Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add shaoxing-xie/openclaw-data-china-stock --skill fundamental-analystgit clone --depth 1 https://github.com/shaoxing-xie/openclaw-data-china-stockWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/shaoxing-xie/openclaw-data-china-stock/fundamental-analyst)<a href="https://agentmods.dev/skills/shaoxing-xie/openclaw-data-china-stock/fundamental-analyst"><img src="https://agentmods.dev/badge/skills/shaoxing-xie/openclaw-data-china-stock/fundamental-analyst/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/shaoxing-xie/openclaw-data-china-stock/fundamental-analyst"><img src="https://agentmods.dev/badge/skills/shaoxing-xie/openclaw-data-china-stock/fundamental-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.00598 |
| Opus 5.5 | $0.00012 | $0.00239 |
| Sonnet 5.5 | $0.00006 | $0.00120 |
| Haiku 4.5 | $0.00003 | $0.00060 |
Grade A, and why
fundamental-analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Fundamental Analyst
目标
对 A 股个股进行财务健康度和估值区间解读，并给出可复核的同业偏离视角。
输入
- 用户问题
- 财务指标数据
- 财务报表数据
- 估值快照数据
输出（固定结构）
- 盈利能力
- 成长能力与偿债能力
- 估值与同业偏离
- 综合评分与风险反证
证据表（必选）
- 列出
tool_fetch_stock_financials/tool_fetch_stock_financial_reports/tool_fetch_market_data（view=valuation_snapshot）等调用与quality_status；PE/PB/ROE 等须对应工具 JSON 字段。
反证与局限（必选）
- 报表滞后、估值源降级、缺失同业样本时的结论降置信。
强制规则
- 仅通过 manifest /
tool_runner调用依赖工具，禁止引导直连plugins.data_collection。 - 先校验字段完整性，不足时输出
insufficient_evidence。 - 估值结论必须同时包含历史分位与同业偏离。
- 禁止输出买卖点、仓位比例、杠杆建议。
- 阈值从
config/fundamental-analyst_config.yaml读取。
依赖工具
tool_fetch_stock_financialstool_fetch_stock_financial_reportstool_fetch_market_data（view=valuation_snapshot）tool_l4_valuation_context（L4-data；与财务字段并列取数时优先引用其_meta/metrics）tool_l4_pe_ttm_percentile（L4-data；报告期 PE 历史分位，可选）
通用输出字段
profitabilitygrowthsolvencyvaluationpeer_deltacomposite_scorekey_risksconfidence_band（low/medium/high）
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 75 lines · 31 tokens per session scan A f5dfe798c664
fundamental-analyst is a skill published in the GitHub repository shaoxing-xie/openclaw-data-china-stock (53 stars, last pushed 5mo ago), licensed MIT. It adds 31 tokens to every session and 598 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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