功能描述

提供基于Fava/Beancount的投资组合管理能力，支持税务亏损收割优化、资产配置分析与等价证券分组识别，辅助用户制定最优卖出策略。

使用说明 (SKILL.md)

Fava 账本查看 (fava-beancount-viewer)

Name: Fava Beancount Viewer
Author: tangweigang-jpg

提供基于Fava/Beancount的投资组合管理能力，支持税务亏损收割优化、资产配置分析与等价证券分组识别，辅助用户制定最优卖出策略。

Pipeline

data_collection -> data_storage -> factor_computation -> target_selection -> trading_execution -> visualization

Top Use Cases (5 total)

Portfolio Management CLI Entry Point (`UC-101`)

Provides a unified command-line interface for portfolio management operations including tax loss harvesting, asset allocation analysis, cash drag dete Triggers: portfolio management, CLI, command line

Tax-Optimized Selling Strategy (`UC-103`)

Determines optimal sell order for securities to minimize realized capital gains by analyzing cost basis and holding periods across multiple lots Triggers: minimize gains, tax-efficient selling, capital gains optimization

Tax Loss Harvesting Opportunity Detection (`UC-105`)

Identifies securities with unrealized losses that can be sold to harvest tax losses, typically looking back 30 days to find positions eligible for was Triggers: tax loss harvesting, loss identification, wash sale

For all 5 use cases, see references/USE_CASES.md.

Execute trigger: When user intent matches intent_router.uc_entries[].positive_terms AND user uses action verb (run/execute/跑/执行/backtest/fetch/collect)

What I'll Ask You

Target market: A-share (default), HK, or crypto? (US stocks in ZVT are half-baked — stockus_nasdaq_AAPL exists but coverage is thin)
Data source / provider: eastmoney (free, no account), joinquant (account+paid), baostock (free, good history), akshare, or qmt (broker)?
Strategy type: MACD golden-cross, MA crossover, volume breakout, fundamental screen, or custom factor?
Time range: start_timestamp and end_timestamp for backtest period
Target entity IDs: specific stocks (stock_sh_600000) or index components (SZ1000)?

Semantic Locks (Fatal)

ID	Rule	On Violation
`SL-01`	Execute sell orders before buy orders in every trading cycle	halt
`SL-02`	Trading signals MUST use next-bar execution (no look-ahead)	halt
`SL-03`	Entity IDs MUST follow format entity_type_exchange_code	halt
`SL-04`	DataFrame index MUST be MultiIndex (entity_id, timestamp)	halt
`SL-05`	TradingSignal MUST have EXACTLY ONE of: position_pct, order_money, order_amount	halt
`SL-06`	filter_result column semantics: True=BUY, False=SELL, None/NaN=NO ACTION	halt
`SL-07`	Transformer MUST run BEFORE Accumulator in factor pipeline	halt
`SL-08`	MACD parameters locked: fast=12, slow=26, signal=9	halt

Full lock definitions: references/LOCKS.md

Top Anti-Patterns (15 total)

AP-ACCOUNTING-001: Using floating-point arithmetic for monetary amounts
AP-ACCOUNTING-002: Skipping initialization calls before VM/script execution
AP-ACCOUNTING-003: Mixing different asset types in monetary operations

All 15 anti-patterns: references/ANTI_PATTERNS.md

Evidence Quality Notice

[QUALITY NOTICE] This crystal was compiled from blueprint finance-bp-078. Evidence verify ratio = 21.6% and audit fail total = 14. Generated results may have uncaptured requirement gaps. Verify critical decisions against source files (LATEST.yaml / LATEST.jsonl).

Reference Files

File	Contents	When to Load
references/seed.yaml	V6+ 全量权威 (source-of-truth)	有行为/决策争议时必读
references/ANTI_PATTERNS.md	15 条跨项目反模式	开始实现前
references/WISDOM.md	跨项目精华借鉴	架构决策时
references/CONSTRAINTS.md	domain + fatal 约束	规则冲突时
references/USE_CASES.md	全量 KUC-* 业务场景	需要完整示例时
references/LOCKS.md	SL-* + preconditions + hints	生成回测/交易代码前
references/COMPONENTS.md	AST 组件地图（按 module 拆分）	查 API 时

Compiled by Doramagic crystal-compilation-v6.1 from finance-bp-078 blueprint at 2026-04-22T13:00:29.702985+00:00. See human_summary.md for non-technical overview.

安全使用建议

What to consider before installing/using this skill: - The skill is instruction-only and will expect the agent/host to run Python (3.12+) and the ZVT ecosystem; the published metadata does NOT list these binaries or environment variables — verify the host requirements before running. - The runtime steps include running python commands, creating/using ~/.zvt, installing packages (pip install zvt), and invoking data recorders which will access network data providers (eastmoney, joinquant, akshare, etc.). Run the skill in a sandbox or isolated environment first. - The SKILL.md describes 'trading_execution' and tax-optimized sell strategies but does not declare or request broker API keys/credentials. Before connecting any real brokerage account, confirm exactly where and how trade orders would be executed (dry-run vs live) and whether the skill will prompt for credentials or call external trading endpoints. - Evidence quality notice in SKILL.md indicates low verification (evidence verify ratio 21.6% and audit fail count). Treat automated recommendations as provisional; cross-check critical financial decisions yourself. - Licensing is proprietary — review LICENSE.txt (not included) for usage/redistribution restrictions. Actionable steps I recommend: 1) Ask the publisher for an explicit runtime requirements list (Python version, required packages, exact data providers/brokers and which credentials are needed). 2) If you decide to run it, do so in a sandboxed environment (VM/container) that has no access to real brokerage credentials or production funds. 3) Review seed.yaml and precondition commands before executing them; disable any automatic install steps until you confirm sources. 4) Use dry-run/backtest modes only until you validate outputs and semantic-lock compliance. 5) If you need higher assurance, request the skill owner to publish an install spec and declared env/credential requirements so the registry metadata matches actual runtime needs.

功能分析

Type: OpenClaw Skill Name: fava-beancount-viewer Version: 0.3.3 The skill bundle provides a comprehensive framework for portfolio management and tax optimization using Beancount and the ZVT quant library. The instructions in SKILL.md and seed.yaml are focused on enforcing financial integrity, such as using Decimal types for monetary calculations (CW-ACCOUNTING-001) and adhering to IRS wash sale rules (finance-C-081). No evidence of data exfiltration, malicious persistence, or harmful prompt injection was found; the system's capabilities are strictly aligned with its stated purpose of financial analysis and reporting.

能力标签

cryptorequires-walletcan-make-purchasesrequires-sensitive-credentials

能力评估

⚠ Purpose & Capability

Name/description claim a Fava/Beancount viewer and portfolio management (tax-loss harvesting, allocation, sell-strategy). SKILL.md and seed.yaml however require Python/ZVT operations, a ZVT data directory (~/.zvt), ZVT recorders/data fetchers, and an end-to-end pipeline including 'trading_execution'. Yet the registry metadata lists no required binaries, no environment variables, and no install spec. That mismatch (required runtime dependencies undocumented) is disproportionate and unexplained. Also: trading-execution stage implies broker interaction, but no broker credentials or endpoints are declared.

ℹ Instruction Scope

The runtime instructions direct the agent to re-read seed.yaml, run precondition checks that invoke python3 commands (import zvt, run recorders, check/write ~/.zvt), and enforce numerous 'semantic locks' (fatal constraints) before trading/backtest. These actions involve filesystem access (~/.zvt), package installation guidance (pip install zvt), network data fetchers (eastmoney, joinquant, akshare, etc. referenced), and running recorders/recording scripts. The SKILL.md does not instruct arbitrary exfiltration, but it does grant broad discretion to run Python commands and write data locally; that broad scope should be expected for an end-to-end pipeline but is more privileged than a simple 'viewer'.

✓ Install Mechanism

This is an instruction-only skill with no install spec and no code files to execute — lowest install risk. However, the instructions expect the agent/host to run Python and install packages like zvt if missing; those installs would be performed by the host (not prepackaged by the skill).

⚠ Credentials

The skill declares no required env vars or credentials, yet SKILL.md and seed.yaml expect/mention ZVT_HOME, python3 availability, and data providers (eastmoney, joinquant, broker/qmt). Trading-related capabilities imply broker credentials or API keys would be necessary, but none are declared. This under-declaration is suspicious because the runtime steps will likely prompt for or require sensitive provider/broker credentials that are not surfaced in metadata.

✓ Persistence & Privilege

Skill does not request 'always:true' and does not claim the ability to modify other skills or global agent settings. It does expect to read/write host workspace paths (e.g., ZVT_HOME ~/.zvt, host_workspace/scripts, host_workspace/skills) as part of preconditions and data storage — typical for a data-processing/backtest tool, but this is a filesystem-modifying behavior to be aware of.

版本历史

v0.3.3

v0.3.3: bilingual metadata injected. H1 shows Fava 账本查看; tagline replaced with skill-specific Chinese hook; tags upgraded to Level 1-4.

v0.3.1

Remove install.sh — knowledge-only bundle. Host AI consumes directly from URL; no user-side installation needed. Fixes ClawHub suspicious flag.

v0.3.0

Doramagic crystal portfolio v0.3.0. Full 5-layer bp-009 standard. github.com/tangweigang-jpg/doramagic-skills

元数据

Slug fava-beancount-viewer

版本 0.3.3

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 3

常见问题

Fava Beancount Viewer 是什么？

提供基于Fava/Beancount的投资组合管理能力，支持税务亏损收割优化、资产配置分析与等价证券分组识别，辅助用户制定最优卖出策略。它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 107 次。

如何安装 Fava Beancount Viewer？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install fava-beancount-viewer」即可一键安装，无需额外配置。

Fava Beancount Viewer 是免费的吗？

是的，Fava Beancount Viewer 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

Fava Beancount Viewer 支持哪些平台？

Fava Beancount Viewer 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。

谁开发了 Fava Beancount Viewer？

由 Tang Weigang（@tangweigang-jpg）开发并维护，当前版本 v0.3.3。

Fava Beancount Viewer