list_enginesList flagship public engines exposed by The Quiet Protocol.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| toolId | Yes | ||
| engines | Yes | ||
| limitations | Yes | ||
| methodology | Yes | ||
| nextStepUrl | Yes | ||
| canonicalUrl | Yes | ||
| evidenceType | Yes | ||
| systemMapping | Yes | ||
| inputAssumptions | Yes | ||
| canonicalPublicUrl | Yes | ||
| evidenceReferences | Yes | ||
| evidenceClassification | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds the 'flagship public engines' qualifier, which hints at a subset of engines but doesn't explain what qualifies as flagship or whether any pagination or ordering applies. It is a harmless list operation, but the description doesn't enrich the behavioral understanding beyond the 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, front-loaded sentence with no filler. Every word earns its place—'List', 'flagship public engines', 'exposed by The Quiet Protocol'—and it is immediately clear what the tool does.
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 (no parameters, read-only, output schema present), the description covers the essential purpose. It doesn't explain what 'flagship' means or if there are other engine categories, but for a basic list tool, it is adequate. The output schema exists, so return format is not needed in the description.
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, so there is nothing for the description to explain. The baseline for 0 parameters is 4, and the description does not introduce any confusing parameter expectations. It correctly mentions no parameters implicitly by listing the resource.
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 states a specific verb ('List') and resource ('flagship public engines') exposed by The Quiet Protocol. It is clear what the tool does and distinguishes from siblings like list_benchmarks or list_kits by referencing engines specifically. However, it does not explicitly contrast with those siblings, leaving a small gap in differentiation.
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 gives no guidance on when to use this tool versus alternative list tools. With many sibling tools (list_benchmarks, list_kits, list_resources, etc.), an explicit note about when to choose this one would be valuable. The context is implied but not stated, such as 'use this to see available engines'.
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.
Most tools have distinct purposes, with clear get/list/run patterns separating fetching, listing, and executing. A few tools like scan_ai_visibility and run_trust_stack_audit both scan websites but focus on different signals, so minor overlap exists but descriptions clarify boundaries.
All 29 tools consistently use snake_case with verb_noun structure (get_, list_, run_, scan_, select_, find_, pricing_lookup). The naming convention is uniform and predictable, making it easy to infer tool behavior.
With 29 tools, the server exceeds the typical comfortable range (16-25 is already heavy). While the domain is broad, the high count may overwhelm agents and increase selection complexity without clear benefit.
The server covers a comprehensive range of operations: listing, fetching, running diagnostics, scanning, and recommendations. It lacks CRUD operations, but as a read-only resource and diagnostic server, that's appropriate. Some minor gaps exist, but the core workflows are well covered.