org-research

org-research is a skill for Claude Code from AgenticAIPlan/AgenticAISkills. It costs 100 tokens per session (3,977 once invoked), scanned A, original, MIT.

A research workflow for investigating government bodies, companies, research institutions, and other organizations. It collects public evidence, checks links, and turns approved facts into a meeting-preparation report.

In plain words
What is it for?
Use it before meetings or partnerships to research an organization’s role, leadership, reporting structure, departments, recent activity, and relevant business contacts.
Why use it?
It reduces unsupported claims, unreliable links, and confusion between an organization’s real departments, projects, news, and responsibilities. The evidence trail lets people review where key facts came from.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the agentic-ai-skills plugin — 54 skills shipped together

Good fit Use it before meetings or partnerships to research an organization’s role, leadership, reporting structure, departments, recent activity, and relevant business contacts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agenticaiplan/agenticaiskills/org-research
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 AgenticAIPlan/AgenticAISkills --skill org-research
Clone the repo
git clone --depth 1 https://github.com/AgenticAIPlan/AgenticAISkills

Made for: Claude Code.

Or install agentic-ai-skills, the plugin that ships this one along with the rest of its 54 skills.

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 org-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/org-research/github.svg)](https://agentmods.dev/skills/agenticaiplan/agenticaiskills/org-research)
Your own site
<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/org-research"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/org-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.

agentmods 80×15 button for org-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/org-research"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/org-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,977 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.
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 $0.00100 $0.03977
Opus 5 $0.00050 $0.01988
Sonnet 5 $0.00020 $0.00795
Haiku 4.5 $0.00010 $0.00398

Measured 10d ago against content hash 384075b3cfd2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

org-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 10d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/link_audit.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/org-research/SKILL.md · 258 lines

How it starts

The opening of the file, as written. The whole thing — 258 lines — stays where its author put it; the contents beside it link to each section on GitHub.

单位调研 Pipeline Skill

本 Skill 不是普通报告生成器,而是一个调研流水线。它必须先产出关键事实的证据(来源链接),再写报告;必须先过链接审计和事实准入,再进入成稿,以尽量确保关键事实有可核查来源,有助于在交流前深入了解对方机构的情况和业务情况;必须通过 Reviewer 终审,才能标记为正式报告。

业务价值

本 Skill 的核心价值不只是生成机构背景报告,而是帮助各领域业务同学在与各类客户会议交流前,可以实现快速、可靠地理解一个机构的管理情况和业务情况。它面向会前沟通、合作研判、客户拜访、政府事务、产业研究和跨团队信息同步等场景,提供两类关键价值:

  • 快速建立机构认知:通过基本介绍、主要职责、隶属关系图示、内设机构、负责人、近期动态和业务相关部门等固定章节,帮助用户快速看清机构定位、权责边界、组织关系和沟通切入点。
  • 显著降低模型幻觉风险:通过候选来源、原子事实、链接审计、事实准入和 Reviewer 终审形成完整证据链,要求关键事实均可回到公开来源复核,避免无来源结论、虚假链接和模型记忆进入正式报告。

在此基础上,本 Skill 进一步解决机构调研中最容易反复出现的五类问题:

  • 报告内容不可查证,无法判断是大模型幻觉还是真实信息。
  • 虚假链接、首页链接、频道页链接进入正文,导致报告无法复核。
  • 机构简介、职能职责、组织架构、负责人信息混入无来源判断。
  • 把业务栏目、项目、活动新闻误写成现行内设机构或稳定隶属关系。
  • 多单位或多轮调研时格式不一致,后续同事无法沿证据链继续补查。

目标交付不是“看起来完整”的长报告,而是可核查、可降级、可复用的会前机构情报:每个关键事实都能回到候选来源、原子事实、链接审计和事实准入表中复核,尽量确保关键事实真实、可核查,便于业务同学基于这些公开事实做出业务判断,以及基于有可能开展合作的方向,可以方便快捷地通过备注的来源链接进一步深入了解,以寻找业务合作机会。

业务收益:

  • 提高调研效率:将官网检索、来源筛选、事实抽取、链接检查和报告成稿固化为同一套流程,减少从零搭建调研框架的时间。
  • 降低协作成本:不同同事产出的报告使用相同字段、附录和准入标准,便于接力补查、复用和交叉复核。
  • 支持业务判断:把主管关系、组织架构、负责人、近期动态和业务相关部门放在同一证据链中,帮助判断沟通路径、审批链条和合作切入点。
  • 提升风险控制:通过事实准入和 Reviewer 终审,显式区分准入事实、待核实线索和剔除信息,避免无来源结论进入正式材料。

适用场景

当用户要求了解、拜访、会见、调研某个政府单位、企事业单位、研究机构、协会、基金会、科技馆、智库或其他机构时使用。

不适用场景 / 边界

本 Skill 保持独立完整,但不应被泛化为所有研究任务。以下情况不使用或必须降级:

  • 只要求政策、行业或议题背景,不需要围绕具体单位建立事实链。
  • 要求无来源内部判断、非公开信息、私人信息或未公开负责人分工。
  • 要求直接生成合作建议、商业方案或沟通策略,但缺少单位事实证据;此时应先完成机构调研,再另行生成建议。
  • 要求法律、投资、审计、合规结论等高风险判断;本 Skill 只提供公开事实背景和待核实线索。
  • 只有主站首页、搜索结果、登录页、无法访问页面或无关页面时,不生成正式报告。

输入

  • 单位名称:必填;可一次输入多个单位。
  • 会议主题:可选;用于排序重点,不得用于创造无来源事实。
  • 单位类型:可选;政府机构 / 事业单位 / 企业 / 社会组织 / 自动判断。
  • 交付形式:可选;完整报告 / 简版正文 + 完整附录 / 仅输出证据表。默认完整报告。

默认执行完整高可靠调研流程。除非用户明确要求简版或只要证据表,否则不得省略候选来源、原子事实、链接审计、事实准入和 Reviewer 终审。

Step 0:输入与默认假设

若用户未提供完整信息,不要阻塞执行,但必须在报告开头标注默认假设:

  • 会议主题缺失:默认做通用会前背景调研。
  • 单位类型缺失:先自动判断,并在候选来源表中说明判断依据。
  • 交付形式缺失:默认完整报告。

只有当用户目标会影响检索范围且无法合理默认时,才提出简短澄清问题。

最小合格交付标准

标记为正式报告前,必须同时满足:

  • 至少覆盖官网或官方介绍页、职责或业务说明、机构设置或组织关系、负责人信息、近期动态五类检索方向;确无公开来源时必须写入缺口说明。
  • 每个进入正文的关键事实都能在原子事实证据表中找到对应行。
  • 每个正文链接都通过链接审计,并在事实准入表中标记为 准入
  • 附录 A-E 齐全;如果用户要求简版正文,附录可另存为单独文件,但不得省略。
  • Reviewer 终审不存在未修复 error

Read the full file on GitHub · 258 lines

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. 10d ago First seen · 258 lines · 100 tokens per session scan A 384075b3cfd2

Subscribe to this mod's changes

org-research is a skill published in the GitHub repository AgenticAIPlan/AgenticAISkills (11 stars, last pushed 3mo ago), licensed MIT. It adds 100 tokens to every session and 3,977 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 2026-08-30.

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