coherence-signal
Server Details
A brand's claim (website coherence) vs its reality (recent news), and the divergence.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.2/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one retrieves coherence data for a single brand, and the other compares multiple brands side by side. There is no ambiguity or overlap.
Both tool names follow a consistent verb_noun pattern in snake_case: compare_brands and get_brand_coherence. The naming is predictable and clear.
With only 2 tools, the server feels thin for its apparent domain. While the tools are focused, the count is borderline low; a broader set (e.g., listing brands, scanning) would be more appropriate.
The tool surface covers core operations (get and compare), but lacks discoverability—there is no way to list available brands or trigger scans. This is a notable gap that could hinder agents.
Available Tools
2 toolscompare_brandsAInspect
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). |
Output Schema
| Name | Required | Description |
|---|---|---|
| brands | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it presents data without recommending, but does not disclose other behavioral traits like read-only nature or data source freshness. It is adequate but leaves some gaps.
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, front-loaded with the core action, and no extraneous information. Every sentence adds value.
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 tool with one parameter and an output schema, the description is fairly complete. It explains what it does and what it does not do. The presence of an output schema means return values need not be explained. Minor gap: jargon 'NES coherence signal' might benefit from brief definition, but overall acceptable.
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 description coverage is 100%, so the schema already documents the sole parameter 'urls'. The description adds no additional meaning beyond what is already in the schema. Baseline score of 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?
The description clearly states the verb 'compare', the resource 'NES coherence signal for several brands', and specifies the output ('claim, reality, divergence for each'). It also distinguishes from the sibling tool by noting it compares multiple brands side by side.
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 it does not recommend one brand over another, which sets expectations. However, it does not explicitly state when to use this tool versus the sibling 'get_brand_coherence', though it's implied by the comparison functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_brand_coherenceAInspect
Get the NES claim-vs-reality coherence signal for one brand: its website coherence score (the claim), recent public reality (matched news events), and the divergence between them. High divergence means the brand presents as coherent while its reality is turning negative. Directional opinion from public signal; not a fraud or financial check. Returns 'no read on file' for brands never scanned.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Brand website URL or domain, e.g. https://acme.com | |
| brand | No | Brand name, used if no URL is given. |
Output Schema
| Name | Required | Description |
|---|---|---|
| brand | No | |
| claim | No | What the brand says about itself via its website. |
| reality | No | |
| divergence | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses the return of 'no read on file' for unscanned brands and clarifies it is not a fraud or financial check, providing adequate behavioral 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?
The description is two concise sentences, each adding value. It front-loads the core functionality and adds important caveats without 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?
Given the presence of an output schema and moderate complexity, the description covers the tool's purpose, return conditions, and limitations comprehensively. It leaves no major gaps.
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%, so baseline is 3. The description adds minimal value beyond schema descriptions, which already explain the parameters. The only addition is the context of 'one brand', but overall it does not significantly surpass schema info.
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 retrieves a coherence signal for one brand, covering website coherence, public reality, and divergence. It distinguishes from the sibling 'compare_brands' by focusing on 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 implies use for a single brand and adds caveats about directional opinion and limitations. It does not explicitly contrast with siblings, but context signals show only one sibling, making the usage clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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