From daily-metrics
This skill should be used when the user asks to "review my week", "analyze my data", "what's working", "check progress", "weekly review", "monthly review", "look at my metrics", "show my trends", or wants to extract signal from tracked data and close the feedback loop.
npx claudepluginhub mberto10/mberto-compoundThis skill uses the workspace's default tool permissions.
Extract signal from noise and close the feedback loop between behaviors and outcomes.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Searches prompts.chat for AI prompt templates by keyword or category, retrieves by ID with variable handling, and improves prompts via AI. Use for discovering or enhancing prompts.
Guides MCP server integration in Claude Code plugins via .mcp.json or plugin.json configs for stdio, SSE, HTTP types, enabling external services as tools.
Extract signal from noise and close the feedback loop between behaviors and outcomes.
Tracking without review is wasted friction. This skill structures the review process to tighten feedback and enable data-driven iteration.
| Review Type | Frequency | Duration | Focus |
|---|---|---|---|
| Daily glance | Daily | 30 sec | Did I execute today? |
| Weekly review | Weekly | 10-15 min | Compliance + trends + adjustments |
| Monthly review | Monthly | 30-60 min | Target progress + system evaluation |
Quick check on today's execution:
No analysis. Just logging and awareness.
For each tracked behavior, calculate:
Compliance = (days executed / days intended) × 100%
| Behavior | Target Days | Actual | Compliance | Status |
|---|---|---|---|---|
| [name] | [N] | [n] | [%] | [OK/Review] |
Threshold: Flag anything below 80% for friction audit.
Low compliance is usually friction, not willpower.
Compare trends not snapshots:
This week vs. Last week vs. 4-week average
| Outcome | This Week | Last Week | 4-Week Avg | Trend |
|---|---|---|---|---|
| [metric] | [value] | [value] | [value] | [arrow] |
Ignore single-point fluctuations. Look for directional trends.
Ask: Are behavior changes producing outcome changes?
| Behavior Change | Expected Outcome | Actual | Conclusion |
|---|---|---|---|
| [change] | [expected] | [actual] | [working/investigate] |
Attribution is hard. Look for patterns over 4+ weeks.
Based on the data:
weekly_review:
week_of: [date]
domain: [domain]
compliance:
[behavior]: [%]
trends:
[outcome]: "[direction and value]"
insights:
- "[observation]"
next_week:
- "[focus area]"
For each defined target:
| Target | Baseline | Current | Goal | Progress | On Track? |
|---|---|---|---|---|---|
| [name] | [start] | [now] | [goal] | [%] | [Y/N] |
Questions to answer:
Which layer needs attention?
| Symptom | Layer | Action |
|---|---|---|
| Unclear success definition | Target | Re-run target-definition |
| Doing behaviors, no results | Algorithm | Research better approaches |
| Know what to do, not doing it | Friction | Run friction-audit |
| Not reviewing data | Feedback | Simplify review process |
SELECT
behavior_id,
COUNT(*) FILTER (WHERE value->>'completed' = 'true') as completed,
COUNT(*) as total,
ROUND(100.0 * COUNT(*) FILTER (WHERE value->>'completed' = 'true') / COUNT(*), 1) as compliance
FROM daily_logs
WHERE date >= CURRENT_DATE - 7
GROUP BY behavior_id;
SELECT
DATE_TRUNC('week', date) as week,
SUM((value->>'minutes')::int) as total_minutes
FROM daily_logs
WHERE behavior_id = '[behavior_id]'
GROUP BY week
ORDER BY week DESC
LIMIT 4;
SELECT
AVG((value->>'rating')::numeric) as avg_rating
FROM daily_logs
WHERE behavior_id = '[outcome_id]'
AND date >= CURRENT_DATE - 7;
When presenting review results: