thousandeyes-synthetic-monitoring

thousandeyes-synthetic-monitoring is a skill for Claude Code, Codex from thousandeyes/thousandeyes-ai-agents-toolkit. It costs 63 tokens per session (2,058 once invoked), scanned A, original, Apache-2.0.

A guide for managing ThousandEyes synthetic monitoring, which uses scheduled tests to check whether networks, applications, or browser journeys work from selected locations.

In plain words
What is it for?
Use it to inspect, create, update, delete, validate, or run one-time ThousandEyes tests, and to deploy application monitoring templates.
Why use it?
It helps choose the appropriate monitoring type and manage tests consistently through their full lifecycle.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the thousandeyes plugin — 4 skills, 1 MCP server shipped together

Good fit Use it to inspect, create, update, delete, validate, or run one-time ThousandEyes tests, and to deploy application monitoring templates.

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Install with agentmods
npx agentmods add skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-synthetic-monitoring
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 thousandeyes/thousandeyes-ai-agents-toolkit --skill thousandeyes-synthetic-monitoring
Clone the repo
git clone --depth 1 https://github.com/thousandeyes/thousandeyes-ai-agents-toolkit

Made for: Claude Code, Codex.

Or install thousandeyes, the plugin that ships this one along with the rest of its 4 skills, 1 MCP server.

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 thousandeyes-synthetic-monitoring

README.md
[![agentmods](https://agentmods.dev/badge/skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-synthetic-monitoring/github.svg)](https://agentmods.dev/skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-synthetic-monitoring)
Your own site
<a href="https://agentmods.dev/skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-synthetic-monitoring"><img src="https://agentmods.dev/badge/skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-synthetic-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.

agentmods 80×15 button for thousandeyes-synthetic-monitoring

Your own site · 80×15
<a href="https://agentmods.dev/skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-synthetic-monitoring"><img src="https://agentmods.dev/badge/skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-synthetic-monitoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,058 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 original No closer match found 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 $0.00063 $0.02058
Opus 5 $0.00032 $0.01029
Sonnet 5 $0.00013 $0.00412
Haiku 4.5 $0.00006 $0.00206

Measured 12d ago against content hash 7decbe99760c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

thousandeyes-synthetic-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.

plugins/thousandeyes/skills/thousandeyes-synthetic-monitoring/SKILL.md · 152 lines

How it starts

The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ThousandEyes Synthetic Monitoring

Use this skill to manage ThousandEyes synthetic monitoring through the available MCP tools. Treat synthetic monitoring as the umbrella workflow for creating, validating, updating, and deleting synthetic tests, and for deploying template-based monitoring for an application.

Use This Skill When

  • A user wants to list or inspect existing ThousandEyes synthetic tests
  • A user wants to create or update synthetic monitoring for an application or service
  • A user wants to delete one or more synthetic tests
  • A user wants to run a dynamic or ad hoc check before creating scheduled monitoring
  • A user wants to deploy a template-based monitoring configuration for an application
  • A user needs help deciding between Network and Application Synthetics and Browser Synthetics

Required Behavior

  1. Inspect the relevant ThousandEyes tool schema before using unfamiliar synthetic-monitoring tools.
  2. Confirm the user intent first: list, get, create, update, delete, instant-test, or deploy-template.
  3. Treat create_synthetic_test, update_synthetic_test, delete_synthetic_test, and deploy_template as external write actions. Get explicit user confirmation before calling them.
  4. Treat instant-test tools as execution actions for dynamic validation. Confirm before running them unless the user explicitly asked to run the check now.
  5. Use read-only discovery tools without extra confirmation when they help identify the right synthetic test, agent set, or application template.
  6. For update and delete, require both test_id and test_type.
  7. Do not invent tool arguments that are not exposed by the MCP tool schema.
  8. When the user gives only a test name, use discovery tools to recover the exact test_id and test_type before any write.
  9. Map the request to the correct product language first:
    • Network and Application Synthetics for network, API, DNS, and HTTP server-style monitoring
    • Browser Synthetics for page-load and transaction-style browser monitoring
    • Synthetic tests and templates for application monitoring workflows
  10. Summarize the exact payload or execution plan before running any write or instant action, then summarize the result after execution.

Read the full file on GitHub · 152 lines

Files

What ships with it

3 files 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.

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. 12d ago First seen · 152 lines · 63 tokens per session scan A 7decbe99760c

Subscribe to this mod's changes

thousandeyes-synthetic-monitoring is a skill published in the GitHub repository thousandeyes/thousandeyes-ai-agents-toolkit (3 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 63 tokens to every session and 2,058 once invoked, about $0.0003 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.

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