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Get Started Free →Compile a month-over-month retrospective from Agent Monitor data — sessions, cost, token volumes, completion rate, top projects by working directory, and notable shifts versus the prior month. Uses daily_sessions/daily_events (365d) from analytics, the session list, and the pricing cost breakdown. Use when doing a monthly retrospective or planning the month ahead.
.claude/skills/hoangsonww-monthly-review/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-10 | ✗→✓ | ▲ Improved | -18% | 0% |
| case-16 | ✗→✓ | ▲ Improved | -16% | 0% |
| case-13 | ✗→✓ | ▲ Improved | -13% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -19% | 0% |
| case-21 | ✗→✓ | ▲ Improved | 100% | 0% |
Generate a month-over-month productivity retrospective from Agent Monitor data.
The user provides: $ARGUMENTS
This may be:
The comparison period is always the immediately preceding calendar month.
| Endpoint | Returns | |----------|---------| | GET /api/analytics | daily_sessions and daily_events (365d) for monthly bucketing and trends; tokens (total_input/output/cache_read/cache_write — baselines pre-summed); tool_usage (top 20); sessions_by_status | | GET /api/sessions?limit=500 | Sessions with started_at, ended_at, status, model, cwd, cost, and metadata (turn_count, thinking_blocks) — for per-project (cwd) grouping and completion rate | | GET /api/pricing/cost | total_cost and per-model breakdown (input/output/cache tokens, cost, matched_rule) |
Compare the target month to the prior month in a table:
| Metric | This Month | Last Month | Change | |--------|-----------|------------|--------| | Sessions | N | N | ▲/▼ N% | | Total Cost | $X.XXXX | $X.XXXX | ▲/▼ N% | | Tokens (in/out/cache) | N | N | ▲/▼ N% | | Completion Rate | N% | N% | ▲/▼ N pts | | Active Days | N | N | ▲/▼ |
Derive monthly buckets from daily_sessions / daily_events. Completion rate = completed sessions / total sessions for the month (from sessions_by_status and the filtered session list).
Group the month's sessions by cwd. For the top 5–8 projects, list session count, total cost, completion rate, and dominant model. Note any project that newly appeared or dropped off versus last month.
From /api/pricing/cost, show cost per model and the dominant token type. Compute cache hit rate = total_cache_read / (total_cache_read + total_input) and compare to last month. Currency to 4 decimals.
From tool_usage, highlight the tools that rose or fell most month-over-month, and any new tool adopted. Flag rising error/Compaction activity if present.
Three to five plain-language observations: what changed, why it likely changed, and what it implies (e.g., "cost up 22% but sessions flat → heavier per-session work").
Two to four prioritized, actionable goals grounded in the numbers above.
Other measured skills in the registry, with their headline benchmark lift.