Use this when a ChatGPT user asks about EntangleEQ, Egapro, Directive UE 2023/970, pay transparency, Inclusion Depth Score, or EntangleEQ public product information. Returns public pages only.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum results to return. Default 5. | |
| query | Yes | Search query about EntangleEQ public content. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool returns public pages and implies it's a read-only search. This is adequate for a simple search tool, though additional details (e.g., pagination) could enhance transparency.
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 two sentences, front-loaded with the essential usage context, and every word earns its place. No redundancy or fluff.
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 (2 params, no output schema), the description is fairly complete. It covers what the tool does and when to use it. Minor details like result ordering or pagination are missing but not critical.
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 coverage is 100%, with descriptions for both parameters. The description adds no additional meaning beyond the schema; thus, baseline 3 is appropriate. The schema already clearly defines the query and limit 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 clearly states the tool's purpose: to search for information about specific topics (EntangleEQ, Egapro, etc.) and return public pages. It distinguishes itself from siblings by specifying the content domain, though it doesn't explicitly contrast with each sibling.
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 explicitly says 'Use this when...' providing clear usage context with specific topics. It also notes 'Returns public pages only,' implying limitations. However, it does not mention when not to use it or alternatives, but sibling differentiation is implicit.
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 has a clearly distinct purpose: readiness assessment, page fetching, demo request, search, and index simulation. No ambiguity or overlap.
Naming is mixed: some use snake_case (assess_readiness, simulate_index_2027), others are single words (fetch, search) or verb_noun (request_demo_lead). While readable, the pattern is inconsistent.
Five tools is well-scoped for the domain of pay transparency and demo requests. Each tool earns its place without redundancy.
The tool surface covers the key workflows: readiness check, public information retrieval (search + fetch), demo request, and index simulation. No obvious gaps for the stated purpose.
