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 thousandeyes/thousandeyes-ai-agents-toolkit --skill thousandeyes-alert-rule-managementgit clone --depth 1 https://github.com/thousandeyes/thousandeyes-ai-agents-toolkitWrote 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/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-alert-rule-management)<a href="https://agentmods.dev/skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-alert-rule-management"><img src="https://agentmods.dev/badge/skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-alert-rule-management/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/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-alert-rule-management"><img src="https://agentmods.dev/badge/skills/thousandeyes/thousandeyes-ai-agents-toolkit/thousandeyes-alert-rule-management.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 | $0.00080 | $0.01724 |
| Opus 5 | $0.00040 | $0.00862 |
| Sonnet 5 | $0.00016 | $0.00345 |
| Haiku 4.5 | $0.00008 | $0.00172 |
Grade A, and why
thousandeyes-alert-rule-management 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ThousandEyes Alert Rule Management
Use this skill to manage ThousandEyes alert rules through the available MCP read and write tools. Align the user request to the official alert-rule docs and expression metadata, but only send fields that exist in the actual MCP tool schema.
Use This Skill When
- A user wants to list existing ThousandEyes alert rules
- A user wants to inspect one ThousandEyes alert rule by ID
- A user wants to create a new ThousandEyes alert rule
- A user wants to update an existing alert rule
- A user wants to delete an existing alert rule
- A user needs help translating ThousandEyes alert-rule UI concepts into MCP tool arguments
- A user needs help writing or validating an alert
expression
Required Behavior
- Inspect the alert-rule tool schema before using any of
list_alert_rules,get_alert_rule,create_alert_rule,update_alert_rule, ordelete_alert_rule. - Confirm the user intent first:
list,get,create,update, ordelete. - Treat
create_alert_rule,update_alert_rule, anddelete_alert_ruleas external write actions. Get explicit user confirmation before calling them. - Treat
list_alert_rulesandget_alert_ruleas read-only discovery tools. Use them without extra confirmation when they help identify the right rule or recover the current required fields for an update. - For
createandupdate, gather the required fields before proceeding:rule_name,expression,alert_type, androunds_violating_out_of. - For
get,update, anddelete, requirerule_id. - Do not invent tool arguments from the UI docs. If a UI concept is not exposed by the tool schema, say that clearly and stop or ask for a supported alternative.
- Validate
rounds_violating_required <= rounds_violating_out_ofbefore calling the tool. - If
rounds_violating_mode=auto, prefer an explicitsensitivity_level. - Use the expression guidance in reference.md when building or reviewing
expression. - Summarize the exact payload you plan to send before execution, then summarize the result after execution.
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.
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 · 130 lines · 80 tokens per session scan A deb34ec499fd
thousandeyes-alert-rule-management 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 80 tokens to every session and 1,724 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 2026-08-31.
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