linkedin_get_application_history

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds useful behavioral context by noting the data source ('submitted through this server') and scope ('including the answers given and any failures'), which goes beyond the annotations and helps the agent understand the tool's limitations and output contents.

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 sentences long, front-loaded with the primary action, and the second sentence adds an important differentiation without fluff. Every word earns its place, making it efficient and easy to parse.

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 filtered-list tool with strong annotations and full parameter schema documentation, the description is complete. It covers the purpose, data source, content scope, and a key alternative, leaving no major gaps for the agent to invoke it correctly.

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?

Both parameters (since and status) have full descriptions in the schema, yielding 100% schema coverage, so the schema already explains the parameter semantics. The description does not independently elaborate on parameters, so the baseline 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 tool lists applications submitted through this server, including answers and failures, using a specific verb 'List' and resource 'applications'. It also distinguishes itself from the sibling tool linkedin_get_applied_jobs by pointing to that tool for LinkedIn's authoritative record, making the purpose precise.

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 names an alternative tool (linkedin_get_applied_jobs) for a different use case, providing a clear exclusion. It implies the primary use case is for server-local application history with answer and failure details, which gives context on when this tool is appropriate.

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