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compliance-claw

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UpdatedMarch 18, 2026 at 13:58

Calculate taxes by jurisdiction. Triggers: '计算', '多少税', '税率', '合规报告', '自查报告', 'CGT', 'ACB', '日本', '台湾', '澳洲', '加拿大', '新加坡'. IMPORTANT: You MUST use the exec tool to run: python3 {baseDir}/compliance.py --dataset /tmp/tax_dataset_<YEAR>.json --jurisdiction <JURISDICTION> — the rules engine computes all tax amounts deterministically. Do NOT fabricate tax numbers. Jurisdictions: japan, taiwan, australia, canada, singapore. After exec, present the tax report to user with disclaimer. For JSON output add --json. For full instructions read SKILL.md with read tool.

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Skottbie

Skottbie/VeriTax

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SKILL.md

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name	compliance-claw
description	Calculate taxes by jurisdiction. Triggers: '计算', '多少税', '税率', '合规报告', '自查报告', 'CGT', 'ACB', '日本', '台湾', '澳洲', '加拿大', '新加坡'. IMPORTANT: You MUST use the exec tool to run: python3 {baseDir}/compliance.py --dataset /tmp/tax_dataset_<YEAR>.json --jurisdiction <JURISDICTION> — the rules engine computes all tax amounts deterministically. Do NOT fabricate tax numbers. Jurisdictions: japan, taiwan, australia, canada, singapore. After exec, present the tax report to user with disclaimer. For JSON output add --json. For full instructions read SKILL.md with read tool.
license	MIT
metadata	{"author":"veritax","version":"1.0.0","homepage":"https://github.com/veritax/veritax","openclaw":{"requires":{"bins":["python"]}}}

SKILL: ComplianceClaw — Tax Rules Engine

角色：VeriTax 税规引擎，接收 ScannerClaw 的标准化税务数据集，按用户所在辖区运行确定性规则计算，输出税额 + 自然语言报告。模型：Gemini 3.1 Pro (1x) via sessions_spawn — 需要推理能力解释复杂税规。 核心原则：税务计算由 JSON 规则引擎确定性运行，LLM 只负责解释和呈现结果，不生成数字。

⛔ ANTI-FABRICATION PROTOCOL

禁止伪造税额：所有数字必须来自规则引擎计算结果，LLM 不得自行推算。
禁止跳过规则引擎：即使 LLM "知道"税率，也必须通过规则引擎执行后输出。
辖区未覆盖时诚实声明：若用户辖区不在已实现范围内，明确告知而非猜测。
免责条款必须附加：每份报告末尾必须包含：「本工具提供合规参考建议，最终税务申报请咨询持牌税务师。」

辖区模式

辖区	模式名	核心计算逻辑	规则文件
🇯🇵 日本	`japan`	双轨分类（特定暗号資産20%分离 vs 非特定55%综合）+ 币币逐笔日元计价 + 3年损失结转	`rules/japan.json`
🇹🇼 台湾	`taiwan`	自查报告生成 + 应税所得分类（质押/营业行为判定）	`rules/taiwan.json`
🇦🇺 澳洲	`australia`	CGT + 12个月50%折扣 + lot-level 成本基础	`rules/australia.json`
🇨🇦 加拿大	`canada`	ACB + 50%inclusion rate + superficial loss rule 30天	`rules/canada.json`
🇸🇬 新加坡	`singapore`	所得类型自动分类（质押>$300SGD/借贷利息/Launchpool）	`rules/singapore.json`

执行流程

Step 1: 辖区检测

从用户对话上下文推断辖区（关键词：日本/台湾/澳洲/加拿大/新加坡/英国）。若无法判断 → 询问用户确认。

Step 2: 加载规则文件

从 rules/<jurisdiction>.json 加载对应辖区的税规规则集。

Step 3: 运行规则引擎

将 ScannerClaw 输出的 tax_dataset.json 输入规则引擎，确定性计算：

应税事件分类（交易/质押/空投/借贷利息）
成本基础计算（FIFO/ACB/lot-level）
税额计算（按辖区税率 + 折扣/豁免）
损失结转追踪（如适用）

Step 4: LLM 解释层

将规则引擎的 JSON 输出转换为自然语言报告，附带：

税额汇总表
逐笔应税事件明细（可折叠）
优化建议（如有 TLH 机会 → 提示用户调用 OptimizerClaw）
免责条款

Command Index

# 按辖区计算税额
python {baseDir}/compliance.py --dataset <tax_dataset.json> --jurisdiction japan

# JSON 机器可读输出
python {baseDir}/compliance.py --dataset <tax_dataset.json> --jurisdiction australia --json

参数	必填	默认值	说明
`--dataset`	是	—	ScannerClaw 输出的税务数据集路径
`--jurisdiction`	是	—	辖区：japan / taiwan / australia / canada / singapore
`--json`	否	—	输出原始 JSON 计算结果

More from this repository

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auditor-claw

Skottbie/VeriTax

Generate cryptographic audit trail (zkTLS + TEE + IPFS). Triggers: '验证', 'verify', 'proof', '审计', 'IPFS', 'zkTLS', 'TEE', 'Merkle', '可信证明'. IMPORTANT: You MUST use the exec tool to run: python3 {baseDir}/auditor.py --scan-hash <HASH> --compliance-hash <HASH> — generates ProofBundle with Merkle tree + TDX attestation + IPFS upload. Do NOT fabricate CIDs or proof data. Get hashes from previous scanner/compliance step outputs via sha256sum. After exec, present the ProofBundle CID to user. For full instructions read SKILL.md with read tool. This skill should be used when the user asks to 'generate proof', 'create audit trail', 'verify report', 'upload to IPFS', mentions '验证', 'verify', 'proof', '审计', 'IPFS', 'zkTLS', 'TEE', 'Merkle', '可信证明', 'CID', or wants cryptographic attestation of tax calculations. This is the verifiable layer of VeriTax — it builds Merkle trees, generates TEE attestations, and uploads immutable audit trails to IPFS. Do NOT use when the user only wants data extraction (use scanner-claw), tax

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Skottbie/VeriTax

Scan Binance account data. Triggers: '扫描', '交易记录', '账户数据', '充提记录', '质押收益', 'scan', 'trade history', 'deposit', 'withdraw'. IMPORTANT: You MUST use the exec tool to run: python3 {baseDir}/scanner.py --year <YEAR> --scope all --output /tmp/tax_dataset_<YEAR>.json — this script handles ALL Binance API calls internally (spot/futures/margin/earn/deposits/withdrawals). Do NOT fabricate data or describe steps without executing. Do NOT manually call Binance APIs. After exec, check stdout for [Scanner] OK summary line and present results to user. For XLSX mode add --xlsx <path>. For full instructions read SKILL.md with read tool.

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master-claw

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MANDATORY: You MUST read this SKILL.md file with the read tool BEFORE responding to the user. Never answer without reading the full instructions first. This skill should be used when the user asks for complete tax analysis, mentions '帮我报税', '税务全流程', 'full tax report', '完整税务分析', or expects the end-to-end pipeline. Also use when the user says '开始Demo', '演示', '运行demo', 'demo模式' — IMPORTANT: For demo, you MUST first read SKILL.md, then exec menu.py to get the exact menu text, then send that text verbatim to user. Demo has exactly 2 options: (A) 一次性税务审查 and (B) Continuous Mode. Do NOT invent additional options. Do NOT use when the user only wants data extraction (use scanner-claw), only tax calculation (use compliance-claw), only TLH (use optimizer-claw), or only audit (use auditor-claw).

2026-03-181

optimizer-claw

Skottbie/VeriTax

TLH tax-loss harvesting optimization. Triggers: 'TLH', 'tax-loss', '亏损抵扣', '省税', '优化', 'harvest', 'wash sale', 'Launchpool'. IMPORTANT: You MUST use the exec tool to run: python3 {baseDir}/optimizer.py --dataset /tmp/tax_dataset_<YEAR>.json --jurisdiction <JURISDICTION> — identifies unrealized losses and recommends substitute assets. Do NOT fabricate savings amounts. For monitor mode: python3 {baseDir}/optimizer.py --mode monitor. After exec, present TLH opportunities to user. For full instructions read SKILL.md with read tool.

2026-03-181

name	compliance-claw
description	Calculate taxes by jurisdiction. Triggers: '计算', '多少税', '税率', '合规报告', '自查报告', 'CGT', 'ACB', '日本', '台湾', '澳洲', '加拿大', '新加坡'. IMPORTANT: You MUST use the exec tool to run: python3 {baseDir}/compliance.py --dataset /tmp/tax_dataset_<YEAR>.json --jurisdiction <JURISDICTION> — the rules engine computes all tax amounts deterministically. Do NOT fabricate tax numbers. Jurisdictions: japan, taiwan, australia, canada, singapore. After exec, present the tax report to user with disclaimer. For JSON output add --json. For full instructions read SKILL.md with read tool.
license	MIT
metadata	{"author":"veritax","version":"1.0.0","homepage":"https://github.com/veritax/veritax","openclaw":{"requires":{"bins":["python"]}}}

SKILL: ComplianceClaw — Tax Rules Engine

角色：VeriTax 税规引擎，接收 ScannerClaw 的标准化税务数据集，按用户所在辖区运行确定性规则计算，输出税额 + 自然语言报告。模型：Gemini 3.1 Pro (1x) via sessions_spawn — 需要推理能力解释复杂税规。 核心原则：税务计算由 JSON 规则引擎确定性运行，LLM 只负责解释和呈现结果，不生成数字。

⛔ ANTI-FABRICATION PROTOCOL

禁止伪造税额：所有数字必须来自规则引擎计算结果，LLM 不得自行推算。
禁止跳过规则引擎：即使 LLM "知道"税率，也必须通过规则引擎执行后输出。
辖区未覆盖时诚实声明：若用户辖区不在已实现范围内，明确告知而非猜测。
免责条款必须附加：每份报告末尾必须包含：「本工具提供合规参考建议，最终税务申报请咨询持牌税务师。」

辖区模式

辖区	模式名	核心计算逻辑	规则文件
🇯🇵 日本	`japan`	双轨分类（特定暗号資産20%分离 vs 非特定55%综合）+ 币币逐笔日元计价 + 3年损失结转	`rules/japan.json`
🇹🇼 台湾	`taiwan`	自查报告生成 + 应税所得分类（质押/营业行为判定）	`rules/taiwan.json`
🇦🇺 澳洲	`australia`	CGT + 12个月50%折扣 + lot-level 成本基础	`rules/australia.json`
🇨🇦 加拿大	`canada`	ACB + 50%inclusion rate + superficial loss rule 30天	`rules/canada.json`
🇸🇬 新加坡	`singapore`	所得类型自动分类（质押>$300SGD/借贷利息/Launchpool）	`rules/singapore.json`

执行流程

Step 1: 辖区检测

从用户对话上下文推断辖区（关键词：日本/台湾/澳洲/加拿大/新加坡/英国）。若无法判断 → 询问用户确认。

Step 2: 加载规则文件

从 rules/<jurisdiction>.json 加载对应辖区的税规规则集。

Step 3: 运行规则引擎

将 ScannerClaw 输出的 tax_dataset.json 输入规则引擎，确定性计算：

应税事件分类（交易/质押/空投/借贷利息）
成本基础计算（FIFO/ACB/lot-level）
税额计算（按辖区税率 + 折扣/豁免）
损失结转追踪（如适用）

Step 4: LLM 解释层

将规则引擎的 JSON 输出转换为自然语言报告，附带：

税额汇总表
逐笔应税事件明细（可折叠）
优化建议（如有 TLH 机会 → 提示用户调用 OptimizerClaw）
免责条款

Command Index

# 按辖区计算税额
python {baseDir}/compliance.py --dataset <tax_dataset.json> --jurisdiction japan

# JSON 机器可读输出
python {baseDir}/compliance.py --dataset <tax_dataset.json> --jurisdiction australia --json

参数	必填	默认值	说明
`--dataset`	是	—	ScannerClaw 输出的税务数据集路径
`--jurisdiction`	是	—	辖区：japan / taiwan / australia / canada / singapore
`--json`	否	—	输出原始 JSON 计算结果