Glassdoor Remote MCP Server

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

With no annotations, the description carries the burden of explaining behavior. It does list the returned fields and suggests practical use cases, but it does not mention potential limitations, error behavior, authentication, or rate limits. This is adequate for a simple fetch operation but not fully transparent.

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 reasonably concise and well-structured: a clear action sentence, a list of returned fields, and a list of use cases. The use-case list is somewhat broad but not excessive, and every sentence contributes useful context.

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 single-parameter tool with no output schema, the description gives enough context to invoke it correctly: what URL to provide, what data will be returned, and common scenarios where it is useful. It does not overpromise or omit critical invocation details.

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 only parameter, 'url', is fully described in the schema as 'The URL of the job vacancy to retrieve details for.' The tool description largely repeats this and adds no new parameter-level details, so the description adds minimal value beyond the 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?

States the specific action ('Fetches a Glassdoor job posting by its vacancy URL'), the resource (Glassdoor job posting), and the scope (details by URL). This clearly distinguishes it from the sibling listing tool and other job detail tools.

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 explains when to use the tool ('by its vacancy URL') and lists relevant use cases such as ATS ingestion, job aggregation, and LLM matching. It does not explicitly name the alternative listing tool or say 'use this when you already have a URL', but the condition is strongly implied.

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?

No annotations exist, so the description carries the burden. It discloses the return structure (array of jobs with specific fields and next page token) and pagination behavior. It does not mention authentication or rate limits, but for a read-only search tool this is acceptable; the description is not misleading.

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?

Three sentences, front-loaded with the core action and scoping. The return fields and use cases are listed efficiently with no filler. Each 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?

With no output schema, the description compensates by explaining the return array and pagination token. It covers purpose, usage, and routing to the details endpoint. It doesn't describe how to chain nextPageToken, but that's a minor gap given the clarity of the rest.

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 baseline is 3. The description merely echoes the parameters (sort, domain, nextPageToken) without adding new semantics or usage details beyond what the schema already states.

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 identifies the resource (Glassdoor job listings) and action (get/search). It distinguishes from the sibling details endpoint by mentioning 'downstream full-detail scraping via the Glassdoor Job endpoint', and from other platforms (Indeed, etc.) by naming Glassdoor explicitly.

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?

States explicit use cases ('build job feeds, monitor hiring trends...') and points to the alternative for full details ('collect URLs for downstream full-detail scraping via the Glassdoor Job endpoint'). This gives clear when-to-use and when-not-to-use guidance.

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