SKILLEMALL.ai

AC gingiris-user-interview

🇺🇸 User Interview & Cold-Start Operations Playbook — Battle-tested framework from HeyGen's 937 interviews to PMF. Complete SOP for user screening, interview execution, Beta testing methodology, cold-start user operations, churn analysis, and user grading systems. 🇨🇳 用户访谈与冷启动运营实战手册 — 基于 HeyGen 937 场访谈验证的 PMF 方法论。包含用户筛选、访谈执行、Beta 测试设计、冷启动用户运营、流失分析、用户分级体系完整 SOP。 🇯🇵 ユーザーインタビュー&コールドスタート運営プレイブック — HeyGenの937回インタビューで検証されたPMF方法論。ユーザースクリーニング、インタビュー実行、Betaテスト設計、コールドスタートユーザー運営、離脱分析、ユーザーグレーディング。 🇰🇷 사용자 인터뷰 & 콜드 스타트 운영 플레이북 — HeyGen 937회 인터뷰로 검증된 PMF 방법론. 사용자 스크리닝, 인터뷰 실행, Beta 테스트 설계, 콜드 스타트 사용자 운영, 이탈 분석, 사용자 등급 시스템. Triggers: "user interview" | "user research" | "customer discovery" | "PMF" | "product-market fit" | "beta test" | "beta testing" | "cold start users" | "cold start operations" | "churn analysis" | "user grading" | "用户访谈" | "用户调研" | "冷启动" | "冷启动运营" | "Beta测试" | "流失分析" | "用户分级"

ClawHub Agent Skills author: Iris Wei v2.1.3 MIT-0 8 files body ≈ 1 617 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructureResearchtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
51/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "source"

Process rating: all ten parameters 51/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 44 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1617 tokens
  • low 14 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 903: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -216 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +5Description quotes 11 example trigger phrases
  • +4Structure: 30 headings
  • +3Step-by-step instructions: 44 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
This is a non-executable user-research playbook, but it needs review because it encourages recording screens, processing transcripts with AI, collecting personal data, and broad outreach without enough privacy or contact boundaries.
LLM: suspicious (high) · 5 Sept 2026