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 must bear the full burden. It accurately describes the non-recommending behavior and the data presentation, but does not mention read-only nature or any other side effects, which is acceptable for a data presentation tool.
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 sentences, concise and front-loaded with the main purpose. No redundant information. Every word contributes.
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 (unseen but present) and the simplicity of input, the description sufficiently covers the tool's purpose and constraints. It could mention the output format briefly, but completeness is adequate.
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%, baseline 3. The description adds value by specifying the limit of up to 8 URLs and clarifying that they are brand URLs or domains, which goes beyond the schema's 'Brand URLs or domains to compare'.
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 compares brands side-by-side for NES coherence signal, listing specific outputs (claim, reality, divergence). This distinguishes it from sibling get_brand_coherence, which presumably handles a single brand.
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 states it presents data and does not recommend, guiding the agent to use it when only data is needed. It does not explicitly mention when to use the sibling tool, but the contrast is implied.
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: one compares multiple brands side by side, while the other retrieves detailed coherence data for a single brand. No overlap or ambiguity.
Both tools follow a consistent verb_noun pattern (compare_brands, get_brand_coherence), using snake_case throughout. The naming is predictable and clear.
With only 2 tools, the server feels minimal for the domain of brand coherence signals. Additional tools for scanning new brands or listing available brands would enhance coverage, but the current count is borderline acceptable.
The server lacks essential operations: there is no way to scan or add a new brand to the database, nor list which brands are already scanned. Users are limited to querying existing data, leaving clear gaps that hinder full workflow completion.