review-intelligence-mcp-server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, indicating a safe read operation. The description adds the specific output fields (ratings, pros, cons, use cases), which gives more detail than the annotations alone. It does not discuss limitations like pagination or rate limits, but for a simple read-only tool this is acceptable.

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 concise and well-structured: a single purpose sentence followed by a documented argument list. Every element contributes to understanding the tool 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 tool's simplicity (2 parameters, no output schema, read-only), the description covers all necessary aspects: what it does, what it returns, and how to pass arguments. No significant gaps remain.

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 description fully explains both parameters: 'product' is specified as a software product name with an example, and 'max_results' is described as max reviews with a default value. Since the schema has no descriptions (0% coverage), the description carries the full explanatory burden and does so effectively.

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 G2 software reviews and specifies the return content (ratings, pros, cons, use cases). It uses a specific verb ('Get') and names the resource ('G2 software reviews'), which differentiates it from sibling tools like Trustpilot and Yelp.

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 usage when G2 reviews are needed, providing clear context. However, it does not explicitly mention alternatives or when not to use the tool, but for a single-purpose review fetcher, the context is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, and the description adds useful information about return content (ratings, text, dates). However, it lacks behavioral details such as pagination, ordering, error handling, or rate limits. No contradiction between description and 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 extremely concise, with a single purpose sentence and a compact arg list. Every word adds value, and the most important information is front-loaded.

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 simple two-parameter tool with read-only annotations, the description covers purpose, parameters, and return fields adequately. It falls slightly short by not offering explicit sibling tool comparison, but this is a minor gap given the tool's simplicity.

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 0%, but the description fully compensates by explaining both parameters: 'company' accepts a name or URL slug with an example, and 'max_results' is described as max reviews with a default. This provides semantic meaning beyond the bare schema.

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 and resource: 'Get Trustpilot reviews for a company.' It also mentions the return fields (ratings, review text, dates), which provides a complete purpose. The platform-specific name and description distinguish it from sibling tools like g2_reviews and yelp_reviews.

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 usage is implied through the platform name and description, but there is no explicit guidance on when to use this tool versus the sibling review tools. No exclusions or alternatives are mentioned, so the agent must infer that this is for Trustpilot reviews.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare readOnlyHint and openWorldHint, so the safety profile is already known. The description adds context about return fields (ratings, review text, photos) and max_results default, which are behavioral details not present in the annotations. No contradictions detected.

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 compact and front-loaded with the main purpose, followed by a clear, well-formatted argument list. No redundant or unnecessary information is present; every sentence contributes to understanding the tool.

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?

With no output schema, the description mentions return fields but does not specify whether the result is a list or a single review, nor the overall structure. The max_results parameter implies a list, but this could be explicit. Overall, it's reasonably complete for a simple read-only search tool.

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?

All three parameters are fully documented in the description with examples and defaults, compensating for the 0% schema description coverage. This goes beyond the schema by explaining what 'business' means (name or type), giving example values, and specifying the default for max_results.

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 'Get Yelp business reviews' with a specific verb and resource, and lists return contents (ratings, review text, photos). This effectively differentiates from sibling tools like g2_reviews and trustpilot_reviews by naming the platform.

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 usage through the 'business' and 'location' parameters, but it doesn't explicitly state when to use this tool over alternatives (e.g., 'use for Yelp reviews only'). No exclusions or alternative tool references are provided, leaving the choice somewhat implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.