Mtr
mtrHackerTarget mtr lookup.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| target | Yes |
mtrHackerTarget mtr lookup.
| Name | Required | Description | Default |
|---|---|---|---|
| target | 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?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. However, the description adds no behavioral context beyond the annotations—it does not mention external service dependencies, rate limits, or any side effects. It is consistent with annotations but adds no value.
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 short but under-specified rather than concise. A single phrase like 'HackerTarget mtr lookup' does not earn its place because it provides no meaningful information. This is closer to a placeholder than a well-structured description.
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?
With a single parameter, no output schema, and minimal annotations, the description still fails to provide essential context such as what mtr does, what kind of output to expect, or how it differs from the sibling 'traceroute' tool. It is minimally viable but leaves major gaps for an agent trying to decide when to invoke it.
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 0%, so the description must compensate for the undocumented 'target' parameter. The description only says 'HackerTarget mtr lookup' and fails to explain what the 'target' should be (e.g., IP address, hostname, domain). This is completely inadequate for an agent to understand how to fill the parameter.
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 'HackerTarget mtr lookup.' is essentially a tautology, restating the tool name 'mtr' and adding 'lookup' without explaining what mtr does. It does not distinguish this tool from siblings like 'traceroute' or 'dns_lookup'. The verb 'lookup' is present but the resource is unclear.
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 provides no guidance on when to use this tool versus alternatives such as 'traceroute' or 'ping'. There is no mention of context, prerequisites, or exclusions. The agent is left without any information to select this tool correctly.
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.
Tools like ask_pipeworx, ask_pipeworx_grounded, deep_research, and entity_profile have overlapping purposes, causing potential confusion. However, their descriptions provide some differentiation, so an agent can usually pick the right one with careful reading.
Naming is highly inconsistent: mixes verb_noun (ask_pipeworx), noun_verb (reverse_dns), single-word (geoip), and compound phrases (generate_llms_txt). No clear pattern, making it hard for an agent to predict tool names.
44 tools is overwhelmingly high for a single server. The set mixes unrelated domains (network tools, data APIs, memory, prediction markets), suggesting it's a grab bag rather than a focused toolkit.
The server lacks a coherent domain, so evaluating completeness is difficult. There are many lookup tools but few for updates or deletes (except memory). The HackerTarget subset is sparse, and the overall surface feels incomplete for any single purpose.