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 rojim666/SztuCode --skill stock-research-report-expertgit clone --depth 1 https://github.com/rojim666/SztuCodeWrote 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/rojim666/sztucode/stock-research-report-expert)<a href="https://agentmods.dev/skills/rojim666/sztucode/stock-research-report-expert"><img src="https://agentmods.dev/badge/skills/rojim666/sztucode/stock-research-report-expert/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/rojim666/sztucode/stock-research-report-expert"><img src="https://agentmods.dev/badge/skills/rojim666/sztucode/stock-research-report-expert.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 | $0.00101 | $0.02658 |
| Opus 5 | $0.00051 | $0.01329 |
| Sonnet 5 | $0.00020 | $0.00532 |
| Haiku 4.5 | $0.00010 | $0.00266 |
Grade A, and why
stock-research-report-expert 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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
你的产物必须满足：
- 内容维度：信息密度高、数据有据可查、逻辑链条完整、风险提示充分、免责条款齐备
- 结构维度：严格遵循
references/structure_contract.md（文档结构/分节规范/免责声明）
Phase 1 — 主题理解
你需要详细思考如下要点：
- 报告体量判定：
| 用户描述 | 体量档位 | 目标字数 |
|---|---|---|
| 深度研究、首次覆盖、行业深度、产业链分析 | 深度报告 | 8,000–30,000字 |
| 周报、动态点评、事件点评、财报点评 | 常规点评 | 3,000–8,000字 |
| 商业计划书、BP、路演材料 | BP/路演 | 3,000–5,000字 |
| 咨询项目交付、白皮书、专题研究 | 咨询交付物 | 10,000–20,000字 |
| 用户未指定 | 默认常规点评 | 5,000–8,000字 |
- 报告类型识别 → 读取
experts/stock-research-report-expert/references/structure_contract.md确认对应的文档结构模板。 - 目标行业/个股：明确研究标的（行业板块、公司名称、股票代码）。
- 核心信息点 5–8 条：用户已提供的关键数据 + 需要检索补全的行业动态、财务数据、政策信息。
保存到 output/params/topic.yaml：
detected_doc_type: "行业深度报告"
volume_tier: "deep" # deep | regular | bp | consulting
target_length: 15000
target_tone: "第三人称，专业金融研报，信息密度高"
industry: "AI / 人工智能"
target_stocks: [] # 个股研究时填入股票代码
report_category: "行业深度" # 封面标签
analyst_info:
name: "<分析师姓名>"
title: "<职称>"
cert_number: "<执业证书编号>"
mandatory_sections: [] # 由 structure_contract 按体量档位确定
risk_level: "high" # 券商研报默认 high
Phase 1.1 — 格式参考 Gate
触发判定：
- ✅ 用户主动提供
.docx/.pdf参考文档 / 显式声明要参考某文档的格式 → 进入格式参考流程 - ❌ 仅工作目录中有文档 / AI 自行扫描发现 / 用户只提报告类型未附参考 → 跳过本步骤，直接进入 Phase 2
- 🚫 禁止跳过后通过搜索文件系统回溯；禁止用扫描动作倒推触发成立
已触发 → 按以下步骤执行格式参考流程：
- 读取参考文档：Read 用户提供的
.docx/.pdf，提取其结构与排版特征 - 归纳格式特征：章节层级、标题编号规则、字号/字体约定、图表标注样式、封面与免责声明位置
- 映射到本报告结构：将提取到的格式特征对齐到本Expert 的
structure_contract.md章节骨架 - 产出格式约定：将映射结果记录为后续 Phase 生成时遵循的排版约定
- 冲突处理：参考文档格式与券商研报强制要素（风险提示、免责声明、数据披露）冲突时，以强制要素优先
Phase 2 — Research（深度优先，不可跳过）
证券研究报告不存在"纯格式化跳过 Research"的情形——即便是简单的动态点评，也必须检索最新行业动态和数据。因此本阶段强制执行。
你需要先参考 参数字典 <plugin_root>/core/engines/deep-research/README.md 生成驱动引擎的参数，保存到 output/params/deep-research.yaml。生成参数文件后，再读取 <plugin_root>/core/engines/deep-research/engine.md 执行 6 步状态机，产出信息库快照到 snapshot_path。
What ships with it
1 file 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.
- today First seen · 236 lines · 101 tokens per session scan A d03b4a5fd9f6
stock-research-report-expert is a skill published in the GitHub repository rojim666/SztuCode (64 stars, last pushed today), licensed MIT. It adds 101 tokens to every session and 2,658 once invoked, about $0.0005 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 2026-09-12.
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