Skill: netanel-abergel/pa-eval (version 1.0.1)

--- name: pa-eval description: "Evaluate PA performance through structured scoring, owner feedback analysis, and behavioral benchmarking. Use when: conducting a weekly/monthly PA performance review, owner gives feedback (positive or negative), assessing response quality, or identifying areas for improvement." --- # PA Eval Skill ## Minimum Model Any model for filling in templates. Use a medium model for trend analysis and recommendations. --- ## When to Run - **Weekly self-eval:** Every 7 days. Run automatically. - **On owner correction:** Log the correction immediately, then re-score the affected dimension. - **Monthly report:** At the end of each month, aggregate all weekly evals. - **On demand:** If owner asks "how am I doing?" → generate current eval on the spot. --- ## Scoring Dimensions Score each 1–5: | Dimension | What to Measure | |---|---| | **Execution** | Tasks completed without reminders | | **Accuracy** | Results are correct and complete | | **Speed** | Response time is fast | | **Proactivity** | Acts without being asked | | **Communication** | Concise and context-appropriate | | **Memory** | Remembers context across sessions | | **Tool Use** | Tools used correctly and efficiently | | **Judgment** | Knows when to act vs. when to ask | **Score meanings:** - 5 = Consistently exceeds expectations - 4 = Meets expectations with minor gaps - 3 = Acceptable but basic - 2 = Frequent gaps or errors - 1 = Fails basic expectations **Total:** Max 40 points. Grade: A (36–40), B (28–35), C (20–27), D (<20) --- ## Weekly Self-Evaluation Save to `.learnings/eval/YYYY-MM-DD.md`. ```markdown # PA Weekly Eval — YYYY-MM-DD ## Scores | Dimension | Score | Notes | |---|---|---| | Execution | /5 | | | Accuracy | /5 | | | Speed | /5 | | | Proactivity | /5 | | | Communication | /5 | | | Memory | /5 | | | Tool Use | /5 | | | Judgment | /5 | | | **TOTAL** | /40 | | ## Owner Feedback This Week - Positive: - Corrections: - Complaints: ## Tasks Completed - ## Tasks Failed or Incomplete - ## What Went Well - ## What to Improve - ## Actions for Next Week - [ ] ``` ### Create the File ```bash #!/bin/bash set -e # Set the output directory EVAL_DIR="$HOME/.openclaw/workspace/.learnings/eval" mkdir -p "$EVAL_DIR" DATE=$(date +%Y-%m-%d) EVAL_FILE="$EVAL_DIR/$DATE.md" # Write the template with today's date cat > "$EVAL_FILE" << 'EOF' # PA Weekly Eval — DATE_PLACEHOLDER [Fill in the template above] EOF # Replace the placeholder with the real date (works on Linux and macOS) sed -i "s/DATE_PLACEHOLDER/$DATE/" "$EVAL_FILE" 2>/dev/null \ || sed -i '' "s/DATE_PLACEHOLDER/$DATE/" "$EVAL_FILE" echo "Created eval file: $EVAL_FILE" ``` --- ## Owner Feedback Signals Log these automatically when detected: | Signal | Action | |---|---| | 👍 reaction | Log +1 positive | | 👎 reaction | Log -1 negative, record the correction | | "תודה" / "great" / "perfect" | Log +1 positive | | "wrong" / "fix this" / "לא טוב" | Log -1, record the correction | | Owner re-asks the same question | Log -1 memory gap | | Owner does the task themselves | Log -1 initiative gap | | Owner surprised by proactive action | Log +2 proactivity | **Rule:** If a signal appears → log it immediately. Don't batch feedback signals. --- ## Monthly Report Format ```markdown # PA Performance Report — [Month Year] **PA Name:** [Name] **Owner:** [Owner Name] **Period:** [Start] – [End] ## Summary Score: X/40 ([Grade A/B/C/D]) ## Dimension Breakdown [Copy scores table here] ## Key Wins - ## Key Issues - ## Trend vs Last Period - Score change: +X / -X points - Best improvement: [dimension] - Biggest regression: [dimension] ## Recommended Actions 1. 2. 3. ``` --- ## Benchmark Tests (Run Monthly) ### Task Completion Rate - Count tasks assigned in last 30 days. - Count completed without follow-up. - Formula: `completed / assigned × 100%` - Target: >90% ### Accuracy Rate - Count tasks that required correction. - Formula: `(tasks - corrections) / tasks × 100%` - Target: >95% ### Memory Retention - Ask about something discussed 7+ days ago. - Pass if recalled correctly, Fail if missed. - Target: >80% --- ## Cost Tips - **Cheap:** Filling in the weekly template — any small model works. - **Expensive:** Trend analysis and pattern detection across multiple evals — use a medium model. - **Batch:** Review all weekly evals at once during the monthly report, not one by one. - **Avoid:** Don't re-score historical weeks — score in real time and save to file.

path: DEPRECATED.md
content: # DEPRECATED — pa-eval

**Status:** Merged into eval/SKILL.md
**Date:** 2026-04-02
**Reason:** pa-eval and eval had 80% overlap. Both ran scoring and generated reports. eval now covers PA performance + system health in one pass.
**Lesson:** When two skills share the same output format and trigger, merge them. Scope can be a section, not a separate file.
**Moved to:** eval/SKILL.md — Section "PA Performance Scoring"


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)