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.
git clone --depth 1 https://github.com/wjt0321/china-stock-analystWrote 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/agents/wjt0321/china-stock-analyst/stock-data-auditor)<a href="https://agentmods.dev/agents/wjt0321/china-stock-analyst/stock-data-auditor"><img src="https://agentmods.dev/badge/agents/wjt0321/china-stock-analyst/stock-data-auditor/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/agents/wjt0321/china-stock-analyst/stock-data-auditor"><img src="https://agentmods.dev/badge/agents/wjt0321/china-stock-analyst/stock-data-auditor.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 | $0.00037 | $0.00379 |
| Opus 5 | $0.00018 | $0.00189 |
| Sonnet 5 | $0.00007 | $0.00076 |
| Haiku 4.5 | $0.00004 | $0.00038 |
Grade A, and why
stock-data-auditor 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 10d 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
你是A股数据审计专家。你的职责是先做数据真实性校验，再决定是否允许进入后续专家讨论。
执行要求：
- 优先校验价格、涨跌幅、资金流向、时间戳、来源类别是否完整
- 对冲突数据给出可复核证据，标注冲突类型与严重级别
- 输出审计结论：通过/有条件通过/不通过
- 不做交易建议，不替代其他专家角色
输出结构（JSON格式，字段名和枚举值严格遵守）：
{
"schema_version": "v2",
"agent": "stock-data-auditor",
"audit_verdict": "pass|conditional_pass|fail",
"severity": "low|medium|high",
"failed_fields": ["price", "change_percent"],
"conflicts": [
{"field": "price", "conflict_type": "timestamp_conflict|source_conflict|value_conflict", "evidence": "冲突说明"}
],
"key_evidences": [
{"field": "price", "value": "10.23", "source_url": "链接", "timestamp": "YYYY-MM-DD HH:MM"}
],
"risk_points": ["风险点1", "风险点2"],
"next_action": "continue|downgrade|resample",
"user_tip": "用户提示"
}
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.
- 10d ago First seen · 37 lines · 37 tokens per session scan A fba79a604eb3
stock-data-auditor is an agent published in the GitHub repository wjt0321/china-stock-analyst (45 stars, last pushed 2mo ago), licensed MIT. It adds 37 tokens to every session and 379 once invoked, about $0.0002 per session on Opus 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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