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 clamp-sh/analytics-skills --skill sequential-monitoringgit clone --depth 1 https://github.com/clamp-sh/analytics-skillsWrote 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/clamp-sh/analytics-skills/sequential-monitoring)<a href="https://agentmods.dev/skills/clamp-sh/analytics-skills/sequential-monitoring"><img src="https://agentmods.dev/badge/skills/clamp-sh/analytics-skills/sequential-monitoring/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/clamp-sh/analytics-skills/sequential-monitoring"><img src="https://agentmods.dev/badge/skills/clamp-sh/analytics-skills/sequential-monitoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00185 | $0.04250 |
| Opus 5 | $0.00093 | $0.02125 |
| Sonnet 5 | $0.00037 | $0.00850 |
| Haiku 4.5 | $0.00018 | $0.00425 |
Grade A, and why
sequential-monitoring 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 12d 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 — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sequential monitoring
A fixed-horizon A/B test promises a 5% false-positive rate at one planned read. The moment you check the result daily and stop "when it looks good", the actual false-positive rate climbs to 20-30%. Sequential testing fixes this: it lets you check as often as you like and stop the moment the evidence is strong enough, with the type-I error still controlled at the nominal alpha. This skill encodes when to apply mSPRT versus confidence sequences, how to read the boundaries, and when sequential math will not rescue an underpowered test.
When NOT to use this
- The test has fewer than ~400 exposed users per variant. Sequential methods do not manufacture power. At n<400 the boundaries are nowhere near being crossed and the honest answer is "wait, do not peek".
- The conversion metric has strong seasonality (B2B day-of-week, retail weekday/weekend, SaaS payday cycles) and the test has not run a full cycle. Sequential boundaries can cross on a Tuesday and uncross by Sunday; the math is valid but the decision is fragile.
- The user wants to design the test (sample size, MDE, variant logic) rather than read a running one. Different skill.
- The experiment was already declared with a fixed analysis plan and the team agreed to read it only at the end. Switching to sequential mid-flight is a governance decision, not a stats one; flag it and ask.
The peeking problem
A fixed-horizon test computes a p-value under the assumption you look once, at the planned end. Each additional peek is another chance to cross the 5% threshold by noise alone.
| Peeks across the test | Actual false-positive rate (nominal 5%) |
|---|---|
| 1 (end only) | 5% |
| 2 | ~8% |
| 5 (weekly) | ~14% |
| 10 (twice weekly) | ~19% |
| Daily over a month | ~25-30% |
If the user has been "checking how the test is doing" every morning, the nominal 5% threshold is meaningless. They need either a sequential method (always-valid) or alpha-spending (pre-commit to a peek schedule and inflate the threshold).
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.
- 12d ago First seen · 273 lines · 185 tokens per session scan A 7df46e0f4aed
sequential-monitoring is a skill published in the GitHub repository clamp-sh/analytics-skills (8 stars, last pushed 3mo ago), licensed MIT. It adds 185 tokens to every session and 4,250 once invoked, about $0.0009 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 2026-08-31.
Other skills, from other repositories
treat
Prune bloated session with a prescription. Removes progress ticks, stale reads, duplicate content, and more.
guard
Protect Claude Code sessions from context overflow by running a background daemon that monitors session size and auto-prunes before compaction hits. Use when the user says "guard", "protect session", "context getting long", "prevent compaction", "session management", or is running agent teams that need continuous…
cozempic-doctor
Run health checks on Claude Code configuration and sessions. Use when troubleshooting Claude Code issues. (cozempic — does not shadow Claude Code's built-in /doctor).
diagnose
Analyze Claude Code session bloat — shows token count, context usage %, and bloat breakdown. Use when the user asks about session size, context usage, or when you notice the context window is getting full.
reload
Treat the current session and auto-resume in a new terminal window.
radin-execute
Work through a project's whole backlog: prioritize every task, execute each via a sub-agent, commit after each. Use when the user wants the entire backlog processed ("work through my backlog"), not one named task. Delegates all implementation to sub-agents; clarifies ambiguity by asking the user rather than guessing.