Bot traffic on a site - DevDome separates every hit into human vs bot. kind 'bots' = known-bot catalog activity; 'threats' = suspicious/behavioral detections.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| kind | No | ||
| site | Yes |
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?
No annotations are provided, so the description carries the full burden of explaining behavior. It adds value by defining 'bots' as known-bot catalog activity and 'threats' as suspicious/behavioral detections, but it never discloses what the returned report contains, default behavior when kind/days are omitted, or time-window handling.
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?
Two compact sentences with no filler; the first scopes the subject to a site's bot traffic and the second unpacks the otherwise-cryptic kind parameter. The dash/semicolon compression is slightly dense, but the description stays well within an appropriate size.
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?
There is no output schema and no annotation coverage, so the description alone must let an agent predict the call's result. It never states the response shape (counts, percentages, time series), the effect of omitting kind or days, or the meaning of the days window, which is a real gap for a report tool.
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?
With 0% schema description coverage, the description must compensate, and it does for 'kind' by explaining the meaning of both enum values. It adds nothing for 'days' (units/range/default) or 'site' beyond the obvious, leaving two of three parameters under-documented.
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 lead phrase 'Bot traffic on a site' names the resource and domain, and the kind definitions clarify what the report distinguishes. The retrieval verb is only implied by the tool name rather than stated in the description, and it does not contrast with the sibling get_breakdown, so it misses full sibling differentiation.
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 the tool is for querying bot-traffic data for a given site and gives meaning to the two kind filters, which helps an agent decide whether bots or threats are wanted. However, it never states when to prefer this over get_breakdown or provides any exclusion criteria, so usage guidance is implied rather than explicit.
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.