qualitative-thematic-coder

qualitative-thematic-coder is a skill for Claude Code, Codex from Nero1688/claude-academic-skills. It costs 330 tokens per session (2,767 once invoked), scanned A, original, MIT.

A guide for thematic analysis of interview transcripts in organizational management and human resources research. Thematic analysis is a method for finding, checking, naming, and reporting patterns in qualitative text.

In plain words
What is it for?
For familiarizing yourself with transcripts, creating a codebook and coding matrix, grouping codes into themes, comparing cases, planning two-person coding reliability, and writing a report using Braun and Clarke’s six stages.
Why use it?
It helps researchers trace every code and conclusion back to the original transcript without inventing interview content. It also makes disagreements, theory links, and decisions easier to audit.

Skill for Claude CodeCodex

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

Good fit For familiarizing yourself with transcripts, creating a codebook and coding matrix, grouping codes into themes, comparing cases, planning two-person coding reliability, and writing a report using Braun and Clarke’s six stages.

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Install with agentmods
npx agentmods add skills/nero1688/claude-academic-skills/qualitative-thematic-coder
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 Nero1688/claude-academic-skills --skill qualitative-thematic-coder
Clone the repo
git clone --depth 1 https://github.com/Nero1688/claude-academic-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 qualitative-thematic-coder

README.md
[![agentmods](https://agentmods.dev/badge/skills/nero1688/claude-academic-skills/qualitative-thematic-coder/github.svg)](https://agentmods.dev/skills/nero1688/claude-academic-skills/qualitative-thematic-coder)
Your own site
<a href="https://agentmods.dev/skills/nero1688/claude-academic-skills/qualitative-thematic-coder"><img src="https://agentmods.dev/badge/skills/nero1688/claude-academic-skills/qualitative-thematic-coder/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 qualitative-thematic-coder

Your own site · 80×15
<a href="https://agentmods.dev/skills/nero1688/claude-academic-skills/qualitative-thematic-coder"><img src="https://agentmods.dev/badge/skills/nero1688/claude-academic-skills/qualitative-thematic-coder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 330 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,767 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 $0.00330 $0.02767
Opus 5 $0.00165 $0.01384
Sonnet 5 $0.00066 $0.00553
Haiku 4.5 $0.00033 $0.00277

Measured 6d ago against content hash 4b9e3160bb32, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

qualitative-thematic-coder 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 6d 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.

skills/qualitative-thematic-coder/SKILL.md · 78 lines

How it starts

The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.

核心立場:主題分析是詮釋性的,不是把文本丟進機器就吐出真相。你的價值在於逼出研究者自己還沒看見的模式與矛盾,並維持可追溯的審計軌跡,讓外部審查者能複核每個 code 到原文的路徑。

階段一 熟悉資料(Familiarization)

  • 通讀逐字稿,不急著編碼。摘記整體印象、反覆出現的說法、語氣轉折、令人意外處。
  • 產出:一份「初步備忘(memo)」——3–8 條觀察,每條附出處(受訪者代號+段落/行號)。
  • 完成判準:能用幾句話說出這批資料「大致在講什麼、哪裡有張力」,且每個印象都指得到原文。

階段二 初始編碼(Initial Coding)

  • 逐段對「與 RQ 相關」的片段給 code。歸納取向:code 貼著受訪者用語(in-vivo 優先);演繹取向:對照既有編碼框架,並保留「框架外」的殘餘片段另立新 code。
  • 每個 code 立即寫進編碼簿(格式見 output_contract),附至少一句逐字例句。
  • 完成判準:資料中與 RQ 相關的片段大多有 code;同義 code 已初步合併;每個 code 都有可辨識的定義與例句。

階段三 搜尋主題(Searching for Themes)

  • 把 code 依語意親近性聚類為候選主題(candidate themes)與次主題。用「這些 code 共享什麼核心概念」來聚,而非只按字面。
  • 不直接宣布最終主題:改列出 5 個左右「矛盾點/有趣現象/模式」,以提問方式引導研究者做理論思考(例:「A 受訪者把授權說成信任、B 說成放生,同一行為兩種框架——這是個別差異,還是職位造成的詮釋差?」)。
  • 完成判準:有一組候選主題+各自涵蓋的 code 清單;至少列出待研究者裁決的 5 個張力點。

階段四 檢視主題(Reviewing Themes)

  • 兩層檢核:(1) 主題內部 code 是否連貫;(2) 主題之間是否互斥、是否忠實反映整體資料集。
  • 檢查過寬(什麼都塞得進)與過窄(只有一兩句支撐)的主題,建議拆併。
  • 完成判準:每個主題都有足夠且一致的資料支撐、彼此界線清楚,且回貼原文後不失真。

階段五 定義與命名(Defining & Naming)

  • 為每個主題寫一段「範圍聲明」:它捕捉什麼、不捕捉什麼、與相鄰主題的界線。給精準、不浮誇的名稱。
  • 理論對接:把主題/code 嘗試對接策略或 HRM 理論(資源基礎觀、制度理論、社會交換理論、JD-R、心理契約等),生成編碼矩陣(主題 × 理論 × 代表引文)。對接是「推測:」性質的詮釋,標明並附可否證的判準,不強行套理論。
  • 完成判準:每個主題有一句話講得清的定義與名稱,且理論對接標明了確定性等級。

階段六 產出報告(Report)

  • 依 output_contract 出編碼簿、主題敘事與編碼矩陣。每個主張配逐字引文與出處。
  • 附方法透明段:分析取向、編碼者、信度做法、審計軌跡位置。

<output_contract>

  1. 編碼簿(Codebook)— 每個 code 一列,固定欄位: | 代碼 (Code) | 定義 | 納入判準(何時該套此碼) | 排除判準(何時不套/易混淆的鄰碼) | 逐字例句(+受訪者代號/行號) |
  2. 主題結構 — 主題 → 次主題 → code 的層級樹,每個主題附範圍聲明與支撐 code 數。
  3. 編碼矩陣 — 主題 × 案例(受訪者)交叉表,格內填代表引文出處;跨案例比較用。理論對接另出「主題 × 理論」表。
  4. 張力清單 — 階段三的 5 個待裁決問題,以提問呈現,不代研究者拍板。
  5. 方法透明段 — 分析取向(歸納/演繹)、編碼者人數、信度指標與做法、審計軌跡(每個主題可回溯到哪些原始片段)。 所有引文一字不差照抄逐字稿,標注來源。凡屬你的詮釋(非受訪者原話)一律標「推測:」或「詮釋:」,與逐字內容清楚分開。 </output_contract>

Read the full file on GitHub · 78 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. 6d ago Changed · +35 tokens per session 4b9e3160bb32
  2. 11d ago First seen · 78 lines · 295 tokens per session scan A 45e9105c00be

Subscribe to this mod's changes

qualitative-thematic-coder is a skill published in the GitHub repository Nero1688/claude-academic-skills (6 stars, last pushed 8d ago), licensed MIT. It adds 330 tokens to every session and 2,767 once invoked, about $0.0016 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 2026-08-31.

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