list_sites
List the websites on this DevDome account with their verification status.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List the websites on this DevDome account with their verification status.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden of disclosing behavior. It discloses the return concept (websites with verification status) and the scope (DevDome account), but it does not state whether the output is paginated, whether it includes all sites or only active ones, or whether the verification status is live-checked or cached. This is acceptable for a simple list operation but lacks deeper behavioral context.
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 a single short sentence with no filler. It front-loads the action ('List'), specifies the resource ('websites'), scopes it ('on this DevDome account'), and adds the key output field ('verification status'). Every word 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 zero-parameter list tool with no output schema, the description is largely complete: the agent knows what resource is returned and what key attribute is included. The main missing piece is whether verification status is the only attribute and whether any filtering or sorting options exist, but with no parameters required, an agent can call this tool confidently without further context.
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?
The input schema has zero parameters, so there are no parameter semantics to document. The description compensates by clarifying the implicit account scope and the output fields, making the tool's inputs effectively nonexistent. Baseline 4 is appropriate because there are no params to explain.
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 uses specific language: it lists websites on the DevDome account and includes verification status. It clearly identifies the resource and the operation, and it distinguishes itself from siblings like verify_site and add_site by focusing on listing rather than modifying. However, it does not explicitly contrast with sibling tools, so there is room for slight improvement.
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 implies a read-only listing context and mentions the account scope ('on this DevDome account'), which helps an agent know when to call it. It does not explicitly state when not to use it or point to alternatives like get_site_health for site details or verify_site for verification actions, but the context is reasonably clear for a simple zero-parameter tool.
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 targets a distinct resource or analytical view: site management (add/list/verify) is cleanly separated from analytics (stats, timeseries, visitors, realtime, bot report, breakdown, health). Even the traffic-related getters differ clearly by granularity and intent, so an agent is unlikely to confuse them.
The naming follows a consistent verb_noun pattern: add_site, list_sites, verify_site, and all analytics tools use get_<noun>. This makes the toolset predictable and easy to navigate.
Ten tools is well-scoped for an analytics product, covering both site administration and multiple data views without redundancy or bloat. Each tool earns its place in the API surface.
The core site lifecycle is covered (add, list, verify), and the analytics side is thorough with stats, timeseries, breakdown, realtime, visitors, bot reports, and health. Minor gaps exist, such as no remove/update site or deeper filtering options, but agents can complete typical workflows without dead ends.