Ip
ipCaller IP (gateway egress).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | Response body with IP info | |
| status | No | HTTP status code | |
| content_type | No | Content-Type header |
ipCaller IP (gateway egress).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | Response body with IP info | |
| status | No | HTTP status code | |
| content_type | No | Content-Type header |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint true and destructiveHint false, establishing it as a safe, idempotent read. The description adds the specific context of 'gateway egress' but does not contradict 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 a single, concise phrase with no unnecessary words. Every word adds value.
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 tool with annotations and an output schema, the description 'Caller IP (gateway egress)' provides sufficient context to understand what the tool returns.
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 tool has zero parameters, and schema description coverage is 100%. The description does not need to add parameter details; baseline for no params is 4.
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 'Caller IP (gateway egress)' clearly states the tool returns the IP address of the calling client from the gateway egress perspective. It distinguishes itself from sibling tools by being the only IP-focused tool.
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 explicit guidance on when or when not to use, but given the lack of sibling alternatives for IP lookup, the usage context is implied. No exclusions are mentioned.
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.
Many tools serve overlapping purposes: ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim, entity_profile, compare_entities, and resolve_entity all perform data lookups with subtle differences. The prediction-market tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.) heavily overlap, and even the HTTP utilities (headers, ip, user_agent, cookies) echo similar request information. Agents will struggle to pick the right tool.
Naming is internally inconsistent: some tools use short imperative verbs (get, post, status, delay), others use long descriptive phrases (ask_pipeworx, entity_profile, scan_competitor_ai_presence). There is no common pattern—some are verb+noun, some noun+noun, some proper nouns. The mix of styles makes it hard to predict tool names.
47 tools is excessive for a server named Httpbin, which conventionally should have a handful of HTTP debugging utilities. Most tools are unrelated to HTTP (data lookups, prediction markets, memory, subscriptions), indicating severe scope creep. The count feels bloated and unwieldy.
For HTTP debugging, the set is incomplete—missing common methods (PUT, DELETE, PATCH) and error-handling features. For the broader data/proposition-market domain, coverage is fragmented and unclear. The server appears to be a jumble of partially complete feature sets with no coherent domain, leaving obvious gaps in each.