List applications

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered, and an output schema exists. The description still adds real value by disclosing the compact one-line-per-application projection, which is why an agent picks this over get_application. It stops short of mentioning the default 100-row cap or any truncation behavior beyond the limit parameter.

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?

Four short sentences, front-loaded with purpose and output shape, followed by filter affordances and then sibling routing. No filler and nothing buried.

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 a fully documented schema and an output schema covering return values, the remaining burden is scope and routing — both fully handled. Nothing an agent needs to call this correctly is missing.

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 all six parameters are self-documenting. The description's sentence about filtering by status, company/role text, submit dates, and open-only merely restates those parameters in prose without adding syntax or edge-case guidance. Baseline 3 applies.

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 a specific verb and resource ('Browse the job applications in the tracker') and immediately defines the shape of what comes back ('one line each: row, company, role, status, submit and follow-up dates'). This makes it clearly distinguishable from get_application, which returns every column of a single row.

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?

Explicitly routes to alternatives by task: 'For every column of one row use get_application. For counts use summary or funnel, and for what is due use followups_due.' It also lists the filter dimensions inline, so the agent knows which narrowing options exist before opening the schema.

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