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review-prep
Generate structured talking points for performance reviews, 1:1s, and self-assessments from accumulated monthly summaries.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Generate structured talking points for performance reviews, 1:1s, and self-assessments from accumulated monthly summaries.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Render brief from template and deliver to configured targets (email, GitHub issue, terminal).
Read and write memory JSON files in the user's dayarc folder.
Check for and apply updates to the Dayarc agent package from GitHub.
Extract corrections from user's reply to a brief email.
Conversationally configure a new signal source connector (Jira, ADO, Linear, Slack, etc.), generate a custom COLLECT skill, and register it in config.json.
Initialize Dayarc data directories, user config, and optional scheduler on first run or reconfiguration.
| name | Review Prep |
| description | Generate structured talking points for performance reviews, 1:1s, and self-assessments from accumulated monthly summaries. |
Trigger this skill when the user says anything like:
This skill reads 1–6 monthly summaries and synthesizes structured talking points for a performance review, 1:1, or self-assessment. Output is rendered to the terminal only — no email, no memory write.
Monthly summaries from memory:
monthly-archive/{YYYY-MM}.json — archived monthly summaries (up to 6)monthly-summary.json — the most recent monthly summaryThe skill determines how many months to include based on the user's request:
Via dayarc-memory, read:
monthly-summary.json (most recent month)monthly-archive/ directorySort by month descending (most recent first). Select the months that fall within the requested period. If fewer months are available than requested, proceed with what exists and note the gap in the output.
If no monthly summaries exist at all, output:
⚠️ No monthly summaries found. Run a monthly brief first (or wait until the end of the month) to build the data this skill needs.
Then stop.
Analyze the selected monthly summaries and produce the following sections. Deduplicate items that appear in multiple months. Where applicable, note month-over-month changes.
accomplishments across all selected months.• {accomplishment} — include source context where available (e.g., PR number, project name).time_allocation across all selected months.learning_progress across all selected months.persistently_stuck across all selected months.time_allocation month-over-month.1. Drove the authentication migration from design to production, reducing login latency by X%.Render to the terminal in the following format. Keep total output under ~2 pages (≈800 words).
╔══════════════════════════════════════════════════════╗
║ Review Prep — {period label} ║
╚══════════════════════════════════════════════════════╝
Data: {N} month(s) — {start month} to {end month}
{If any months were missing: ⚠️ Note: {missing months} not available.}
───────────────────────────────────────────────────────
🏆 KEY ACCOMPLISHMENTS
───────────────────────────────────────────────────────
{Theme group}
• {accomplishment}
• {accomplishment}
{Theme group}
• {accomplishment}
───────────────────────────────────────────────────────
📊 IMPACT AREAS
───────────────────────────────────────────────────────
{area} — {avg effort share}% avg {trend arrow}
{one-line impact narrative}
───────────────────────────────────────────────────────
📈 GROWTH & LEARNING
───────────────────────────────────────────────────────
{topic} — {trajectory}
{recommendation}
───────────────────────────────────────────────────────
🧱 CHALLENGES & BLOCKERS
───────────────────────────────────────────────────────
• {blocker} — stuck {N} weeks {🔴 still open | ✅ resolved}
───────────────────────────────────────────────────────
🔄 FOCUS SHIFTS
───────────────────────────────────────────────────────
{3–5 sentence narrative of how priorities evolved}
───────────────────────────────────────────────────────
💬 TALKING POINTS (copy-paste ready)
───────────────────────────────────────────────────────
1. {crisp one-liner}
2. {crisp one-liner}
...
───────────────────────────────────────────────────────
config.json has a non-en locale, translate the rendered output into that language before displaying. Preserve formatting markers (box-drawing characters, emoji, numbers) unchanged.