# Portfolio Pattern > Use when someone wants to understand the writing patterns in their portfolio — not what it says but how it reads: passive voice ratio, subject audit, number density, and decision visibility. Triggers on: "패턴 분석해줘", "오너십이 잘 드러나나", "피동형 많이 썼나". - Skill: `newkayak12/portfolio-pattern` (Agent Skill) - Install (CLI): `npx skillmds@latest add newkayak12/portfolio-pattern` - Raw SKILL.md: https://api.skillmd.com/api/skills/newkayak12/portfolio-pattern/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Security - Author: newkayak12 (https://skillmd.com/u/newkayak12) - Updated: 2026-09-21 - Page: https://skillmd.com/skills/newkayak12/portfolio-pattern --- # Portfolio Writing Pattern Analyzer ## When to Use / When Not to Use **Use when:** - Wanting to understand how your writing reads to an interviewer before making changes - Diagnosing patterns: passive voice, vague participation language, number-free impact claims, missing decision visibility - You've received feedback that your portfolio lacks "ownership" but don't know where **Not for:** - Rewriting specific weak sections (use portfolio-rewrite) - Overall portfolio quality scoring (use portfolio-feedback) - JD-specific keyword matching (use portfolio-jd) ## Process 1. **Map the dimensions** — identify which patterns to analyze: subject ratio, agency language, number density, failure narrative, decision visibility, verb energy 2. **Detect patterns** — tally each dimension; flag ambiguous cases with think-tool 3. **Calculate ratios** — decision-verb rate and passive rate (never the 저는/제가 rate); number-free impact claim rate 4. **Identify top 3 patterns** — which most hurt (or help) this portfolio's impression; quote specific examples 5. **Produce per-pattern fixes** — concrete, specific rewrites: not "use active voice" but exactly which sentence to change and how ## Standalone Inputs Provide: your portfolio text (paste or upload). Korean-language portfolios are fully supported. ## What Claude Does / What You Do | Claude | You | |--------|-----| | Audits 6 dimensions: subject ratio, agency language, number density, failure narrative, decision visibility, verb energy | Provides the portfolio text | | Calculates approximate ratios (subject frequency, number-free impact claims) | Validates findings against your actual intent | | Identifies top 3 patterns hurting (or helping) the portfolio | Decides which patterns to address in a rewrite | | Gives one concrete fix per flagged pattern | Executes the rewrites (or uses portfolio-rewrite) | ## Related Skills - `../portfolio-rewrite/SKILL.md` — act on the patterns identified here - `../portfolio-feedback/SKILL.md` — overall assessment alongside pattern analysis - `../portfolio-jd/SKILL.md` — after improving patterns, check fit against a specific JD --- ## Stage 1 — Map the Patterns (Sequential Thinking) Call `sequentialthinking` to plan the analysis before reading the text closely. Think through: - What dimensions of writing signal ownership and seniority? - What counts as "passive voice" in Korean technical writing specifically? (되었습니다, 구현했습니다 with team subject, etc.) - How will you tally patterns systematically vs. anecdotally? - What is the most useful way to present findings — list, table, annotated excerpt, or summary? --- ## Stage 2 — Pattern Detection (Think Tool — Required per Dimension) Call `think` **before analyzing each of the 6 dimensions** — not only when something is ambiguous. The proactive question for every dimension: ``` think: "What would this dimension look like if the candidate had strong ownership? What does this portfolio actually show? Am I seeing a real pattern or a single salient example?" ``` Additionally, call `mcp-reasoner` (beam_search, beamWidth=3) when a passage has competing ownership signals: - Beam A: 개인 오너십 — the candidate is clearly the decision-maker and actor - Beam B: 팀 크레딧 — appropriate acknowledgment of collaborative work - Beam C: 소유권 회피 — collective language used to obscure weak personal contribution This judgment matters most for Subject Audit and Agency Language dimensions, where a single sentence can read differently depending on context. > 🧠 **Pattern note**: Record non-obvious judgments inline — especially when mcp-reasoner changed the classification. --- ## Dimensions to Analyze ### 1. Subject Audit Track who is doing things in each sentence: - **"저희 팀이 / 팀에서"** — team credit where the individual contribution is unclear (flag when it dominates) - **No subject, active voice** — "제안했습니다", "채택했습니다" (normal Korean; not a defect) - **No subject, passive** — "구현되었습니다", "도입되었습니다" (flag) **Do not measure the `저는/제가` rate.** Subject omission is standard in 국문 경력기술서, and well-written ones sit near 0% — scoring against a pronoun threshold flags documents whose ownership is in fact strong, which is exactly backwards. What separates an owner from an executor is the **verb**: count action sentences carrying a decision verb (제안 / 채택 / 배제 / 결정 / 도입 판단) and report that ratio. Under ~20% is the signal worth calling out — the candidate built what they were told to build and never says who chose it. ### 2. Agency Language Flag sentences where the candidate is acted upon rather than acting: - Passive constructions: ~되었습니다, ~되었고, ~되어 - Vague participation: "관여했습니다", "참여했습니다", "기여했습니다" (without saying what) - Directed work: "맡았습니다" without explaining why they were chosen or what decisions they made ### 3. Number Density Count how many impact claims have a concrete number attached: - With number: "응답시간 40% 감소", "MAU 12만 → 80만" - Without: "성능 개선", "대용량 트래픽 처리", "안정적인 서비스 운영" Report the ratio. For a 5+ year portfolio, a number-free impact claim rate above 60% is a problem. ### 4. Failure Narrative Presence Senior engineers have war stories. Scan for: - Incident descriptions and what was done - Decisions that turned out to be wrong and how they recovered - Technical debt acknowledged and addressed - Trade-offs explicitly stated Complete absence of failure or difficulty in a multi-year portfolio is itself a signal — either the candidate is not introspective, or they're being evasive. ### 5. Decision Visibility Can you see the candidate making choices? Look for: - "A 대신 B를 선택한 이유는..." - "당시 옵션은 X, Y, Z였고 우리는 Y를 선택했는데..." - "돌아보면 이 결정이 좋지 않았던 이유는..." If every tech choice is presented as obvious or pre-decided, that's a pattern worth flagging. ### 6. Verb Tense and Energy Korean technical writing often defaults to a flat, report-like register. Note if: - The portfolio reads like a status report vs. a story - Action verbs are specific ("설계했다", "디버깅했다", "제안했다") or generic ("했습니다", "진행했습니다") --- ## Output Structure Write the analysis in Korean. Use this structure: --- **[패턴 분석 요약]** A 3–5 sentence overview of what the portfolio's writing pattern signals to an interviewer. Start with the most important finding. --- **[항목별 분석]** For each dimension: - **의사결정 동사 비율**: [ratio, short interpretation] - **수동/피동 표현**: [count or estimate, examples] - **숫자 밀도**: [ratio — how many claims have numbers] - **실패/어려움 서술**: [present / minimal / absent — examples] - **의사결정 가시성**: [how many decisions are visible vs. implied] - **동사 에너지**: [flat / moderate / active — examples] Insert `🧠 Pattern note` where a finding required non-obvious judgment. --- **[가장 자주 나타나는 패턴 Top 3]** The three patterns that most hurt (or help) this portfolio's impression. Concrete, with a quoted example from the text. --- **[패턴별 개선 제안]** For each flagged pattern: one concrete fix. Not "use more active voice" — but "'팀에서 Kafka를 도입했습니다'를 '대안 3안을 비교해 Kafka를 채택했습니다'로 바꿔, 누가 무엇을 근거로 정했는지 드러내세요." --- **[시그널 요약]** What does this writing pattern say about the candidate to an interviewer — even before they read the content?