analytic-memo

analytic-memo is a skill for Claude Code, Codex from yipng05-max/-skills. It costs 216 tokens per session (1,638 once invoked), scanned A, original, MIT.

A tool for turning spoken or rough research thoughts into structured analytical memos saved as Markdown files. Analytical memos are notes researchers use to develop ideas while studying interview or other qualitative data.

In plain words
What is it for?
Use it in thematic analysis, grounded theory, and similar qualitative research to record ideas about codes, categories, relationships, exceptions, or the researcher’s own assumptions.
Why use it?
It prevents useful interpretations, questions, and connections from being lost during coding. The tool structures the researcher’s thought and asks follow-up questions based on what was said.

Skill for Claude CodeCodex

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

Good fit Use it in thematic analysis, grounded theory, and similar qualitative research to record ideas about codes, categories, relationships, exceptions, or the researcher’s own assumptions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yipng05-max/-skills/analytic-memo
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 yipng05-max/-skills --skill analytic-memo
Clone the repo
git clone --depth 1 https://github.com/yipng05-max/-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 analytic-memo

README.md
[![agentmods](https://agentmods.dev/badge/skills/yipng05-max/-skills/analytic-memo/github.svg)](https://agentmods.dev/skills/yipng05-max/-skills/analytic-memo)
Your own site
<a href="https://agentmods.dev/skills/yipng05-max/-skills/analytic-memo"><img src="https://agentmods.dev/badge/skills/yipng05-max/-skills/analytic-memo/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 analytic-memo

Your own site · 80×15
<a href="https://agentmods.dev/skills/yipng05-max/-skills/analytic-memo"><img src="https://agentmods.dev/badge/skills/yipng05-max/-skills/analytic-memo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 216 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,638 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 $0.00216 $0.01638
Opus 5 $0.00108 $0.00819
Sonnet 5 $0.00043 $0.00328
Haiku 4.5 $0.00022 $0.00164

Measured 9d ago against content hash e9434e6093aa, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

analytic-memo 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.

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.

analytic-memo/SKILL.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

分析备忘录(Analytical Memo)

分析备忘录是质性研究中捕捉分析动能的核心工具。Charmaz(2014)将备忘录定义为 研究者与数据之间持续进行的智识对话,而非填写分类表格的形式操作。 此 skill 的设计原则:研究者只管说出想法,工具负责追问和结构化

启动:获取必要信息

触发后,只需收集两项信息(其余由 skill 自动判断):

  1. 触发内容:用户输入的编码片段、类属名称、原始资料段落、初步想法或困惑 (直接使用用户的原始表述,不要要求用户重新整理或分类)

  2. 保存路径(可选):若未提供,默认保存到 ~/Documents/research-memos/

若用户在之前对话中已提供研究背景(研究主题、研究问题),直接沿用,不重复询问。


内部识别逻辑(对用户不可见)

根据用户输入,自动判断分析方向,不向用户暴露这个判断过程

→ 概念深化(输入是单个编码或类属,附带描述或疑问) 追问:这个概念的核心含义和边界是什么?在哪些条件下更显著或消退? 与已有理论概念有何联系或张力?它暗示了什么理论主张?

→ 关系假设(输入涉及两个或以上概念,且包含关系词:关系、影响、导致、联系、之间) 追问:这个关系的性质是什么(因果、条件、并行、对立)? 数据中有哪些直接证据?在什么情境下成立或不成立(边界条件)?

→ 负面案例(输入包含反差信号:但是、例外、不符合、反而、奇怪、矛盾、和别人不一样) 追问:这是真正的反例,还是揭示了边界条件? 是否需要修订现有类属或理论假设?修订方向是什么?

→ 反身性(输入包含研究者自我指涉:我觉得、我担心、我是否、我的立场、我注意到自己) 追问:研究者的哪种预设或情绪可能影响了这段分析? 这个反思对理论抽样或研究设计有什么启示?

→ 综合展开(输入混合多种信号,或信号不明确) 先用一句话锚定这段想法的核心,再沿最主要的分析方向展开。


发展阶段判断(参考 Birks, Chapman & Francis, 2008)

根据用户描述的研究进展,在文件 frontmatter 中自动标注阶段:

  • preliminary:研究者处于开放编码早期,想法贴近数据、印象式
  • interim:开始跨类属思考,建立概念间联系
  • advanced:涉及核心类属、理论命题或整体理论框架

判断依据:

  • "刚开始编码"/"第一份访谈" → preliminary
  • 提到多个类属的关系/"开始看到模式" → interim
  • 提到核心类属/"理论框架"/"饱和" → advanced
  • 无法判断 → 留空,不强行填写

备忘录生成

按以下结构生成分析内容(对话中展示,同时写入文件):

文件 frontmatter

---
date: YYYY-MM-DD HH:MM
stage: <preliminary | interim | advanced>
tags: [<研究主题关键词>, <核心概念名>]
status: draft
---

正文结构

## 触发材料

用户原始输入,完整引用,一字不改。

## 核心追问

根据内部识别的分析框架展开,400–600字。 语气是研究者自己在思考,不是"建议你思考"——用第一人称或直接陈述。 追问应该推进分析,而不是复述输入内容。

## 暂定命题

一句话。陈述式,可被证伪。格式:"[条件/情境]下,[现象/机制],因为[初步解释]。" 这是备忘录的核心产出,逼迫研究者从模糊感觉走向可检验的命题。

## 待检验

  • 具体的、可操作的检验行动(回到哪份数据?找什么?问什么?)
  • 如需理论抽样,明确说明"去找什么类型的受访者/情境"

保存文件

文件名格式:YYYY-MM-DD_<核心概念词(2-4字)>.md

保存步骤:

  1. 使用 Bash 工具确认目录存在,若不存在则创建:mkdir -p <路径>
  2. 使用 Write 工具写入文件

保存完成后,在对话中只输出三项:

  1. 文件完整路径
  2. 暂定命题(重复一次,让研究者看清楚这句话)
  3. 待检验清单

不要总结备忘录全文,不要复述追问过程。


连续记录模式

一次对话中多次触发时,每条生成独立文件,自动累积。 对话结束时若生成了 2 条以上,汇总告知:本次共生成 N 条备忘录,列出路径和各自的暂定命题


参考文献(供课程引用)

Read the full file on GitHub · 150 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. 9d ago First seen · 150 lines · 216 tokens per session scan A e9434e6093aa

Subscribe to this mod's changes

analytic-memo is a skill published in the GitHub repository yipng05-max/-skills (285 stars, last pushed 4mo ago), licensed MIT. It adds 216 tokens to every session and 1,638 once invoked, about $0.0011 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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