> 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.
npx skills add https://github.com/hoangsonww/Claude-Code-Agent-Monitor --skill monthly-review
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.
Expert startup business analyst specializing in market sizing, financial modeling, competitive analysis, and strategic planning for early-stage companies. Use PROACTIVELY when the user asks about market opportunity, TAM/SAM/SOM, financial projections, unit economics, competitive landscape, team planning, startup metrics, or business strategy for pre-seed through Series A startups.
This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests organizational design and headcount planning for a startup.
End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and publication figures (scientific-visualization). Use whenever the user has bulk RNA-seq reads or quant output and wants a complete, reproducible differential-expression workflow — e.g. "analyze my RNA-seq", "FASTQ to DESeq2", "run nf-core/rnaseq", "STAR/Salmon quantification", "build a counts matrix for DESeq2", or "go from reads to differentially expressed genes and enriched pathways". Routes between an nf-core/rnaseq (Nextflow) path and a standalone STAR/Salmon path, and covers experimental design, strandedness, and QC gates. For single-cell RNA-seq use the scanpy skill instead.
Generate project status reports from Jira issues and publish to Confluence. When an agent needs to: (1) Create a status report for a project, (2) Summarize project progress or updates, (3) Generate weekly/daily reports from Jira, (4) Publish status summaries to Confluence, or (5) Analyze project blockers and completion. Queries Jira issues, categorizes by status/priority, and creates formatted reports for delivery managers and executives.
Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.
Google Workflow: Today's meetings + open tasks as a standup summary.
Read event data from a Google Sheets spreadsheet and create Google Calendar entries for each row.
Create professional, dark-themed SVG diagrams of any type — architecture diagrams, flowcharts, sequence diagrams, structural diagrams, mind maps, timelines, illustrative/conceptual diagrams, and more. Use this skill whenever the user asks for any kind of technical or conceptual diagram, visualization of a system, process flow, data flow, component relationship, network topology, decision tree, org chart, state machine, or any visual representation of structure/logic/process. Also trigger when the user says "画个图" "画一个架构图" "diagram" "flowchart" "sequence diagram" "draw me a ..." or uploads content and asks to visualize it. Output is always a standalone .svg file.
Take hoangsonww/monthly-review from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.