sn-search-year-report

sn-search-year-report is a skill for Claude Code, Codex from OpenSenseNova/SenseNova-Skills. It costs 37 tokens per session (1,383 once invoked), scanned A, original, MIT.

A workflow for finding free official annual reports and periodic filings from public companies and bond issuers.

In plain words
What is it for?
It helps locate company filings, report PDFs, filing dates, security codes, and source links for financial research.
Why use it?
It filters out paywalled, inaccessible, and unofficial sources so research uses publicly available disclosures.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps locate company filings, report PDFs, filing dates, security codes, and source links for financial research.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/opensensenova/sensenova-skills/sn-search-year-report
About the project

SenseNova-Skills is a collection of modular skills that extend SenseNova models with office-assistant capabilities such as image generation, presentation creation, spreadsheet analysis, and research. The skills are designed for use in agent runtimes and can be combined into productivity workflows; the catalogue entries are individual skills and agents from this collection.

OpenSenseNova/SenseNova-Skills · 5,570 stars · on GitHub

Install

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.

Any agent
npx skills add OpenSenseNova/SenseNova-Skills --skill sn-search-year-report
Clone the repo
git clone --depth 1 https://github.com/OpenSenseNova/SenseNova-Skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for sn-search-year-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/opensensenova/sensenova-skills/sn-search-year-report/github.svg)](https://agentmods.dev/skills/opensensenova/sensenova-skills/sn-search-year-report)
Your own site
<a href="https://agentmods.dev/skills/opensensenova/sensenova-skills/sn-search-year-report"><img src="https://agentmods.dev/badge/skills/opensensenova/sensenova-skills/sn-search-year-report/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.

agentmods 80×15 button for sn-search-year-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/opensensenova/sensenova-skills/sn-search-year-report"><img src="https://agentmods.dev/badge/skills/opensensenova/sensenova-skills/sn-search-year-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,383 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00037 $0.01383
Opus 5 $0.00018 $0.00691
Sonnet 5 $0.00007 $0.00277
Haiku 4.5 $0.00004 $0.00138

Measured 9d ago against content hash 212f564e9142, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

sn-search-year-report 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 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/year_report_api.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/sn-search-year-report/SKILL.md · 76 lines

How it starts

The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Search Year Report

凭证配置

API key、token 与 cookie 统一建议写在仓库根目录 .env(参考 .env.example),并由 runtime 或用户在执行前加载为同名环境变量。脚本仍只从环境变量或显式 CLI 参数读取凭证;不要把真实密钥写入 skill payload、报告、日志或提交。

只使用免费、官方、可正常访问的年报/年度账目/定期报告来源。遇到商业库、订阅、试用额度、付费下载、登录墙、验证码、防护页、不可访问页面,立即丢弃,不要绕过限制。

输出时保留公司/证券代码、报告期、文件标题、披露日期、PDF 或详情页 URL、来源名称。

工作流

  1. 先判断主体类型:A 股/港股/美股/英企/日本上市公司/发债主体/加拿大/新加坡/澳洲。
  2. scripts/year_report_api.py 和 browser-use 可混合使用:脚本适合结构化查询,网页适合站内筛选、页面确认、下载公开 PDF。
  3. 没有脚本覆盖或需要交互筛选的来源,用 browser-use 打开下表网页,通过站内搜索、筛选公告类别、定位 PDF 或详情页。
  4. 只接受官方披露源;公司官网 IR 可作补充,但不能替代官方源。
  5. 中国普通非上市企业通常没有公开完整财务年报;工商年报不是审计财报,且本技能已丢弃不可稳定访问的工商公示系统。

API 脚本

脚本位置:scripts/year_report_api.py。只依赖 Python 标准库。

python scripts/year_report_api.py cninfo "平安银行" --year 2023 --page-size 5
python scripts/year_report_api.py sec-company apple --limit 5
python scripts/year_report_api.py sec-filings --ticker AAPL --limit 5
python scripts/year_report_api.py download "https://static.cninfo.com.cn/finalpage/2024-03-15/1219306493.PDF" --output report.pdf
命令 免费性 用途
cninfo 免费、免 key 巨潮资讯 A 股公告,默认查年度报告 PDF
sec-company / sec-filings 免费、免 key SEC EDGAR 公司 CIK、10-K/20-F/40-F 年报文件
download 免费公开 URL 下载脚本返回的公开 PDF

cninfo --year 表示报告期年份;脚本会自动查下一年的披露窗口。若要按披露日期精确过滤,改用 --date-range

脚本只保留免 key 接口;任何需要 API key、token、注册登录或订阅的接口都不要加入脚本。

Browser-use 资源

以下来源作为免费官方网页入口;按任务需要与 API 脚本混合使用。

范围 资源 URL 使用要点
A 股全市场 巨潮资讯 https://www.cninfo.com.cn/new/index?lang=zh 搜索公司名/证券代码,筛“年度报告”
沪市上市公司 上交所定期报告 https://www.sse.com.cn/disclosure/listedinfo/regular/ 按证券代码、年份、定期报告筛选
深市上市公司 深交所上市公司公告 https://www.szse.cn/www/disclosure/notice/company/ 按公司、公告类型、时间筛选
北交所上市公司 北交所信息披露 https://www.bse.cn/disclosure/announcement.html 搜索年度报告/定期报告
港股 HKEXnews Predefined Documents https://www1.hkexnews.hk/search/predefineddoc.xhtml 选 Annual Report / Environmental, Social and Governance Information
中国债券发行人 中国货币网债券信息披露 https://www.chinamoney.org.cn/chinese/zqfx/ 搜索发行人年报、审计报告、跟踪评级
中国债券发行人 上海清算所 https://www.shclearing.com.cn/ 搜索发行人年度报告/审计报告
中国债券发行人 上交所债券信息披露 https://bond.sse.com.cn/disclosure/ 搜索债券发行人年度报告
英国公司账目 Companies House 网页 https://find-and-update.company-information.service.gov.uk/ 无 API key 时查 filing history / accounts
加拿大上市公司 SEDAR+ Documents Search https://www.sedarplus.ca/csa-party/service/create.html?_locale=en&service=searchDocuments&targetAppCode=csa-party 选择 Documents,按 issuer/profile 和 annual filings 搜索
新加坡上市公司 SGX Company Announcements https://www.sgx.com/securities/company-announcements 搜索 Annual Report 或公司代码
澳洲上市公司 ASX Announcements https://www.asx.com.au/markets/trade-our-cash-market/announcements 按 ASX code 和 announcement type 搜索

Read the full file on GitHub · 76 lines

Files

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.

Changes

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.

  1. 9d ago First seen · 76 lines · 37 tokens per session scan A 212f564e9142

Subscribe to this mod's changes

sn-search-year-report is a skill published in the GitHub repository OpenSenseNova/SenseNova-Skills (5,570 stars, last pushed yesterday), licensed MIT. It adds 37 tokens to every session and 1,383 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 2026-09-03.

Related

Other skills, from other repositories

stock-analyzer

A comprehensive stock deep analysis tool that combines real-time quotes, fundamental metrics, technical indicators, and growth analysis into a single professional report. Supports A-share, US stocks, HK stocks. Generates detailed investment recommendations with risk assessment and actionable trading strategies.

netease-youdao/LobsterAI · 53 tokens

stock-announcements

A tool guide for fetching official announcements from companies listed on China’s A-share stock markets.

netease-youdao/LobsterAI · 79 tokens

stock-explorer

A Yahoo Finance (yfinance) powered financial analysis tool. Get real-time quotes, generate technical indicator reports (RSI/MACD/Bollinger/VWAP/ATR), summarize fundamentals, and run a one-shot report that outputs a text summary.

netease-youdao/LobsterAI · 55 tokens

Total_Fees_Calculation

Skill for computing total payment processing fees for a merchant over a specific day, date range, or month in the dabstep dataset. Use this skill whenever the question asks for "total fees", "fees paid", or "fees charged" for a merchant over some time period. The computation requires matching each transaction to a fee…

zjunlp/DataMind · 101 tokens

applicable-fee-ids

Solve questions about which fee IDs apply to a payment merchant, transaction characteristics, or time period in the dabstep dataset. Use this skill for any question asking "which fee IDs apply to X", "what are the applicable fee IDs for merchant Y", "which merchants are affected by fee Z", or any query involving…

zjunlp/DataMind · 81 tokens

Dataset_Metadata_and_Business_Rules

Answers questions about the structure, metadata, field definitions, and business rules of the dabstep payment processing dataset. Use this skill when questions ask about: column names, field meanings, fee rule structure, which factors affect fees, fee formula, boolean factor effects on cost, volume/fraud/capture-delay…

zjunlp/DataMind · 101 tokens