A
licenseA
qualityD
maintenanceSearch URDB's product integrity database — integrity scores, enshittification events, warranty cuts, and material downgrades across consumer products. Sourced and evidence-backed.
Last updated
4
44
2
MIT
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
A4/5.0
Tool DescriptionsA
Average 4.3/5 across 2 of 2 tools scored.
Server CoherenceA
Disambiguation5/5
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.
Naming Consistency5/5
Both tool names follow a consistent verb_noun pattern in snake_case: 'compare_brands' and 'get_brand_coherence'. The naming is predictable and uniform.
Tool Count3/5
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.
Completeness2/5
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.
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.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | Brand URLs or domains to compare (up to 8). |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| brands | No |
Tool Definition Quality
A3.8/5.0
Behavior2/5
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.
Conciseness5/5
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.
Completeness4/5
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.
Parameters3/5
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.
Purpose5/5
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.
Usage Guidelines4/5
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.
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.
ParametersJSON Schema
| 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
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| brand | No | |
| claim | No | What the brand says about itself via its website. |
| reality | No | |
| divergence | No |
Tool Definition Quality
A4.7/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and excels. It discloses the meaning of high divergence, that it's public directional opinion, not financial check, and the edge case of 'no read on file' for unscanned brands.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences, no wasted words. It front-loads the main purpose and provides necessary detail without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
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, output schema present), the description is complete. It covers return components and edge cases, making it sufficient for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds value by clarifying the relationship between url and brand parameters ('used if no URL is given'). This aids correct usage beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves the NES claim-vs-reality coherence signal for one brand, including website coherence score, recent public reality, and divergence. It distinguishes itself from the sibling tool compare_brands by specifically targeting single-brand analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (for a single brand's coherence signal) and provides important caveats (directional opinion, not fraud check). It could be improved by explicitly stating when to prefer compare_brands, but the context implies it.
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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