Uuid
uuidRandom UUID.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | Response body with UUID | |
| status | No | HTTP status code | |
| content_type | No | Content-Type header |
uuidRandom UUID.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| body | No | Response body with UUID | |
| 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, and destructiveHint, so the description carries low burden. It adds no behavioral details beyond the fact that it returns a random UUID, which is consistent with 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?
Two words long, immediately front-loaded with the core purpose. Every word earns its place with zero redundancy.
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 an output schema, the description conveys exactly what the tool does. No additional information is necessary for correct invocation.
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?
Tool has zero parameters, so schema coverage is 100%. Description 'Random UUID' succinctly conveys what the tool outputs. Baseline for 0 parameters is 4, and description is adequate.
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?
Description 'Random UUID.' explicitly states the tool generates a random UUID, which is a specific verb+resource. It is clear and distinguishable from sibling tools, none of which are UUID-related.
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 guidance on when to use this tool versus alternatives. The description provides no context for decision-making, such as when UUID generation is appropriate.
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.