healthchecksio_list_pingsList a check's logged pings (100 on the free plan, 1000 on paid), most recent first. Each ping: type, date, n, scheme, remote_addr, method, ua, rid, duration, body_url. Healthchecks: GET /checks/{uuid}/pings/.
| Name | Required | Description | Default |
|---|---|---|---|
| uuid | Yes | The check's UUID. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, and the description adds meaningful behavioral context: free vs paid plan limits, ordering by most recent first, and the exact set of fields per ping. It does not contradict annotations and goes beyond what the structured data already reveals.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is tightly packed in two sentences plus an endpoint reference. Every element adds value: plan limits, ordering, returned fields, and the underlying API call. No filler or repetition is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only listing tool with one required parameter, the description covers the operation, the response fields, ordering, and limits. No output schema exists, but the listed ping fields compensate well, making the tool safely callable by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single uuid parameter, and the schema already explains it as 'The check's UUID.' The description adds the endpoint template but no new semantic meaning for the parameter, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource ('List a check's logged pings'), distinguishes pings from sibling tools like list_flips and get_ping_body, and enumerates the returned fields. The endpoint mention further grounds the operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: it lists all logged pings for a single check, returns them most-recent-first, and indicates plan-based limits. It does not explicitly name alternatives or when-not-to-use, but the context is sufficient for this simple list operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool maps to a distinct resource and action: check CRUD, pause/resume, pings, flips, badges, and integrations. The only potentially related pair, list_pings and get_ping_body, is clearly separated by metadata vs raw body.
All tools follow a clean verb_noun snake_case pattern, with list_* for collections and get_/create_/update_/delete_/pause_/resume_ for single-resource actions. There are no mixed casing styles or inconsistent verb choices.
12 tools is well within the ideal range for this domain, and each tool covers a distinct, necessary operation for managing and inspecting Healthchecks monitoring. The set feels complete without being bloated.
The check lifecycle is fully covered with create, get, update, delete, pause, and resume, plus history and supporting data like pings, flips, badges, and integrations. The main minor gap is that there is no tool to send a ping or manually trigger a check success/failure, so end-to-end ping verification must happen out-of-band.