total-pages\": 38,\n    \"labels\": {\"field_name\": \"Human Readable Label\"},\n    \"dataTypes\": {\"field_name\": \"STRING|NUMBER|DATE|CURRENCY\"},\n    \"dataFormats\": {\"field_name\": \"String|10.2|YYYY-MM-DD\"}\n  },\n  \"links\": {\"self\": \"...\", \"first\": \"...\", \"prev\": null, \"next\": \"...\", \"last\": \"...\"}\n}\n```\n\n**Note:** All values are returned as strings. Convert as needed (e.g., `float()`, `pd.to_datetime()`). Null values appear as the string `\"null\"`.\n\n## Common Patterns\n\n### Load all pages into a DataFrame\n\nUse the bounded `fetch_all()` helper in [parameters.md](references\u002Fparameters.md). For small result sets, a single request with `page[size]=10000` may suffice when `meta.total-pages` is 1.\n\n```python\n# Single-page fetch when total-pages == 1\nparams = {\"sort\": \"-record_date\", \"page[size]\": 10000}\nresp = requests.get(f\"{BASE_URL}\u002Fv2\u002Faccounting\u002Fod\u002Fdebt_outstanding\", params=params)\nresult = resp.json()\nif result[\"meta\"][\"total-pages\"] > 1:\n    raise ValueError(\"Use fetch_all() from parameters.md for multi-page results\")\ndf = pd.DataFrame(result[\"data\"])\n```\n\n### Aggregation (automatic sum)\n\nOmitting grouping fields triggers automatic aggregation:\n\n```python\n# Sum all deposits\u002Fwithdrawals by record_date and transaction type\nresp = requests.get(f\"{BASE_URL}\u002Fv1\u002Faccounting\u002Fdts\u002Fdeposits_withdrawals_operating_cash\", params={\n    \"fields\": \"record_date,transaction_type,transaction_today_amt\"\n})\n```\n\n## Reference Files\n\n- **[api-basics.md](references\u002Fapi-basics.md)** — URL structure, HTTP methods, versioning, data types\n- **[parameters.md](references\u002Fparameters.md)** — All parameters with detailed examples and edge cases\n- **[datasets-debt.md](references\u002Fdatasets-debt.md)** — Debt datasets: Debt to the Penny, Historical Debt, Schedules of Federal Debt, TROR\n- **[datasets-fiscal.md](references\u002Fdatasets-fiscal.md)** — Daily Treasury Statement, Monthly Treasury Statement, revenue, spending\n- **[datasets-interest-rates.md](references\u002Fdatasets-interest-rates.md)** — Average interest rates, exchange rates, TIPS\u002FCPI, certified interest rates\n- **[datasets-securities.md](references\u002Fdatasets-securities.md)** — Treasury auctions, savings bonds, SLGS, buybacks\n- **[response-format.md](references\u002Fresponse-format.md)** — Response objects, error handling, pagination, response codes\n- **[examples.md](references\u002Fexamples.md)** — Python, R, and pandas code examples for common use cases\n\n## Agent operating procedure\n\n1. **Check the environment.** Confirm network access, API keys (if required) and the database's current API documentation and rate limits.\n2. **Pin down the inputs.** Confirm formats, identifiers and parameters from the data or the user. Ask rather than guess any value that changes the result.\n3. **Run a small version first.** Fetch a single known record and check the response format before bulk queries.\n4. **Execute the full task** using the instructions and references above.\n5. **Validate the result.** Identifiers resolve, record counts are reported, and the database version or access date is recorded.\n6. **Report.** State what was run (versions, commands, parameters), what was checked, and what is still uncertain.\n\n| If this happens | Do this |\n|---|---|\n| HTTP 429 or 5xx errors | Respect rate limits with backoff, batch requests, and report partial results honestly. |\n| A function, flag or endpoint in these instructions is missing in the installed version | Check the installed version's own documentation (`help()`, `--help`, official docs), adapt, and tell the user. Never invent an API. |\n| A required input, identifier or parameter is ambiguous | Ask the user, or state the assumption explicitly before running. |\n\n**Integrity rules**\n\n- Never fabricate results, parameters, identifiers, citations or statistics. If something cannot be run or verified, say so plainly.\n- Never invent accession numbers, IDs or records; report 'not found' instead.\n- Treat version-specific details here as possibly outdated: confirm them against the official documentation for the installed version.\n- Ask before actions that cost money, consume shared GPUs or cloud quota, touch personal or patient data, or cannot be undone.\n",{"name":5,"license":15,"metadata":54,"description":7,"allowed-tools":59},{"tags":55,"version":56,"category":57,"maintainer":58},"US Treasury, fiscal data, economics, public finance, open data","1.3","scientific-databases","Kalaris Labs","Read Write Edit Bash","main","2b63f856ce19c2a797929cacabd9e0fc936812fa","plugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata",490,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins","https:\u002F\u002Fhol.org\u002Fplugins\u002Fbest-codex-plugins","https:\u002F\u002Fgithub.com\u002Fhashgraph-online","https:\u002F\u002Fhol.org","Open-source standards and developer tools for interoperable AI agents: discovery, identity, communication, payments, privacy and security.","2026-11-14 02:12:02",{"source":8,"skillName":5,"commands":71,"prompt":81,"zipAvailable":82},[72,75,78],{"tool":73,"command":74},"npx","npx skills add hashgraph-online\u002Fawesome-codex-plugins --skill usfiscaldata",{"tool":76,"command":77},"bunx","bunx skills add hashgraph-online\u002Fawesome-codex-plugins --skill usfiscaldata",{"tool":79,"command":80},"pnpm","pnpm dlx skills add hashgraph-online\u002Fawesome-codex-plugins --skill usfiscaldata","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002FSKILL.md",true,[84,90,94,98,102,106,110,114],{"path":85,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":88,"sourceHtmlUrl":89},"references\u002Fapi-basics.md","REFERENCE","参考文档",3704,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002Freferences\u002Fapi-basics.md",{"path":91,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":92,"sourceHtmlUrl":93},"references\u002Fdatasets-debt.md",5333,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002Freferences\u002Fdatasets-debt.md",{"path":95,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":96,"sourceHtmlUrl":97},"references\u002Fdatasets-fiscal.md",8867,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002Freferences\u002Fdatasets-fiscal.md",{"path":99,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":100,"sourceHtmlUrl":101},"references\u002Fdatasets-interest-rates.md",6423,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002Freferences\u002Fdatasets-interest-rates.md",{"path":103,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":104,"sourceHtmlUrl":105},"references\u002Fdatasets-securities.md",7908,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002Freferences\u002Fdatasets-securities.md",{"path":107,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":108,"sourceHtmlUrl":109},"references\u002Fexamples.md",9665,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002Freferences\u002Fexamples.md",{"path":111,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":112,"sourceHtmlUrl":113},"references\u002Fparameters.md",5465,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002Freferences\u002Fparameters.md",{"path":115,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":116,"sourceHtmlUrl":117},"references\u002Fresponse-format.md",5196,"https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002FKalarisLabs\u002Fresearch-agent-skills\u002Fskills\u002Fusfiscaldata\u002Freferences\u002Fresponse-format.md",[119,128,135,142,169,194],{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":123,"licenseFileUrl":6,"sourceHtmlUrl":124,"categories":125,"keywords":126,"publishedAt":127},"01M746ZWACVKMZ1BJXJZHYJSSX","migrate-to-e2e","Moves an existing Playwright, Cypress, Selenium, Appium, Detox, Maestro, or TesterArmy suite to e2e one slice at a time, with the old suite running beside the new one until each ported test is proven. Keeps a MIGRATION.md progress file so any later session resumes where the last stopped. Optionally plants a defect to show both suites catch it. Use for \u002Fmigrate-to-e2e, \"migrate our tests to e2e\", \"port these Maestro flows\", \"move our TesterArmy tests\", or when a project has an e2e config and an older suite still running.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftester-army\u002Fe2e\u002Fskills\u002Fmigrate-to-e2e\u002FSKILL.md",[],[],"2026-11-11 15:11:14",{"skillNo":129,"name":130,"nameZh":6,"description":131,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":123,"licenseFileUrl":6,"sourceHtmlUrl":132,"categories":133,"keywords":134,"publishedAt":127},"01M746ZPTAX1Q0FBKAB1CYND7E","e2e","Writes, runs, and debugs end-to-end tests for web and mobile apps with e2e, the agentic test runner, which mixes agent.act goals with exact locator assertions on a Playwright browser or an iOS or Android device. Also drives a project's running app live over the e2e MCP server to look at a screen, check a UI change, take a screenshot or record a video, and try a locator; and runs bug bashes, parallel e2e explore runs with each bug proven by a repro test. Use when a project depends on e2e or has an e2e.config.ts, when asked for end-to-end, browser, mobile, or agentic UI tests, to check a change in the running app, to QA or bug bash an app or branch, or when an e2e run fails.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftester-army\u002Fe2e\u002Fskills\u002Fe2e\u002FSKILL.md",[],[],{"skillNo":136,"name":137,"nameZh":6,"description":138,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":123,"licenseFileUrl":6,"sourceHtmlUrl":139,"categories":140,"keywords":141,"publishedAt":127},"01M746ZJN784HVHMDP9MQGCSGG","create-verification-skill","Generate a project-local verify-\u003Capp> skill on top of e2e, so any coding agent can launch the app, check it is worth driving, exercise a feature the way a user does, keep evidence, and bug bash it. Writes the skill, a feature map with one explore charter per feature, and proves it once. Use for \u002Fcreate-verification-skill, \"make a verification skill for this repo\", or when a project has no scripted way to prove UI behavior.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftester-army\u002Fe2e\u002Fskills\u002Fcreate-verification-skill\u002FSKILL.md",[],[],{"skillNo":143,"name":144,"nameZh":6,"description":145,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":123,"licenseFileUrl":6,"sourceHtmlUrl":146,"categories":147,"keywords":148,"publishedAt":49},"01M716A6ETNB9B1SQ3GXZC75VR","deja-search","deja-vu memory — search the user's past AI coding sessions with the deja CLI. Holds what they already settled and never wrote into the repo (naming rules, banned or already-tried tools, required checks before merge, preferred values, who owns what). Use before your first edit in a task, before you call a change done or ready to merge, before you recommend a tool, library, design or reviewer, before re-debugging an error that may already be solved, when they say 'didn't we fix this before', 'what did we decide about X' or 'I already have that', and before telling them something on this machine does not exist.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fvshulcz\u002Fdeja-vu\u002Fskills\u002Fdeja-search\u002FSKILL.md",[],[149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168],"search","deja search","never","error","ready","memory","re","decide","fix","design","debugging","when","you","done","reviewer","io","change","cli","merge","past",{"skillNo":170,"name":171,"nameZh":6,"description":172,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":123,"licenseFileUrl":6,"sourceHtmlUrl":173,"categories":174,"keywords":175,"publishedAt":49},"01M716A3J2W5SENSE9VGMXB375","deja-reflect","End-of-session reflection and memory curation with deja-vu. Review what was decided, what commands broke and what repaired them, and record durable project rules or decisions with deja remember so the next session starts with them.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Fvshulcz\u002Fdeja-vu\u002Fskills\u002Fdeja-reflect\u002FSKILL.md",[],[176,177,178,164,179,180,181,182,183,184,185,186,187,188,154,189,190,191,192,193],"deja reflect","reflect","review","with","record","github","next","https","node","Rules","decisions","brew","remember","project rules","project","session","end","reflection",{"skillNo":195,"name":196,"nameZh":6,"description":197,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":123,"licenseFileUrl":6,"sourceHtmlUrl":198,"categories":199,"keywords":207,"publishedAt":49},"01M715T3RR4BAYSR57HPPTJ0PF","revid","Make, edit, export and post AI videos with Revid (revid.ai) through the Revid MCP server. Use whenever the user wants a short-form or long-form video made (from an idea, a script, a URL, an article, a PDF, a tweet, a product page, their own clips, or a song), wants to find what is going viral on TikTok, YouTube, Instagram or X before making something, wants to edit or re-export an existing Revid project, generate a standalone AI image or clip, make a series episode, or publish and schedule a finished video to connected social accounts. Covers setup (hosted MCP with OAuth, or an API key), the 36 tools, credits, polling and the rules for publishing. Routes to the more specific revid-* skills when one fits.","https:\u002F\u002Fgithub.com\u002Fhashgraph-online\u002Fawesome-codex-plugins\u002Fblob\u002Fmain\u002Fplugins\u002Ftmakersas\u002Frevid-skills\u002Fskills\u002Frevid\u002FSKILL.md",[200,203,206],{"categoryNo":201,"categoryName":202,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":204,"categoryName":205,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[196,208,209,210,211,212,213,190,214,155,215,216,217,218,160,219,220,221,48,222],"URL","Video","short-form","standalone","PDF","viral","tiktok","short","social","MCP","song","image","mcp server","schedule","publish"]