Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill monthly-reviewgit clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-MonitorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/monthly-review)<a href="https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/monthly-review"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/monthly-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/monthly-review"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/monthly-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.00827 |
| Opus 5 | $0.00036 | $0.00413 |
| Sonnet 5 | $0.00015 | $0.00165 |
| Haiku 4.5 | $0.00007 | $0.00083 |
Grade A, and why
monthly-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monthly Review
Generate a month-over-month productivity retrospective from Agent Monitor data.
Input
The user provides: $ARGUMENTS
This may be:
- "this month" or empty (default: the current calendar month to date)
- "last month" for the previous full calendar month
- A specific month: "2026-02" or "February 2026"
The comparison period is always the immediately preceding calendar month.
Data Sources
| 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) |
Report Sections
1. Month at a Glance
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).
2. Top Projects (by cwd)
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.
3. Cost & Token Breakdown
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.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 79 lines · 73 tokens per session scan A eecc7a4888e9
monthly-review is a skill published in the GitHub repository hoangsonww/Claude-Code-Agent-Monitor (991 stars, last pushed 3d ago), licensed MIT. It adds 73 tokens to every session and 827 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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