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.
npx skills add Nero1688/claude-academic-skills --skill interview-method-designergit clone --depth 1 https://github.com/Nero1688/claude-academic-skillsWrote 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/nero1688/claude-academic-skills/interview-method-designer)<a href="https://agentmods.dev/skills/nero1688/claude-academic-skills/interview-method-designer"><img src="https://agentmods.dev/badge/skills/nero1688/claude-academic-skills/interview-method-designer/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/nero1688/claude-academic-skills/interview-method-designer"><img src="https://agentmods.dev/badge/skills/nero1688/claude-academic-skills/interview-method-designer.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 | $0.00423 | $0.01730 |
| Opus 5 | $0.00211 | $0.00865 |
| Sonnet 5 | $0.00085 | $0.00346 |
| Haiku 4.5 | $0.00042 | $0.00173 |
Grade A, and why
interview-method-designer 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.
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.
What it actually says
深度訪談方法設計師(Interview Method Designer)
Step 1|質化證成(先問值不值得訪)
- 研究問題必須是「如何/為何/過程/意義」型;若其實是「多大/是否顯著」型, 誠實建議轉 research-method-selector 重新適配。
- 定位質化取徑:主題分析(彈性,接 Braun & Clarke)/紮根理論(建理論)/ 個案研究(Yin 式,重脈絡)——取徑決定抽樣與飽和語言,先選再往下。
Step 2|訪談大綱(三層結構)
主題區塊(3–5 個)→ 每區塊主問題(1–2 題)→ 備用追問(每主問 2–4 個)
設計鐵律:
- 主問題開放且經驗導向:「請談談您公司決定導入○○的那段過程」——不是 「您認為○○重要嗎?」(封閉+誘導雙重犯規)。
- 追問只備不搶:probe 是「後來呢?」「當時誰反對?」「能舉個實例嗎?」—— 追經驗細節,不追認同你的假設。
- 順序:暖身(角色與背景)→ 核心區塊(由具體事件到抽象反思)→ 收尾 (「有沒有我沒問到但您覺得重要的?」必放)。
- 全綱禁誘導詞:「是不是因為」「有沒有覺得」開頭的主問一律重寫。
- 大綱要試訪(pilot 1–2 人)後修訂,修訂紀錄留審計軌跡。
Step 3|抽樣與飽和(頂刊審查重點)
- 抽樣策略三選一並說理:立意抽樣(依理論相關特徵選人,附選樣矩陣:職位× 產業×年資)/理論抽樣(紮根專用,邊分析邊決定下一個訪誰)/滾雪球(難觸及 母體,揭露引介偏誤)。
- 飽和判準先訂後驗:預設初始樣本(管理研究單一脈絡通常 15–25 人起), 宣稱飽和要有證據——最後 3–5 筆訪談無新增主題碼(附新碼出現曲線表), 不是「訪到沒時間了」。
- 受訪者資訊表:匿名代號、關鍵特徵、訪談時長、地點形式——投稿必附。
Step 4|倫理與知情同意
知情同意書必含:研究目的(白話)、錄音與逐字稿授權、匿名化承諾(化名+可識別 細節模糊化)、資料保存(加密、年限、僅研究用)、隨時退出權、聯絡方式。
- 組織內訪談的特殊風險:上級引介時受訪者的「自願」是否真自願;訪談內容不回流 給其主管——設計裡寫明防火牆。
- 需 IRB/倫理審查時提醒送審,不代做合規判斷。
Step 5|執行與記錄雙軌
- 執行守則:60–90 分鐘;前 10 分鐘 rapport 不進核心;錄音+即時關鍵詞筆記; 訪後 24 小時內寫田野筆記(情境、非語言訊息、研究者自我反思)——這是 reflexivity 的原料,頂刊 JARS-Qual 要求。
- 逐字稿規格:全逐字(含語氣詞)、說話者標記、時間戳每 5 分鐘、匿名化在 轉錄階段完成。逐字稿一字不造——這條與 qualitative-thematic-coder 的 鐵律同源。
- 交棒:逐字稿+田野筆記+受訪者資訊表 → qualitative-thematic-coder。
紅線
- 大綱不誘導、追問不帶假設;訪談是聽故事不是求印證。
- 飽和要證據,樣本數要說理;「質化不用管樣本數」是常見誤解,審稿人不吃。
- 倫理先行:沒有知情同意的錄音一個字都不能用。
- 本 skill 不生成假訪談內容、不代寫「示範逐字稿」——需要練習用模擬資料時, 明確標註為虛構且不得進任何分析。
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.
- 10d ago First seen · 70 lines · 423 tokens per session scan A 2e3383500776
interview-method-designer is a skill published in the GitHub repository Nero1688/claude-academic-skills (6 stars, last pushed 7d ago), licensed MIT. It adds 423 tokens to every session and 1,730 once invoked, about $0.0021 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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