Borrowing it
Nothing to install: this file belongs to spy007111/Vibe-Research. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/spy007111/Vibe-Research/main/.agents/skills/company-research/SKILL.mdgit clone --depth 1 https://github.com/spy007111/Vibe-ResearchWrote 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/spy007111/vibe-research/company-research)<a href="https://agentmods.dev/skills/spy007111/vibe-research/company-research"><img src="https://agentmods.dev/badge/skills/spy007111/vibe-research/company-research/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/spy007111/vibe-research/company-research"><img src="https://agentmods.dev/badge/skills/spy007111/vibe-research/company-research.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 | $0.00133 | $0.06592 |
| Opus 5.5 | $0.00053 | $0.02637 |
| Sonnet 5.5 | $0.00027 | $0.01318 |
| Haiku 4.5 | $0.00013 | $0.00659 |
Grade A, and why
company-research 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 26d 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.
This is a copy
100% identical to company-research — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
个股研究 SOP(company-research)
前置:研究宪法(methodology/constitution.md)是最高纪律(三条不可越线 / 五问 Gate / 估值口径 / 落盘契约),本 SOP 只规定流程。
取数一律用 data-access skill 的脚本(.agents/skills/data-access/scripts/);由编排器在每个阶段开始前执行(手工运行时由研究者执行),脚本输出落在 RUN/fetch/<script>.json,执行账本在 RUN/fetch/_ledger.json——agent 只读取这些结果,不得自行运行取数脚本(取数与解释分阶段,研究宪法 §5)。计算一律用 calc/cli.py(函数契约见 calc/SPEC.md),自己不做任何算术、不做单位换算。
Phase 0 范围声明:本 SOP 当前交付的是"财务估值闭环"——行情 / 财务 / 一致预期 / 估值 / 公告线索。不可替代性与产业链位置的证据(产能 / 客户认证 / 良率 / 专利)需要 industry-chain 等 Phase 1 skill;Phase 0 下该项只能标 待补,报告必须明示"不可替代性未验证"。
0. 开工三件事
- 解析标的:A 股代码 → 6 位 + 市场(SH/SZ/BJ);港股 5 位数字(HK)、美股代码(US)见 §7;由任一 data-access 脚本完成校验。只给名称不给代码时,要求用户提供代码(Phase 0 没有登记的名称解析脚本,不得自造反查)。解析失败就停,不猜。
- 确定运行目录
.local/runs/<run-id>/(编排器给定;手工运行用YYYYMMDD-HHMMSS-<symbol>);取数脚本由编排器 / 研究者传--out-dir执行(原始响应进raw/,结构化输出进fetch/),calc 一律传--run-dir,每次计算一个文件写入calcs/。 - 若
knowledge/companies/有该标的档案:只作线索读取(status 为 stale / refuted 的不得引用为事实);其中历史结论与本次实时数据冲突时,必须用实时数据反证并在报告"风险与反证"中写明,不顺从旧结论。
1. 六阶段(顺序固定,每阶段结束过 Gate 才进下一阶段)
| 阶段 | 目标 | 取数脚本(必需 ★ / 可选 ○) | calc 函数(输入口径) | 阶段 Gate(不过 = 补跑或标缺口) |
|---|---|---|---|---|
| profile | 公司是谁、上市状态、市值、报价是否可用 | ★ fetch_profile ★ fetch_quote ★ fetch_trade_calendar(读其结果) | — | 名称 / 市场 / 上市状态齐;报价通过 §2 依赖矩阵的 stale 判定(非盘前的 is_stale=true 不通过;盘前且日期吻合可按昨收继续);不可替代性标签 tech_moat / capacity_moat / both / 待补(Phase 0 通常为 待补,须明示) |
| financials | 近 8–12 报告期的营收 / 归母 / 扣非(累计值)→ 单季、TTM | ★ fetch_financials | quarterize(对 revenue_cum / net_profit_parent_cum / net_profit_deducted_cum 各跑一次,unit=元, money=true)→ latest_quarter(扣非,unit=元, money=true)→ ttm_sum(归母与扣非各一次,money=true,作 ttm_yoy 与 TTM PE 交叉验证的中间量)→ ttm_yoy(主用归母净利润,money=true,与一致预期 EPS 同口径;扣非口径并列作交叉)→ qoq(最新单季扣非,money=true,仅作拐点信号);EPS 序列(元/股)用 money=false |
最新报告期有扣非净利润;单季序列 ≥ 8 期;每个数带报告期与单位;每次拆分 / 求和都有 calculation_id |
| estimates | 一致预期 EPS(FY T / T+1 / T+2)+ 机构数 + 区间 | ★ fetch_estimates | forward_cagr(eps_t = FY T 均值, eps_t_plus_n = FY T+2 均值, years=2);consensus_dispersion(min, mean, max) 对 FY T+2 |
机构数 ≥ 3(否则标"一致预期不可靠"并继续);min / max 必须一起报;走东财逐篇备源时只能叫"逐篇预测",不得冒充一致预期,且不得进 forward_cagr |
| valuation | 标准产出列 | ★ fetch_quote(总市值、现价)○ fetch_pe_history(分位) | pe_deducted_annualized(总市值 evidence 的 value+unit, 最新单季扣非 value+unit;单位原样传入,由 calc 归一);forward_pe(现价, FY T 均值 EPS);pe_ttm_from_parts(与数据源 pe_ttm 交叉);percentile_rank(history={"history_csv": {"raw_ref": <PE 历史 raw>, "column": "peTTM", "where": {"tradestatus": "1"}}}, current = pe_ttm);peg(扣非×4 PE, 前瞻 CAGR);pe_digestion_scenarios(扣非×4 PE, 前瞻 CAGR)(四个锚 30 / 25 / 22 / 18 各算);forward_vs_ttm_judgement(前瞻 CAGR, 归母 TTM 同比) |
标准产出列每一格要么有 calculation_id,要么写"未获取:原因";无意义域如实 not_meaningful;季节性提示(淡季单季×4 会高估 PE)写入推断段;PE 消化年数只基于当前 PE 与前瞻 CAGR,必须标注"CAGR 为预测";本产品不输出价格锚(红线) |
| risk | 反证与裁决点 | ○ fetch_announcements ○ fetch_kline | — | 每个强结论至少一条反证;前瞻 vs TTM 判读已给出并解释;一致预期分歧已报;数据源冲突逐条列出;数据缺口列出;至少三个裁决点(什么数据出来会推翻 + 下一个公开数据时点) |
| report | 按契约写 report.md | — | — | 结构 = 结论摘要 / 事实 / 推断 / 估值 / 风险与反证 / 裁决点 / 数据缺口;原始事实标 evidence id、派生数字标 calculation id;无任何投资动作建议;状态如实 |
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.
- 26d ago Changed · +16 lines · +18 tokens per session 9a90af83ab1d
- 1mo ago First seen · 123 lines · 115 tokens per session scan A 58c1af4cd8df
company-research is a skill published in the GitHub repository spy007111/Vibe-Research (8 stars, last pushed 8d ago), licensed MIT. It adds 133 tokens to every session and 6,592 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to company-research, differing in 0 lines, and is treated as a copy.
company-research compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| company-researchspy007111/Vibe-Research | Skill | 8 | 8d ago | MIT | A | 133 | Claude Code, Codex |
| sector-rotationHKUDS/Vibe-Trading | Skill | 38k | yesterday | MIT | A | 39 | Claude Code, Codex |
| twitter-readerhimself65/finance-skills | Skill | 3.5k | 2d ago | MIT | A | 110 | Claude Code |
| strategy-pivot-designertradermonty/claude-trading-skills | Skill | 3.7k | 2d ago | MIT | A | 28 | Claude Code, Codex |
| energy-procurementhashgraph-online/awesome-codex-plugins | Skill | 1.5k | yesterday | Apache-2.0 | A | 93 | Claude Code, Codex |
| airdrop-hunting-guidenirholas/three.ws | Skill | 269 | yesterday | Apache-2.0 | A | 54 | Claude Code, Codex |
| multi-expert-analyzerdigoal/blog | Skill | 8.6k | 2d ago | GPL-2.0 | A | 292 | Codex |