healthchecksio_list_checksList all checks in the project, optionally filtered by slug and/or tags. Returns {checks:[...]} — each check's status, schedule, last ping, and ping URL. Healthchecks: GET /checks/.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | Filter to checks carrying ALL of these tags (each is sent as a separate `tag` query param). | |
| slug | No | Filter to checks with this exact slug. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only provide readOnlyHint, and the description adds meaningful detail: it returns {checks:[...]} and enumerates the per-check fields (status, schedule, last ping, ping URL). This gives the agent a concrete picture of the read-only response without contradicting the annotation.
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?
Three short sentences with no filler; the main purpose and filters are front-loaded, followed by the return shape and endpoint reference. Every sentence earns its place.
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 two fully documented optional parameters, the description is sufficient. It states output shape and key fields, and no pagination or side effects need to be disclosed given readOnlyHint=true. There is no output schema, but the description provides the essential return information.
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 coverage is 100%, so the schema already fully documents 'tag' and 'slug'. The description only lightly paraphrases the filters and adds no new meaning beyond 'and/or', matching the baseline rather than exceeding it.
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 names the specific operation ('List all checks in the project'), identifies optional filters, and contrasts naturally with sibling tools like get_check (single check) and list_pings. The action and resource are unambiguous.
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?
It clearly states the list scope and the optional slug/tag filters, so an agent knows when a filtered list is appropriate. It does not explicitly name alternatives or say when not to use it, such as routing single-check lookups to get_check, so it stops short of a 5.
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.