Compare the NES coherence signal for several brands side by side (claim, reality, divergence for each). Presents the data; it does NOT recommend one brand over another. The caller decides.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | Brand URLs or domains to compare (up to 8). |
| Name | Required | Description | Default |
|---|---|---|---|
| brands | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only adds that the tool 'does not recommend', but does not disclose read-only behavior, auth needs, rate limits, or any side effects. Inadequate for a mutation-ambiguous context.
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 succinct sentences with no filler. Front-loaded purpose, then key caveat. Every sentence earns its place.
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 output schema exists, description does not need to detail returns. It covers the essential purpose and limitation. Could mention prerequisites or when to use the sibling, but it's adequate for a simple tool with one parameter.
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% and includes the 'up to 8' constraint. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
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?
Clearly states 'Compare the NES coherence signal for several brands side by side', which is a specific verb+resource+format. Distinct from sibling 'get_brand_coherence' which likely handles single brands.
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?
Implicitly indicates use for multi-brand comparison and clarifies it does not recommend. However, no explicit mention of when to use vs. sibling or when-not to use.
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.
Both tools have clearly distinct purposes: one compares multiple brands side by side, the other retrieves detailed coherence data for a single brand. There is no ambiguity between them.
Both tool names follow a consistent verb_noun pattern in snake_case: 'compare_brands' and 'get_brand_coherence'. The naming is predictable and uniform.
With only two tools, the server feels minimal. While it covers basic retrieval and comparison, additional tools for scanning brands or managing data would justify a broader scope.
The server lacks essential tools for creating or updating brand coherence data. There is no apparent way to scan a new brand, leaving the 'no read on file' message as a dead end.