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 time-of-daygit 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/time-of-day)<a href="https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/time-of-day"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/time-of-day/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/time-of-day"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/time-of-day.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 | $0.00074 | $0.00716 |
| Opus 5 | $0.00037 | $0.00358 |
| Sonnet 5 | $0.00015 | $0.00143 |
| Haiku 4.5 | $0.00007 | $0.00072 |
Grade A, and why
time-of-day 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Time of Day
Profile activity and productivity across the hours of the day and days of the week.
Input
The user provides: $ARGUMENTS
This may be:
- empty or "all" (default: all available sessions)
- a window like "last 30 days" or "last 90 days" to limit the analysis
- a project path to scope the analysis to one
cwd
Data Sources
| Endpoint | Returns |
|---|---|
GET /api/sessions?limit=500 |
Sessions with started_at, ended_at, status, cwd, cost, and metadata (turn_count, total_turn_duration_ms) — primary source for hour/weekday bucketing |
GET /api/events?session_id=X |
Events with timestamp and event_type (PreToolUse, PostToolUse, Stop, Compaction, APIError, etc.) — finer-grained activity within sessions and error timing |
GET /api/analytics |
daily_sessions / daily_events (365d) and sessions_by_status for trend context and completion baselines |
Report Sections
1. Activity by Hour of Day
Bucket sessions (by started_at) and events (by timestamp) into 24 hourly bins.
Show a text bar chart of session and event counts per hour. Identify the busiest
hours by raw volume.
2. Productivity by Hour of Day
For each hour bin, compute completion rate (completed / total sessions started in
that hour) and average sustained turn time
(total_turn_duration_ms / turn_count, ms → minutes). Distinguish "active" hours
(high volume) from "productive" hours (high completion + sustained turns).
3. Day-of-Week Pattern
Bucket the same metrics into 7 weekday bins. Table: weekday, sessions, completion rate, avg cost, dominant model.
4. Peak vs. Low-Output Windows
- Peak windows: hours/days with high completion rate and long sustained turns.
- Low-output windows: hours/days with high abandonment/error/Compaction rates
or fragmented short turns. Pull error timing from
/api/eventsevent types (APIError, Compaction) to corroborate.
5. Schedule Recommendation
Suggest which hour/weekday blocks to reserve for deep work and which to use for lighter or shallower tasks, grounded in the buckets above.
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 · 67 lines · 74 tokens per session scan A 3221ec116cc5
time-of-day is a skill published in the GitHub repository hoangsonww/Claude-Code-Agent-Monitor (991 stars, last pushed 3d ago), licensed MIT. It adds 74 tokens to every session and 716 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.
Other skills, from other repositories
commit-optimization
Use when configuring settings.json to reduce fuse-commit-pro's context token usage.
ideating
Generates and explores ideas. Use when capturing fleeting thoughts, brainstorming, exploring a problem space before committing to a direction, or reviewing stored ideas to decide what to pursue.
prime
Session prime — start a fresh session by reading project state to orient yourself. Use this when you have no project context yet or the user asks to "prime the session", "read state", or start work.
delegating-to-codex
Delegates a task to OpenAI Codex running as an interactive session in a herdr pane - uses the user's ChatGPT subscription, visible in herdr, steerable mid-session. Use when delegating work to codex, offloading a task to a GPT model (sol, terra, luna), or running a second opinion from a non-Claude frontier model. Not…
handoff
Capture current work context for handoff to another agent/developer. Gathers git state, todos, and modified files into a structured handoff document saved to the related spec folder.
notion-to-blog
Transfer a blog post from Notion to the Wasp blog. Fetches content, downloads and optimizes images, and creates a properly formatted MDX file.