Reverse Ip
reverse_ipHackerTarget reverse_ip lookup.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| target | Yes |
reverse_ipHackerTarget reverse_ip 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 indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. However, the description adds no behavioral context beyond naming the HackerTarget source. It does not mention potential rate limits, external API dependencies, or response format, which are not disclosed by annotations.
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. It restates the tool name and fails to convey necessary details, making it more of a placeholder than a concise, informative description. Every word does not earn its place because the sentence lacks substantive content.
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?
Given the tool's simplicity (one parameter, no output schema) and the available annotations, the description is incomplete. It does not clarify what input the tool accepts or what output it produces, making it difficult for an agent to select and invoke it correctly without prior knowledge.
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 schema has one required parameter 'target' with no description, and schema description coverage is 0%. The tool description also fails to explain what 'target' should contain (e.g., an IP address) or its format. This leaves the agent without essential parameter semantics.
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 reverse_ip lookup.' is essentially a restatement of the tool name, with only the addition of the data source (HackerTarget). It does not explain what a reverse IP lookup does, what it returns, or how it differs from similar tools like reverse_dns.
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?
No usage guidance is provided. The description does not state when to use this tool, what input is expected, or how it compares to alternatives such as reverse_dns, dns_lookup, or as_lookup. The agent must infer usage entirely from the tool name.
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.