monitor-experiments

monitor-experiments is a skill for Claude Code from amplitude/mcp-marketplace. It costs 69 tokens per session (3,206 once invoked), scanned A, a copy of monitor-experiments-consolidated, MIT.

An experiment-monitoring workflow that reviews active and recently finished product experiments in Amplitude. It ranks experiments by importance and produces a plain-language report with findings and actions.

In plain words
What is it for?
Checking experiment status, reviewing what is running, monitoring completed tests, and preparing periodic experiment reports. It also identifies experiments that need setup or follow-up.
Why use it?
It removes the need to inspect every experiment separately and makes urgent results easier to spot. The report gives a concise overview before providing more detail on experiments needing attention.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the amplitude plugin — 37 skills shipped together

Good fit Checking experiment status, reviewing what is running, monitoring completed tests, and preparing periodic experiment reports. It also identifies experiments that need setup or follow-up.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/amplitude/mcp-marketplace/monitor-experiments
Install

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.

Any agent
npx skills add amplitude/mcp-marketplace --skill monitor-experiments
Clone the repo
git clone --depth 1 https://github.com/amplitude/mcp-marketplace

Made for: Claude Code.

Or install amplitude, the plugin that ships this one along with the rest of its 37 skills.

Wrote 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.

agentmods badge for monitor-experiments

README.md
[![agentmods](https://agentmods.dev/badge/skills/amplitude/mcp-marketplace/monitor-experiments/github.svg)](https://agentmods.dev/skills/amplitude/mcp-marketplace/monitor-experiments)
Your own site
<a href="https://agentmods.dev/skills/amplitude/mcp-marketplace/monitor-experiments"><img src="https://agentmods.dev/badge/skills/amplitude/mcp-marketplace/monitor-experiments/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.

agentmods 80×15 button for monitor-experiments

Your own site · 80×15
<a href="https://agentmods.dev/skills/amplitude/mcp-marketplace/monitor-experiments"><img src="https://agentmods.dev/badge/skills/amplitude/mcp-marketplace/monitor-experiments.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,206 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 91% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00069 $0.03206
Opus 5 $0.00034 $0.01603
Sonnet 5 $0.00014 $0.00641
Haiku 4.5 $0.00007 $0.00321

Measured 9d ago against content hash 3b521a53a27b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

monitor-experiments 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.

Origin

This is a copy

91% identical to monitor-experiments-consolidated — 24 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/amplitude/skills/monitor-experiments/SKILL.md · 306 lines

How it starts

The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Experiment Monitor & Report Generator

Scan active and recently completed experiments, surface what needs attention, and report on the ones that matter.

This is a monitoring skill — keep output accessible to non-experts. Avoid statistical jargon (no p-values, no power analysis). For deep-dive analysis of a specific experiment, use the analyze-experiments skill instead.


CRITICAL: Managing Response Sizes

  1. get_experiments: 3-5 IDs max per call. Filter using search results BEFORE fetching.
  2. query_experiment responses are large. Extract only summary objects and validity flags. Ignore timeseries, xValues, bulk arrays.
  3. Metric name resolution: search does NOT match metric IDs in queries. Search with entityTypes: ["METRIC"], empty queries, limitPerQuery: 50, scoped to project. Match IDs from results.

Report Structure

The report has two parts:

  1. Summary & Actions (top) — One table + action items. Someone should be able to read just this and know the full picture.
  2. Details (bottom) — Deep-dives on experiments that need attention, briefs on recently decided, one-liners for monitoring experiments, and a needs-setup list.

Do NOT duplicate information between the summary table and the details. The summary table is the single source of truth for the portfolio state. Details expand on specific experiments.


Instructions

Step 1: Context & Discovery

  1. Call Amplitude:get_amplitude_context. If multiple projects, ask which to monitor.
  2. Search for experiments:
Amplitude:search({
  entityTypes: ["EXPERIMENT"],
  appIds: [projectId],
  queries: [],
  sortOrder: "lastModified",
  sortDirection: "DESC",
  limitPerQuery: 50
})
  1. Filtering rules — include experiments that are:
    • Running and not stale: Any experiment in a running state that is NOT marked as stale. Stale experiments have gone idle and should be excluded.
    • Recently decided: Completed experiments that have a decision recorded AND were modified within the last 14 days. These are worth reviewing to confirm the decision or share learnings.
  2. Exclude: Drafts, disabled experiments, and stale experiments.

Read the full file on GitHub · 306 lines

Changes

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.

  1. 9d ago First seen · 306 lines · 69 tokens per session scan A 3b521a53a27b

Subscribe to this mod's changes

monitor-experiments is a skill published in the GitHub repository amplitude/mcp-marketplace (35 stars, last pushed today), licensed MIT. It adds 69 tokens to every session and 3,206 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to monitor-experiments-consolidated, differing in 24 lines, and is treated as a copy.

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